A complete listing of approved research topics is provided below. Your Research Information Paper should be tailored to one of the listed topics. You may sort by Research Competency, Participation Type, or Research Facility Location. If you have questions regarding a specific topic, please reach out to the research advisor listed for the associated topic. General inquiries may be directed to ARLFellowship@orau.org.
Application Deadline: January 12, 2025
View this research opportunity and apply
| Advisor | Research Project Title | Detailed Project Description | Required Major(s) | |||
|---|---|---|---|---|---|---|
| Rebecca Renberg |
Biological & Biotechnical Sciences (BBS) | On-site | ALC - Adelphi Laboratory Center, MD | Environmental fungal characterization, genomics, and enzymes | Biological and Biotechnology Sciences division is seeking summer researchers to work on a fungal microbiology project. This project will entail culturing and characterizing an environmental fungal microorganism, performing ultra-high molecular weight genomic DNA extractions and long-read sequencing, and isolating and characterizing proteins/enzymes from the fungal organism. Previous laboratory experience in a microbiology/molecular biology lab is preferred, but not required. | Molecular Biology, Microbiology, Mycology, Genetics |
| Jessica Liba |
Biological & Biotechnical Sciences (BBS) | Hybrid | APG - Aberdeen Proving Ground, MD | Cellulose Biosynthesis and Biofabrication | Cellulose is a natural material with many Army-relevant applications. This project aims to harness microbially-sourced cellulose to achieve tunable physical properties and assemble advanced functionalities with nanofiber resolution. Research techniques will include biofabrication, functionalization, and processing of microbially-produced cellulose, along with characterization of the resulting material prototypes and variant methods. | biochemistry, bioengineering, biological sciences, chemistry, chemical engineering |
| Jordan Baumbach |
Biological & Biotechnical Sciences (BBS) | On-site | APG - Aberdeen Proving Ground, MD | Filamentous fungal genetic engineering for organism control. | The student will be involved in the culturing and genetic engineering of filamentous fungal organisms. This will involve designing experiments and using modern cloning and transformation techniques. The student will then work on characterizing the modified organisms they create to see if there are functional changes due to the genetic modifications. | Biology, life science or chemistry recommended |
| Meagan Small |
Biological & Biotechnical Sciences (BBS) | On-site | APG - Aberdeen Proving Ground, MD | Biotechnology Approaches to Plastics Degradation | Students will utilize various biotechnology approaches to understand the mechanisms of how to breakdown plastics. Methods include genetic engineering, microscopy, and directed evolution. | Biology |
| Randi Pullen |
Biological & Biotechnical Sciences (BBS) | On-site | ARL South - Austin, TX | Strain and Metabolic Engineering | We are seeking a motivated student to join our team for research in strain engineering, which focuses on modifying microorganisms to enhance their capabilities in producing valuable chemicals, improving stress resilience, or optimizing metabolic pathways. In this role, you will have the opportunity to work with cutting-edge genetic engineering techniques, including modifying gene expression, creating mutant strains, and evaluating their performance under different conditions. You’ll collaborate with experienced researchers to design, test, and refine microbial strains to achieve specific, innovative outcomes. | biology, biochemistry, microbiology, chemical engineering, molecular biology, evolutionary biology |
| Randi Pullen |
Biological & Biotechnical Sciences (BBS) | On-site | ARL South - Austin, TX | Computational Science for biotechnology | We are seeking a driven student to join our team in a computational biology project focused on writing scripts to automate data workflows and streamline experimental planning. You will help develop and implement scripts that bridge input and output formats for robotic systems and create complex data analysis pipelines. This role will also involve designing automation tools for experimental planning and integrating FAIR (Findable, Accessible, Interoperable, Reusable) data principles into the design-build-test-learn cycle. You will collaborate with scientists to ensure data flows seamlessly across different platforms, contributing to more efficient and reproducible research. | computer science, data science, machine learning, bioinformatics |
| Randi Pullen |
Biological & Biotechnical Sciences (BBS) | On-site | ARL South - Austin, TX | Analytical chemistry for biotechnology | We are seeking a chemistry student to join our team in a research project focused on chemical identification and strain characterization using advanced analytical techniques. In this role, you will work with mass spectrometry (MS) and high-performance liquid chromatography (HPLC) to analyze and identify chemical compounds produced by engineered strains. This project will give you hands-on experience in sample preparation, operation of MS and HPLC systems, and data analysis to characterize metabolites, proteins, or other biomolecules. You will collaborate with researchers to uncover the chemical profiles of different strains, contributing to breakthroughs in biotechnology and synthetic biology. | chemistry, chemical engineering, biological engineering, biochemistry |
| Randi Pullen |
Biological & Biotechnical Sciences (BBS) | On-site | ARL South - Austin, TX | Laboratory automation for biotechnology | We are seeking a detail-oriented student to join our team in a research project focused on laboratory automation, where you’ll work with advanced robotic systems to streamline and optimize experimental workflows. This project involves using state-of-the-art automation platforms such as the Tecan Fluent, Echo robot, Mantis robot, and Integra Assist Plus to perform tasks like high-throughput screening, liquid handling, and assay setup with precision and efficiency. You’ll gain valuable experience in programming and operating these automated systems to accelerate data collection and improve experimental reproducibility, working closely with researchers to develop cutting-edge solutions in a variety of scientific fields. | biology, chemistry, biological engineering, chemical engineering, biochemistry |
| Randi Pullen |
Biological & Biotechnical Sciences (BBS) | On-site | ARL South - Austin, TX | Protein engineering for biotechnology | We are looking for an enthusiastic student to join our team in a research project focused on protein engineering, where you will work to design and modify proteins to enhance their functions or create new capabilities. This project will involve using techniques such as mutagenesis, directed evolution, and computational modeling to develop proteins with desirable traits for applications in areas like biotechnology or industrial processes. You’ll gain hands-on experience in protein expression, purification, and characterization, working closely with researchers to test and optimize new protein designs. | biology, biochemistry, molecular biology, biotechnology, biological engineering, chemical engineering |
| A. Glen Birdwell |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Diamond surface characterization and analysis | Interns will be responsible for analyzing surfaces and interfaces of diamond and related semiconductor, dielectric, and metallic materials using analysis techniques such as Raman Spectroscopy, X-Ray Diffraction (XRD), and X-ray Photoelectron Spectroscopy. Measurements may require materials and surfaces be cleaned and/or prepared for measurement using mechanical and chemical techniques. Interns may be required to perform some experimentation to determine optimal preparation methods. | Engineering, chemistry, physics, materials science |
| Alex Bouvy |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Counter-Improvised Explosive Device (CIED) antenna design & evaluation | The project involves continually assessing the design of sinuous antennas and exploring new designs and approaches for application to standoff synthetic aperture radar (SAR) and close-in downward-looking ground penetrating radar (DLGPR) for ultra-wideband (UWB) linear and nonlinear radar transceivers. | electrical or electronics engineers |
| Alex Bouvy |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Radar Development and Data Collection | Become acquainted with stepped-frequency radar. Learn to operate custom radar software and collect data. Learn to analyze radar results. Perform testing on RF hardware using lab equipment. Perform analysis in MATLAB or similar. | Electrical Engineering or similar |
| Ben Kirk |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Distributed SMART RF nodes | The project focuses on reconfigurable hardware and firmware support using the RF System on a Chip (RFSoC), along with algorithms and processing to conduct signal ID, direction finding, unique waveform excitation, detection of air targets, and spectrum situational awareness (SSA) and dynamic spectrum sharing (DSS) specific algorithms. | electrical and electronics engineers |
| Brian Phelan |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Hardware/Firmware upgrades to RF System-on-a-Chip (RFSoC) along with signal and image processing for pre-screen and AI/ML detection-based algorithms | The project aims to provide updated capabilities to the transceiver via hardware and firmware upgrades. The upgrades will involve inserting signal and image processing into the RFSoC to support pre-screening, signal ID, and direction finding, along with spectrum agility and reconfiguration based on electromagnetic environment (EME) assessments. | electrical, electronic and computer scientists and engineers |
| Colin Kelly |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Signal and Image processing capability assessments for 3-D SAR image formation and distributed RF Node tracking and communication | Assess unique integration angle positions for optimum 3-D SAR image formation to detect buried explosive hazard targets. Communication and tracking algorithms associated with distributed RF nodes to address simultaneous tracking and comms within a contested and congested EME. | electrical and electronic engineers and computer science |
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| Daniel Jean |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Electromagnetic Effects in Electronics | This project works to incorporate novel materials and processes with microelectronics to control and/or limit the propagation of electromagnetic signals radiating from an electronics package. The project will involve tasks related to one or more of the following, subject to candidate skills, interests, and experience: data collection and analysis using electrical probe stations, oscilloscopes, high-speed videography, and/or infrared videography; coordination of experimental reliability tests with statistically relevant sample numbers under temperature, humidity, shock, and other environmental stresses; materials characterization such as Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), and/or Atomic Force Microscopy (AFM). | Electrical Engineering, Mechanical Engineering, Materials Science, or Chemistry |
| David Storm |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Ultrawide Bandgap Power Switches | Semiconductor power switches, used to control and regulate power supplies to electronic devices, electromechanical equipment, and lighting, will find increasingly broad application in such diverse fields as telecommunications, energy storage, renewable energy, and electric vehicles. Ultrawide bandgap (UWBG) materials are attractive candidates for power switches due to their high breakdown fields and low on-resistance. We investigate the design, epitaxial growth, device fabrication, and device testing of UWBG AlGaN-based lateral power switches. | Electrical engineering, materials science/materials engineering, physics |
| Franklin L Nouketcha |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Ultrawide Bandgap Power Switches | Semiconductor power switches, used to control and regulate power supplies to electronic devices, electromechanical equipment, and lighting, will find increasingly broad application in such diverse fields as telecommunications, energy storage, renewable energy, and electric vehicles. Ultrawide bandgap (UWBG) materials are attractive candidates for power switches due to their high breakdown fields and low on-resistance. We investigate the design, epitaxial growth, device fabrication, and device testing of UWBG AlGaN-based lateral power switches. Interested students of electrical engineering, materials science, physics, or chemistry are encouraged to apply to this announcement. | Electrical Engineering, Electronic Engineering, Mechanical Engineering |
| Gabe Smith |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Additive Manufacturing for Electronics | The Additive Manufacturing team within the Electromagnetic Effects Branch works to incorporate new materials with micrometer scale and nanometer scale 3D-printing process with microelectronics chips, interconnects, and packaging to enable novel, conformal, printed-circuit-board-like integration into non-planar form factors. The project will involve tasks related to one or more of the following, subject to candidate skills, interests, and experience: solid modeling, 3D printing, testing related to novel convergent manufacturing and additive manufacturing methods, low-SWaP sensor systems, data analysis, user interfaces, data analysis, and/or artificial intelligence/machine learning techniques for 3D printing part design. | Electrical Engineering, Mechanical Engineering, Materials Science, or Chemistry |
| Kathleen Coleman |
Electromagnetic Spectrum Sciences (EMSS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Advanced Ferroelectric-Based Sensing, Packaging and Integration | The U.S. DEVCOM Army Research Laboratory (ARL) is pleased to announce an exciting opportunity for a summer internship with a focus on microsystems, ferroelectrics, 2.5D integration and MEMS. Responsibilities will include circuit design, chip to chip bonding, and testing. The successful candidate will primarily be stationed in Adelphi, Maryland. Key Responsibilities include: conducting innovative research in the design, fabrication, and testing of microsystems, sensors, and MEMS technologies, and present research findings to ARL scientists. | Electrical Engineering, Mechanical Engineering, Materials Science, Physics, or a related field. |
| Kathleen Coleman |
Electromagnetic Spectrum Sciences (EMSS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Sensor Analytics Intern | By leveraging signal processing and machine-learning algorithms, the hired candidate will help develop autonomous sensor systems that can analyze moving targets. The goal is to analyze extensive sensor datasets to extract knowledge from large geographic areas. | Computer Science, Computer Science and Engineering, Computer Engineering, Electrical Engineer, Materials Science, or equivalent fields |
| Kyle Gallagher |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | High Dynamic Range Ultra Wideband Harmonic Measurements | The student will develop a high dynamic range harmonic measurement system before measuring electrical nonlinearities. The student will implement ultra-wideband filter bank technology to maintain high linearity while operating over an ultra-wide frequency range. | Electrical Engineering |
| Lam Nguyen |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Signal & Image Processing and Target Classification for Synthetic Aperture Radar | The project involves developing radar signal processing techniques for noisy and congested environments, including signal and noise separation, detection of targets in noisy imagery, SAR image formation techniques, and machine learning techniques for image recovery and target classification. | Electrical and Electronic Engineering and Computer Science |
| Lam Nguyen |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | AI and ML-based detection algorithm development and assessment | Collection of multiple position, angle and frequency spectrum data sets to feed AI and ML-based detection algorithms. | electrical and electronic engineers, and computer science |
| LeighAnn Larkin |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Thermal Spectroscopy of Ultra-Wide and Wide Bandgap Semiconductors | New ultra-wide and wide bandgap (U/WBG) semiconductor materials are important to making advances in power and RF electronics. This project applies laser spectroscopy techniques, including time-domain thermoreflectance and frequency-domain thermoreflectance, to understanding the thermal boundary conductance and thermal conductivity in these new materials. This understanding is used to provide feedback to team members so they can grow better materials and design improved devices including RF electronics and high-power platforms. | Physics, Optics, Material Science, Mechanical Engineering, Electrical Engineering, or equivalent |
| LeighAnn Larkin |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Laser Spectroscopy of Ultra-Wide and Wide Bandgap Semiconductors | New ultra-wide and wide bandgap (U/WBG) semiconductor materials are important to making advances in power and RF electronics, and ultraviolet (UV) opto-electronics. This project applies laser spectroscopy techniques, including photoluminescence and time-correlated single photon counting, to understanding electron-hole dynamics in these new materials. This understanding is used to provide feedback to team members so they can grow better materials and design improved devices including transistors, light emitting diodes (LEDs), and laser. | Physics, Optics, Material Science, Electrical Engineering, or equivalent |
| Leo De La Cruz |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | 1. Applications of interface traps analysis techniques to UWBGS Devices | The student will performance a literature review of current traps analysis techniques, and test them out on our UWBGS devices. The goal to understand which techniques are applicable to UWBGS, and which one are not, and why. If time allows, are there modifications that can be done to current make techniques applicable. The student will used laboratory equipment to perform the measurements. Training on equipment will be provided, however the student will be expected to familiarize with the measurements system via manual or any other resources available. More details will be provided as required. | Electrical Engineering, Computer Engineering, |
| Leo De La Cruz |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | MOSFET Field Plate Engineering | The student will perform a literature review of current field plate designs for field effect transistors and attempt to reduce the electric field intensity on our UWBGS devices. The goal to understand the role of each field plate parameters, which parameters have the most impact and recommend a design to be implemented. The student will be using COMSOL to perform simulations of field plate design. More details will be provided as required. | Electrical Engineering, Computer Engineering, Physics |
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| Quang Nguyen |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Transparent Antenna Design | In the next generation of wireless communication system, electronic devices are becoming smaller and thinner, which result in less space for antenna. However, miniaturized antenna will suffer from low radiation efficiencies due to smaller footprint. In this abstract, we are looking at the concept of transparent antenna. It means that antenna is invisible to human eye. Thus, by incorporating the invisible antenna to the frame of electronic devices, we don’t necessarily have to sacrifice the real estate for smaller antenna with much less ideal performance. We can utilize the whole area of device’s frame for antenna if needed since the antenna is transparent. To validate the feasibility of this concept, we will design and simulate the wire grid antenna. The optical transparent rate can be adjusted by tuning the grid patterns such as, grid widths and spacing. The efficiency of antenna will be studies with different conductive paste, such as Cu, or Ag paste. | Electrical Engineering |
| Quang Nguyen |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | NEURAL NETWORK FOR ELECTROMAGNETIC APPLICATIONS | With modern computing power and advances in novel electromagnetic structures, the engineer is now afforded a vast design space towards the arbitrary control of electromagnetic waves. However, once a design is chosen, the optimization of this design can be a slow and computationally expensive process. To overcome this limitation, neural networks can be leveraged thanks to their powerful ability to model non-linear, complex relationships and produce solutions at speeds orders of magnitudes faster than traditional numerical electromagnetic solvers. Neural networks are flexible, able to act as surrogate models in the forward problem, predicting a structure’s electromagnetic response from its geometry, and also the inverse problem, generating geometry from a desired response. In this work, deep neural networks for electromagnetic structure design are studied and applied towards a practical problem: the design of multi-layered substrates for radar absorbent material (RAM). We seek to understand and demonstrate the capability of neural networks as proxies for numerical electromagnetic codes in the design of useful structures. We make simplifying assumptions to allow for the quick generation of training data through fast, analytical solutions, and study how the architecture of the network affects its prediction ability in the context of this specific electromagnetic problem. Further, we also explore the use of generative neural network architectures for inverse design problems, comparing and analyzing generated results against full-wave simulations. | Electrical Engineering |
| Sean Heintzelman |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Sensor Analytics | By leveraging signal processing and machine-learning algorithms, the hired candidate will help develop autonomous sensor systems that can analyze moving targets. The goal is to analyze extensive sensor datasets to extract knowledge from large geographic areas. | electrical engineering, computer engineering, computer science, materials science, physics, applied math |
| Theodore Anthony |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Creating Innovative EM Models with I/O Neural Networks | Objective goal is to develop neural network(s) to take electromagnetic simulation run parameters (I/O variables) to predict the inputs needed for desired outputs. This machine learning neural network source code will be created, trained & run successfully predictively this summer. | Computer Science or Electrical Engineering |
| Timothy Garner |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Technologies for Distributed Beamforming | Distributed beamforming combines the signals from multiple radio transceivers to form beams in a desired direction, effectively transforming the distributed transceivers into a single phased array antenna. This technology requires precise synchronization of the transceivers and knowledge of their locations. Distributed beamforming has both commercial and military applications, enhancing the performance of small, low-powered transceivers with small antennas by consolidating them into a single, large transceiver. Key application areas include radio-frequency sensing and communications. DEVCOM ARL is seeking an electrical engineering student for a summer internship to work on distributed beamforming technologies. The internship may focus on transceiver synchronization, positioning, or signal processing of received signals. While experience with software-defined radios, radio-frequency systems on a chip (RFSOCs), and signal processing in MATLAB or Python is desirable, these skills can be developed on the job. The internship will provide hands-on experience with radio and microwave-frequency test equipment. The position will be located at the Adelphi Laboratory Center, 2800 Powder Mill Road, Adelphi, MD 20783. |
Electrical engineering |
| Timothy Garner |
Electromagnetic Spectrum Sciences (EMSS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Technologies for Distributed Beamforming | Distributed beamforming combines the signals from multiple radio transceivers to form beams in a desired direction. The distributed transceivers act as a single phased array antenna. This requires precise synchronization of the transceivers and precise knowledge of their locations. Distributed beamforming has commercial and military applications to increase the performance of small, low-powered transceivers with small antennas by combining them to create a single, large transceiver. Application areas include radio-frequency sensing and communications. DEVCOM Army Research Laboratory is seeking a graduate student in electrical engineering for a summer internship working on technologies for distributed beamforming. This work may focus on synchronization, positioning, or signal processing of the received signals. Skills for the position include the ability to work with software-defined radios or radio-frequency systems on a chip (RFSOCs) and the ability to perform signal-processing analyses in MATLAB or Python. The ideal candidate is someone working in this area as part of a thesis or dissertation. The internship will be located at the Adelphi Laboratory Center, 2800 Powder Mill Road, Adelphi, MD 20783. Depending on the facilities available at the candidate’s university laboratory, it may be possible to do part of the internship at the university and part at Adelphi. | Electrical engineering |
| Traian Dogaru |
Electromagnetic Spectrum Sciences (EMSS) | On-site | ALC - Adelphi Laboratory Center, MD | Electromagnetic Field and Antenna Array Optimization for Distributed Radar and RF Technologies | DEVCOM ARL is seeking a highly qualified individual for a visiting faculty appointment in the areas of antennas, antenna arrays and active electromagnetic field manipulation, for radar and general RF applications. This position requires a strong theoretical background in complex optimization problems, as well as advanced knowledge of electromagnetic field theory, with emphasis on antenna radiation, as well as beamforming and imaging using antenna arrays. The candidate will collaborate with ARL researchers on problems of current interest to the Army in radar and RF technologies, involving sparse, multi-static arrays implemented as distributed RF systems on unmanned aerial vehicle (UAV) platforms. The position will involve algorithm development for fast solution of optimization problems, using the Matlab and/or Python languages. The algorithms will be tested on computer models, with a well-defined path to future practical applications. A Ph.D. in applied mathematics, combined with a current academic appointment is preferable for this position. | applied mathematics combined with current academic appointment Ph.D. |
| Dat Tran |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Advanced Li-ion Battery Materials | Students will work on Li-ion battery materials to improve battery performance, including energy density, capacity, life cycle, and stability. | Chemistry, Chemical Engineering, Materials Science, Mechanical Engineering |
| Ei Ei Brown |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Exploring New Solid-State Materials for Infrared Laser Applications | This project offers a hands-on approach to studying materials for infrared laser sources. By investigating the optical properties of solid-state materials, students will gain insights into how these materials can serve as gain media for lasers. The project will introduce spectroscopic methods to characterize material properties, helping students understand how light interacts with different materials. This research is fundamental to advancing the next generation of laser technologies, with applications ranging from environmental monitoring and sensing to medical diagnostics. | Physics, Material Science, and Engineering |
| James J. Carroll |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Nuclear Physics Research at the US Army Combat Capabilities Development Command Army Research Laboratory | DEVCOM Army Research Laboratory (ARL) research into nuclear physics is focused on the measurement of fundamental physical quantities relevant to nuclear properties and reaction cross sections. The project will encompass active participation in nuclear measurements, development of detection systems, or analysis of nuclear data. | For students: Physics, engineering; For RESET educators: Physical Science |
| Jan Allen |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Li-ion battery materials | The students will work on materials to improve the performance of Li-ion batteries in terms of improved energy density, cycle life and rate capability. | Chemistry, Chemical Engineering, Materials Science, Mechanical Engineering |
| Janet Ho |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Graphene as Electrode Materials for Electrochemical Energy Storage Devices | The student will learn about the various aspects of supercapacitors and lithium-ion batteries and conduct a comparative study on the performance between graphene-based devices and conventional counterparts. This project is part of an effort to establish a road map for strengthening domestic materials supply chain for energy storage applications. There have been claims that graphene, if made appropriately, can provide higher energy density in supercapacitors than the conventional material which is activated carbon. Graphene can also be used to replace graphite which is the anode material for lithium-ion batteries. While graphene, graphite, and activated carbon are all carbon materials, their morphologies are different and have significant impact on the device performance. This project will serve as an independent evaluation against the claims and provide the student an opportunity to learn about the various allotropes of carbon. | STEM |
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| Janet Ho |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Parasitic Reaction Study for Aqueous Rechargeable Batteries | The summer internship aims to give the student an opportunity to learn about the basics of a rechargeable battery. Side reactions are undesirable but often inevitable and cause poor battery performance. The student will learn to perform density measurements based on Archimedes' Principle to determine rate of gas generation caused by parasitic reactions between the electrolyte and anode. Various electrolyte formulations and in combination of different anode materials will be tested. The student will also test battery (coin cell) performance to correlate with the density measurement results. | Chemistry or Material Engineering/Science is preferred, otherwise Physics or other Engineering |
| Jonathan Boltersdorf |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Chemical and Electrochemical Energy Conversion Materials, Devices, and Sensors | This research effort will focus on the identification, characterization, and development of enhanced fuel conversion, exploring the enhancement of chemical reactions involved in both fuel consumption and creation. The overall research objective is to selectively drive localized, energy-intensive reactions for performance of otherwise impractical (high temperature/pressure) industrial-scale processes, portably and safely, on the nanoscale, such as the utilization of high energy ethanol in fuel cells at lower overall operation temperatures, and local synthesis of hydrocarbon fuels. Explore novel concepts in energy generation and capture in technologies for efficient conversion of ambient energy to electrical energy for use and storage. | Chemistry, Chemical Engineering, Material Science and Engineering, Physics, Mechanical Engineering |
| Marc Litz |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Radioisotope Persistent Power | Investigate the radiation tolerance of ultra-wide bandgap (UWBG) semiconductor materials (AlGaN, Ga2O3, diamond) to increase the power density of both betavoltaic and alphavoltaic power sources. | any |
| Oleg Borodin |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Modeling of Battery Materials | As part of this research effort, the selected candidate will work within a highly interdisciplinary team of scientists at DEVCOM ARL, university collaborators, and Department of Energy Laboratory counterparts to apply one or more molecular to mesoscale level computational methodologies spanning from density functional theory (DFT), molecular dynamics (MD) simulations of bulk battery electrolytes and electrochemical interfaces and complex/composite interphases. | Chemistry, Chemical Engineering, Materials Science |
| Rachel McAfee |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Thermal/Mechanical Engineering Research | DEVCOM ARL's mission is to research and develop compelling technologies for the US Military and Defense sectors. This includes power electronics systems for military vehicles, power conversion systems, lasers, etc. The thermal team conducts research across electronics cooling, fluidic systems, and materials development for thermal energy storage. Major projects include phase change materials, electronic device packaging, and thermal modeling. The student's project will cover materials investigation for thermal energy storage and its application to electronics cooling. | Mechanical Engineering, Electrical Engineering, Materials Science, Computer Science |
| Thomas N. Rohrabaugh, Jr. |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Synthesis and Characterization of Novel Organic and Organometallic Chromophores for Non-Linear Optical (NLO) Applications | The successful student would aid in the synthesis, purification, and characterization of new organic and organometallic chromophores for the development of novel non-linear optical (NLO) materials. The student would gain experience in analyzing chemical characterization techniques such as nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), x-ray crystallography, electrochemistry, and optical characterization including, UV-visible absorption, photoluminescence, transient absorption, and Z-scan spectroscopies. References: [1]Olumba, M. E., et al., Inorg. Chem. 2022, 61, 48, 19344–19353; [3] O'Donnell, R. M., et al., Inorganic Chemistry 2017, 56 (15), 9273-9280. |
Chemistry, Physics, Chemical Engineering |
| Vijay Parameshwaran |
Energy Sciences (ES) | On-site | ALC - Adelphi Laboratory Center, MD | Radioisotope Voltaics for Persistent Power Conversion | We are looking for a student team that can support us in a variety of projects in materials research of semiconductors and scintillators for radioisotope voltaic converters. Specific research projects include: 1) Utilizing Monte Carlo and radiation physics modeling to investigate alpha particle damage and energy deposition in materials. 2) Supporting materials synthesis programs to make both semiconductors and scintillators to be able to process and integrate within a device. 3) Utilizing COMSOL to integrate alpha particle irradiation and semiconductor device physics for modeling an alphavoltaic converter. 4) Engineering and prototyping a voltaic stack integrated with a scintillator for device testing under both electron beam and alpha particle irradiation. 5) Performing electron beam irradiation tests to be able to obtain I-V curves and analyze device performance. The overall goal is to investigate the radiation tolerance of materials to increase the power density of both alphavoltaic and alphaphotovoltaic sources, but also includes optimizing the more well-established betavoltaic devices. |
Variety of majors are suitable. In the past we've had: chemical engineering, electrical engineering, physics, and materials science. |
| Sunny Karnani |
Energy Sciences (ES) | On-site | ARL Central - Chicago, IL | Emissivity Characterization of Refractory Materials and Data Acquisition | The Summer Participant will focus on making direct emissivity measurements of various refractory materials at high temperatures. Emissivity, which varies with material type, temperature, and surface morphology, will be measured to help in the system design of a thermo-photovoltaic power source, where accurate data is essential to understand energy conversion. Indirect measurements techniques will be explored, depending on available time and participant's interest. | Mechanical, Aerospace, or Electrical Engineers. Physics. |
| Brittany Story |
Humans in Complex Systems (HCxS) | Hybrid | APG - Aberdeen Proving Ground, MD | Neuroscience and Navigation: Connecting the vertices | Graphs have long been used to model connectivity. In navigation tasks, connectivity could mean line of sight, communication availability, or the ability to get between point A and point B. In neuroscience, graphs have been used to model neural connectivity. For example, two neurons are connected if they consistently fire together. In each of these examples, edges are used to represent connections between vertices. But what happens when we have connections between 3 or more vertices? The overarching goal of the internship is to look at how this higher order structure can be used in navigation tasks, both in the task itself and within the structure found in the brain. If you’re interested in mathematics, graph theory, topology, neuroscience, how mammals and/or robots navigate, or anything mentioned above, this internship might be for you! | STEM |
| Chloe Callahan- Flintoft |
Humans in Complex Systems (HCxS) | Hybrid | APG - Aberdeen Proving Ground, MD | Exploring human cognition and behavior to enable human machine integration | Are you a human? Interested in studying humans? For the purposes of teaming them with robots? Then come work with us! Our team of leading experts in fields such as cognitive psychology, biomechanics, data analysis and software engineering run experiments to understand the underlying mechanisms that drive human behavior so that we can effectively team humans with artificial intelligence (AI) tools. We want to enhance human performance with AI. To do that the AI has to understand what the goals are of the human and how those goals might change depending on the context—we want to do this in a way that doesn't add additional burdens to the human (e.g., it is not helpful if a Soldier has to write out a continuous description of what they're trying to do). We also need a way for the AI to provide aid to the human—again, this needs to be done in a way that doesn't cause additional workload (e.g., Soldiers cannot navigate the environment if their heads-up display completely blocks their field of view with notifications from the AI). To help us achieve these goals, summer interns would work with our scientists to construct experiments in virtual and augmented reality, run participants, analyze and/or visualize data. These duties are flexible depending on the research interests of the intern. Previous experience in psychology, neuroscience, biomechanics, statistics or computer science is helpful but not required. Scientific curiosity is the main requirement! | Not required but helpful: Psychology, Computer Science, Neuroscience, Biomechanics |
| Dave Hairston |
Humans in Complex Systems (HCxS) | On-site | APG - Aberdeen Proving Ground, MD | Materials and Tool Development for Neuroscience Research | This project involves the design and investigation of the mechanical, electrical, biomagnetic, and functional properties of various materials and model tools that will be used for neuroscientific study of tissues such as brain, bone, or skin. The topic contains a broad range of sub-tasks throughout areas of neuroscience, biomedical engineering, materials science, and biochemistry. Example duties may include construction and characterization of materials simulating tissue; investigation of various materials and techniques for appropriateness; design and developing physical models and/or techniques for constructing physical models; use of CAD for model development; or use of additive manufacturing for molds, models, or components. Tasks can range from theoretical development to practical application. A niche can be carved out based on knowledge and interest. | Mechanical engineering, biomedical engineering, electrical engineering, bioengineering, chemistry, neuroscience, physics, biochemistry, materials science |
| David Boothe |
Humans in Complex Systems (HCxS) | On-site | APG - Aberdeen Proving Ground, MD | Neuroscience and Neurotechnologies | Computer science has often borrowed different things from neuroscience to use as a blueprint for artificial systems. For example, convolutional neural networks (CNNs), are modeled after the mammalian visual system, and are used for tasks like image classification, feature recognition, and object identification. But there are many other systems the brain uses to interact with the world that can serve as foundations for new machine learning algorithms. This project will explore different brain systems and how these systems can be used to develop new, energy-efficient, adaptable algorithms. Potential research questions include: How can different neuroscience research be used as inspiration for new intelligent systems? What and how can technology benefit from different brain-inspired systems? | Computer science, neuroscience, biology, mathematics, and engineering. Others considered if relevant. |
| Ioannis Schizas |
Humans in Complex Systems (HCxS) | Hybrid | APG - Aberdeen Proving Ground, MD | Brain Inspired Artificial Intelligence Algorithms | The human brain has always been a source of inspiration for building computer systems, especially in how we create artificial intelligence (AI). This project is focused on understanding how the brain processes information—essentially how it thinks—and using that knowledge to enhance AI algorithms. We’ll look at how the brain’s neural pathways work. These pathways are networks of neurons (brain cells) that communicate and process information. By studying these pathways, we can create mathematical models that simulate how the brain operates. One specific tool we’ll use is called a graph neural network. This type of network helps us model complex relationships, similar to how neurons in the brain interact. By using these networks, we hope to develop better methods for AI to navigate and understand information. The goal is to create smarter AI that can navigate its environment or tasks more effectively, much like how humans use their cognitive skills to solve problems. We’ll also investigate the patterns and connections between neurons in the brain. Understanding these connections can help us figure out how to make AI systems that can perform various cognitive tasks, like reasoning or decision-making, more efficiently. This project is a fantastic chance to dive into neuroscience—how the brain works—and see how it can be applied to create the next generation of AI systems. Overall, the aim is to bridge the gap between how humans think and how we can make machines think better! | Computer Science, or Math, or Electrical and Computer Engineering |
| Javier Garcia |
Humans in Complex Systems (HCxS) | On-site | APG - Aberdeen Proving Ground, MD | Hybrid Human-Technology Intelligence | Most problems benefit from teamwork. Different mindsets, approaches, experiences, and strengths enable teams to accomplish large goals that would be impossible for a single individual to accomplish alone. As technology continues to advance, more and more teams will include both humans and AI agents. This project looks at how to integrate humans and machines to create hybrid teams that surpass what humans can accomplish alone. A few potential research questions include: What new forms of thinking emerge from combining human collectives with technology in novel ways? How might we accelerate the process of collective decision making or creative problem solving with novel frameworks, systems, and technological integration? | Neuroscience, computer science, psychology, and data science. Other relevant majors will be considered. |
| Kaleb McDowell |
Humans in Complex Systems (HCxS) | On-site | APG - Aberdeen Proving Ground, MD | Human-Guided System Adaptation | AI is a quickly evolving tool, that when used properly, can assist both soldiers and civilians alike. But, AI is not yet able to adapt as efficiently or as effectively as humans. We (humans) are highly adaptable and can adjust to a wide variety of situations quickly and without any additional training. On the other hand, current AI systems need large amounts of situation-specific training to become effective and useful, and when the situation changes, it can completely confuse the system. This project will look at the creation and modification of human-guided adaptation approaches; a method that uses the human to inject adaptability into intelligent systems, reducing training time, cost, and errors. A few potential research questions include: How can humans intuitively adapt intelligent systems for new uses, environments, and situations? How can intelligent systems take in and use human feedback and experience? | Computer science, data science, psychology, and engineering. Other relevant majors will be considered. |
| Mariela Perez- Cabarcas |
Humans in Complex Systems (HCxS) | On-site | APG - Aberdeen Proving Ground, MD | Enhancing Human Cognition with Foundational Models | This group project aims to enhance human cognition by leveraging foundational models to improve memory, mental model formation, communication, and decision making amongst Soldiers. Students of diverse backgrounds will collaborate in a multi-disciplinary (e.g., computer science, machine learning, neuroscience, psychology, and human-computer interaction) effort to research human behaviors, human-machine interactions, and AI system design. Students will create novel methods to research and develop human-AI systems interactions that can lead to augmented development and maintenance of situational understanding during complex and dynamic human interactions. | Computer science, Neuroscience, Psychology, Human-Computer Interaction, or related major. |
| Russell Cohen Hoffing |
Humans in Complex Systems (HCxS) | On-site | ARL West - Playa Vista, CA | Human See, Robot Do: Developing novel forms of communication and teaming with LLM based agents. | Join our innovative research team focused on advancing human-robot integration! We're a collaborative group of experts in cognitive science, working on a project aimed at enhancing understanding between humans and agents in real-world contexts by leveraging physiological data for multi-modal LLMs. What You'll Do: - Assist in developing and prototyping a multimodal dialogue system that integrates physiology and speech/text to improve understanding between LLMs and humans. - Conduct experiments to evaluate the effectiveness of our system by comparing it to traditional models without physiological data. - Data sources may include gaze, gestures, pupil size, heart rate, and movement data. Why You Should Apply: Work at the cutting edge of robotics and cognitive science with a focus on real-world applications in military settings. - Gain hands-on experience in natural language processing, machine learning, and human-machine interfaces. |
computer vision, computer science, engineering, data science, applied math, math, applied physics |
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| Steven Thurman |
Humans in Complex Systems (HCxS) | Hybrid | ARL West - Playa Vista, CA | Basic Research in Advancing Hybrid Human Technology Intelligence | Our research projects focus on advancing the state-of-the-art in hybrid intelligence, which involves studying interactions between humans and AI systems (large language models, generative models, etc). To execute this basic research, we are looking for students to work in person (Irvine or San Francisco) or (possibly) remotely with an interest and background in at least 2 of the following: computer science, AI/ML, software development, neuroscience, cognitive science, and/or human-subjects research. We will work with the student to scope a summer research project that contributes to one of our ongoing research efforts in the hybrid human technology intelligence area. | computer science, neuroscience, cognitive science |
| Geoffrey Goldman |
Mechanical Sciences (MS) | Remote | ALC - Adelphi Laboratory Center, MD | Tracking the acoustic spectrum of vehicles | Update, organize and improve Matlab software to track the acoustic spectrum of moving targets. The software works similar to active contours used in image processing applications. Process unclassified data with the updated software. | STEM |
| Geoffrey Goldman |
Mechanical Sciences (MS) | Remote | ALC - Adelphi Laboratory Center, MD | Update acoustic classifier | Improve an existing acoustic classifier for ground targets developed by BSU. Improve the architecture of the neural network, number of supported classes, and its robustness to noise and interference. | Computer science |
| Luis Bravo |
Mechanical Sciences (MS) | Hybrid | APG - Aberdeen Proving Ground, MD | Large eddy simulations of high-speed combustion and gas-surface interactions for hypersonic propulsion | The project involves advancing hypersonic propulsion technologies by simulating high-speed turbulent combustion and material ablation in scramjet engines. The researcher will apply Large Eddy Simulation (LES) tools and Fluid Structure Interaction (FSI) models to analyze system dynamics under extreme conditions. The research aims to bring new fundamental knowledge about high-speed propulsion systems, enhance model accuracy, and support the development of more efficient and robust hypersonic vehicles. This work will contribute to improving the performance and operational capabilities of future military platforms. | Aerospace Engineering, Mechanical Engineering, Chemical Engineering, Physics |
| Nikhil Murthy |
Mechanical Sciences (MS) | On-site | APG - Aberdeen Proving Ground, MD | Machine learning to characterize fuel pump damage with vibrational data. | This project will utilize machine learning algorithms to characterize the damage state of fuel pumps from vibration data. High-frequency acoustic sensors can detect vibrations from a damaged component. These vibration signals can act as a 'fingerprint' to help identify the damage state of the fuel pumps, however interpretation of the signals is difficult due to their complexity. The student will utilize machine learning and other advanced algorithms to reliably characterize vibration data. | Computer Science, Engineering or related field |
| Stephen Berkebile |
Mechanical Sciences (MS) | On-site | APG - Aberdeen Proving Ground, MD | Tribology of Materials in Fuels | This project seeks to determine the mechanisms of fuel lubricity and the behavior of different materials in fuels in sliding mechanical interfaces. Our group uses tribometers to measure the mechanical behavior of materials (friction, wear, damage) and relate that to the properties of the materials and lubricants and the unique chemistry between them. This project will involve research to understand how and why different material combinations with various fuel chemistries resist wear and destruction for potential use in high performance fuel systems for air and ground vehicles. The project specifics can be adjusted based on student abilities and interests. | Materials Science/Engineering, Mechanical/Aerospace Engineering, or Physical Science |
| Todd Henry |
Mechanical Sciences (MS) | On-site | APG - Aberdeen Proving Ground, MD | Small UAS Platform Design and Control | DEVCOM ARL seeks research in platform design and control that will enable unique aerial maneuvers. Technical challenges include developing a computational framework for design of mechanical systems (soft/compliant robots and platforms) capable of performing morphological computation. Control paradigms need to be developed for non-linear adaptive structures where maneuverability is being maximized. The goal is to address (1) structural adaptations, (2) describing structural and aerodynamic performance in dynamic environments, and (3) controlling these highly coupled vehicles. | Aerospace Engineering, Mechanical Engineering, Computer Science |
| Frank Gardea |
Mechanical Sciences (MS) | On-site | ARL South - Austin, TX | Materials for Soft Actuation | DEVCOM ARL is interested in scientific research into the integration of active, actuating soft materials into passive structures for robotic maneuverability. The goal is to obtain multi-degree of freedom motion by leveraging additively manufactured complex architectures coupled with selective positioning of active components. | Aerospace Engineering, Mechanical Engineering, Materials Science |
| Adrienne Raglin |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD | AI and Artificial Reasoning | ARL is seeking students and/or faculty with background in computational modeling, artificial intelligence, machine learning, and analysis. Research opportunities are available to create algorithms and methodologies that enable efficient computational models for recommendations and informed decisions by capturing individual characteristics of users, tasks, and context including domain knowledge and situational awareness, agents’ behavior, and decision outcomes. Research will ultimately allow the generation and the deployment of intelligent information systems that incorporates multiple levels and approaches for reasoning. Research requires experience and interest in interactive visual systems, artificial intelligence, machine learning, reasoning, and analysis of data from various modalities. | Computer Science, Engineering, Mathematics, Science |
| Andre Harrison |
Military Information Sciences (MIS) | On-site | ALC - Adelphi Laboratory Center, MD | Scene context for decision making | DEVCOM Army Research Lab (ARL) is seeking dedicated researchers, engineers, and technologists with an interest in developing or implementing visual perception models to extract relevant visual information from a scene. These models are aimed to support the decision making of an autonomous system or human agent to help them better or more rapidly understand their surrounding environment. Decision-making may require understanding the surrounding environment using a combination of low, mid, or high-level visual concepts. | Computer Science, Electrical Engineering, Electrical and Computer Engineering, Mechanical Engineering, Data Science |
| Claire Bonial |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Novel LLM and neurosymbolic architectures for dialogue systems | We seek students interested in the interdisciplinary intersection of language, natural language processing, and robotics. In particular, students with interest or experience in working with LLMs and considering how to use LLMs in novel, broader (neuro)symbolic architectures would be ideal candidates. However, candidates with strong linguistic experience, human-robot interaction experience, or robotics experience and interest in the intersection of these skills are also highly desirable. | Computer Science, Engineering, Linguistics |
| Dan Cassenti |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Human-AI Collaboration | Humans and Artificial Intelligence are diverse agents that must collaborate with one another to achieve breadth of skills to succeed in the future battlefield. This internship represents the opportunity to learn how to do research at the intersection of computer science and psychology. | Computer Science |
| Heesung Kwon |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Exploring Synthetic Data Generation for AI Models with Minimal Real Data Dependency | This project focuses on advancing techniques in synthetic data generation using generative AI, specifically targeted at computer vision and perception applications. The intern will be responsible for developing and optimizing algorithms to generate synthetic image datasets that closely mimic real-world data, maintaining high diversity and quality. They will explore various generative models and data augmentation techniques to create datasets suitable for training and evaluating machine learning models, especially in scenarios with limited or sensitive visual data. The project will investigate how these synthetic datasets can improve the robustness, generalization, and performance of visual perception models across various domains. | Master’s or PhD student in CS, EE, CSE, or other relevant technical fields. |
| Melvin Felton |
Military Information Sciences (MIS) | On-site | ALC - Adelphi Laboratory Center, MD | Atmospheric Remote Sensing | The atmosphere effects all propagating signals, such as acoustic, electro-optic, and electromagnetic. This research will focus on atmospheric remote sensing: data collection, preparation, and analysis. Of particular interest is identifying atmospheric/environmental phenomena in urban, littoral, and other complex environments, developing methodologies to analyze and characterize phenomena (e.g., vortex shedding, ducting), developing methodologies to identify and remove dynamic clutter for autonomous sensing, and analyzing environmental impacts on signatures (EO, EM/RF and acoustic). Research may include operating remote sensing equipment, analyzing data, and writing data analysis and/or control software. Codes utilize Matlab, but python, C, and C++ may also be available for those interested. Remote sensing equipment includes Doppler wind lidars, Doppler radars, and acoustic sensors. | Physics, Atmospheric Sciences, Meteorology, Engineering, Mathematics, or Computer Science |
| Steve LaRocca |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Developing speech-to-text models for low-resource languages of military interest | Intern will use open development tools in a Linux environment to train deep neural network models from recorded examples of speech. | Computer science |
| Yongle Pan |
Military Information Sciences (MIS) | On-site | ALC - Adelphi Laboratory Center, MD | Detection of bioaerosol using polarized light scattering | There is a research opportunity for AEOP High School Apprenticeship Program in the Aerosol Research Team, Atmospheric Sensing Branch, Military Information Sciences Division, DEVCOM Army Research Laboratory. The opportunity is to work in developing innovative real-time, in-situ point-detection systems for detecting, discriminating, and identifying biological and chemical aerosol particles from complex atmospheric aerosol particles using laser spectroscopic methods. Student accepted in the lab will learn the fundamental knowledge & devices about laser, electronics, optical-mechanics, aerodynamics, and how to use these instruments for environmental research. | STEM students |
| Erin Zaroukian |
Military Information Sciences (MIS) | Hybrid | APG - Aberdeen Proving Ground, MD | Artificial reasoning to support decision making | Artificial reasoning explores how artificial intelligence solves problems, and our research focuses on artificial reasoning technology to address human uncertainty and bias in military decision making. Projects include computationally modeling human decision-making patterns, experimentally identifying biases in decision making, and identifying and exploiting problem-solving abilities of large language models to augment human decision making. | Computer science, psychology, cognitive science, or related |
| Prabhat Kumar |
Military Information Sciences (MIS) | On-site | APG - Aberdeen Proving Ground, MD | Multimodal Machine-Learning Approaches for Theory of Mind | Theory of Mind (ToM) is the capability of an individual to infer the internal mental states (goals, intentions, strategies, desires) of others. It is considered the holy grail of artificial intelligence research, as systems with such capabilities enhanced with computational processing capabilities will have consequences in areas like human-agent teaming, socially-assistive systems, game theory, and wargaming. We still have a long way to go before machines attain such a capability which may be the result of a lack of computational resources; after all, human ToM arose after billions of years of evolution. However, we also theorize that potential ToM systems require diverse training, to the extent of even requiring open-ended learning to allow systems to experiment. Several studies have shown promising results with single agents in static environments, but we aim to expand to multi-agent, dynamic environments to test and facilitate development of a computational ToM system.In this project, we have a few problems we would like to address: + Data: Open-source data illustrating agent intention in a closed environment is lacking. One goal is to create a method for procedurally generating (synthetic) data for training and testing ToM and other cognitive systems. We hypothesize that multimodal data will be the key in facilitating model understanding between, for example, what is being said by, or described about, the agent, and what is being done. + ToM Metrics: How do we ""measure"" ToM? A classic evaluation of ToM capabilities is the Sally-Anne Test and while studies have designed their own versions of the Sally-Anne test, we hypothesize that ToM is a process not tied to performing any one task is particular; it also requires adaptability in learning and understanding. Research in child development proposes several stages to ToM development each of which may help yield tests or a battery of tests for measuring ToM capabilities. Other research proposes the use of natural language to gauge a model's understanding. + Model: How do we build on recent studies developing ToM models? Is it possible to define a reinforcement learning model for ToM the partakes in open-ended learning? Currently, our best approaches involve using state-of-the-art transformer technologies to train on multimodal datasets, so we inspect such developments to inform our own design choices. + Mathematical formalization: The concepts for ToM arose from studies in cognitive science and psychology, however we would like to attempt to research literature in mathematical cognitive science/psychology/neuroscience to break the problem down in the language of sets/functions, which may facilitate algorithm development. |
Computer Science; Mathematics; Cognitive science; Psychology; Neuroscience; Others with computer science experience and an interest in machine learning/artificial intelligence are welcome to apply. |
| Benjamin T. Files |
Military Information Sciences (MIS) | On-site | ARL West - Playa Vista, CA | XR for Shared Mission Planning, Analysis, and Situational Awareness | Technologies like Virtual Reality and Augmented Reality (collectively XR) create new opportunities to help people understand complex, quickly changing, and highly uncertain information. Research under this project will help us understand how to effectively and efficiently portray information to people and groups to support fast, accurate decision-making, creativity, and adaptability. Specific topics might include: Dynamic filtering, contextual zoom, and information summarization for individual and group awareness Uncertainty portrayal and expression Interacting with new kinds of information Human/Autonomy Interaction in XR |
Computer Science, Human/Computer Interaction, Psychology, UI/UX, Game Design, and related fields |
| Suya You, Sean Hu |
Military Information Sciences (MIS) | Remote | ARL West - Playa Vista, CA | Deepfake Detection | Deepfake - an emerging AI digital manipulation technology is being increasingly weaponized, posing a significant threat to our society and national security. The original concept of deepfake or AI-synthesized hyper-realistic images or videos, has been decried primarily in connection with involuntary depictions of people. Recently, significant concerns have been raised about a far more nefarious threat, Deepfake geospatial data (i.e., satellite images, maps, digital terrain models, etc.), which drives deepfakes to another level. Geospatial data plays a pivotal role in mission planning and operations. Imagine a scenario in which a data analyst or mission planning software is fooled by faked satellite image or map that shows a non-existent bridge in marching route, or a terrain model of fake road obstacles being transmitted to an autonomous vehicle to mislead its navigation system. Deepfakes are increasingly used to manipulate scenes and pixels/objects to create artifacts on geospatial data for malicious purposes. This project aims to develop novel techniques and solutions for detecting and defending against deepfake attacks on geospatial data. It will focus on theoretical research and practical algorithms that enable deepfakes of geospatial data to be detected and defended respecting the functional and physical properties of real scenes. We have developed a breakthrough method for detection of deepfake face images to support mission-essential tasks such as adversarial threat detection and recognition. This technique achieves a lightweight, low training complexity and high-performance deepfake face detection. We will enhance and extend this theory and framework for the detection and recognition of deepfake geospatial data including satellite images, maps, and digital terrain data. Anticipated research results include new theory and algorithm developments leading to publications in scientific forums and real-world utility and software for evaluation. |
Computer science, Electrical Engineering, AI/ML |
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| Rajneesh Singh |
Military Information Sciences (MIS) | Hybrid | ALC - Adelphi Laboratory Center, MD; APG - Aberdeen Proving Ground, MD; Graces Quarters, MD | Intelligent Systems Research Opportunity | The Science of Intelligent Systems Division (SISD) has multiple internship opportunities for research on increasing complexity levels, robustness, and resilience of autonomy to enable future unmanned aerial and ground systems to perform semi-autonomous to fully autonomous maneuvers. This includes foundational research on developing improved vehicle perceptual, learning, reasoning, communication, and advanced mobility capabilities. Research in autonomy utilizes continuous experimentation to investigate, assess, and improve advanced algorithms as well as assess ARL autonomy stacks – integrated perceptions, processing, and control software modules - for autonomous behavior for various air and ground vehicle platforms. Internship project locations are Robotic Research Collaboration Campus (R2C2) test site at Graces Quarters, Autonomous System Integration Lab at APG, and Emmerman Intelligent Systems Lab at ALC. Internship opportunities are available in the following research areas: - Hardware/software integration and data generation for perception sensors (integrate sensors onto robot and into autonomy stack, collect data, label data, update algorithms). - Legged robot controllers’ investigations in uncertain environment and integrating perception to enable legged robots to reason about the world they move through. - Autonomy and related technologies to enable BVLOS flight in congested environments including proximity to terrain flights or flying through forest. - Simulations on integrating autonomy and coupling AI and autonomy for next generation robotics and multi-agent teaming. Evaluate and assess simulations applications to develop autonomous behaviors using reinforcement learning. - Soft robotics manipulations to overcome inherent limitations of traditional rigid manipulators. - Experimentally evaluate novel learning-based techniques for control, navigation, perception, and state estimation for ground and/or small aerial robotics -Research multi-agent coordination and collaboration techniques for small teams of autonomous robots |
Computer Science, Aerospace, Mechanical, and Electrical and Electronics |
| Gail Vaucher |
Military Information Sciences (MIS) | On-site | WSMR - White Sands Missile Range, NM | Tactical Power Hybridization– Hydrogen Fuel Cell and Photovoltaic Investigation (Phase 2) | Battlefield electrical power requirements continue to grow with the deployment of new devices, DEVCOM ARL is proactively investigating the hybridization of multiple power sources and the exploitation of atmospheric intelligence to meet this increasing demand. Researchers are actively exploring the use of photovoltaic (PV) and hydrogen fuel cells (HFC) as part of a future mobile recharging unit. Building on the strong foundation established by the FY24-AIAD HFC Internship research and subsequent advances at DEVCOM ARL, students will have the opportunity to work with state-of-the-art equipment currently being tested for tactical integration. Collaborating with DEVCOM ARL scientists, students will apply analysis techniques to the HFC/PV and atmospheric data that is populating the laboratory's research and development (R&D) archives. The insights and recommendations gleaned from this joint effort will help shape the FY26 R&D program. |
All STEM fields are invited. |
| Robb M. Randall |
Military Information Sciences (MIS) | On-site | WSMR - White Sands Missile Range, NM | Atmospheric Effects for Decision Advantage and Lethality Overmatch | These efforts conducts Army-focused environmental security research across multiple temporal operating pictures which feed a cross-echelon situational awareness for command and control decisions. This effort includes research on dynamics and changes in the atmospheric boundary layer in complex Multi-Domain Operations (MDO) environments and conditions (complex terrain/ dense urban and unique or dynamic regions of atmospheric change) with particular emphasis on the atmospheric surface layer and the land- surface processes, which inform Windows of X (mitigating vulnerability, exploiting opportunity, etc) in planning and operations. The effort will also investigate atmospheric effects on multi-modal sensing for detection, localization and tracking to improve accuracy of aided target recognition for air and ground defense in an increasingly uncertain and rapidly changing threat environment. This effort applies foundational research in atmospheric impacts and effects on DoD systems and operations. Research will employ experimental data collection and model development of Atmospheric Boundary Layer conditions and impact on key systems in achieving freedom of maneuver and lethality overmatch. Focusing research on atmospheric characterization and modeling of complex atmospheric conditions in challenging terrain provides prediction and correction information for developing Army systems for kinetic and non-kinetic collaborative protection, protection and exploitation of electromagnetic spectrum for tactical advantage (to include renewable energy), detection and characterization of threat and toxic industrial aerosol, resilient and robust sensing and counter-sensing for UAVs, and models for UAV flight dynamics and high-speed flight systems operating under extreme conditions. |
Recommended degrees (depends on specific project), Atmospheric Science, Data Science, Computer Science, Most Engineering degrees, Statistical Science,. |
| Geoffrey Goldman |
Network Cyber & Computational Sciences (NCCS) | Remote | ALC - Adelphi Laboratory Center, MD | Transformers with 2D positional encoding for acoustic classification | Develop new techniques to encode 2D positional information for processing acoustic data in time and frequency. Implement the technique on a neural network and evaluate results. | Computer science |
| Kevin Chan |
Network Cyber & Computational Sciences (NCCS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Tactical Networks and Communications | Student research includes work in adaptive networking and communications focusing on theories, methods, algorithms, and experimental approaches to enable resilient communications in complex and contested environments via novel communication modalities, multi-layer adaptive protocols for robust information delivery (including storage, computing, and communications), interpretable and adversarial machine learning to enable autonomous control of heterogeneous network structures and dynamics for resilience to adversarial attacks. | CS, ECE |
| Robert F. Erbacher |
Network Cyber & Computational Sciences (NCCS) | On-site | ALC - Adelphi Laboratory Center, MD | CyberSecurity | This project will focus on enhancing the security of Army relevant systems. There is the potential for collaboration in different sub-projects. 1. Methods for developing cybersecurity insights from data collected from robotic vehicle platforms; 2. Development of novel secure and resilient models for enterprise and/or edge devices; 3. Exploration of AI/ML techniques to improve cyber capabilities and efficiency. | Computer Science/Engineering |
| Matthew Dwyer |
Network Cyber & Computational Sciences (NCCS) | Hybrid | APG - Aberdeen Proving Ground, MD | Artificial Intelligence in Edge Environments | Alongside DEVCOM ARL researchers, the applicant will develop and deploy Artificial Intelligence (AI) algorithms and applications, and analyze their effectiveness in resource constrained, dynamic environments. Intelligence, Surveillance, and Reconnaissance (ISR) applications largely depend on AI models to effectively deliver analysis from data gathered at sensor devices. Like traditional computer applications, these models behave poorly when resources are limited through environment constraints and dynamics. We are focused on developing and validating solutions that enable robust, quality, high performance ISR in constrained, dynamic environments. This effort has several areas of opportunity where the applicant can contribute. Specifically, the applicant can learn and contribute in one or more of the following areas: AI model and algorithm development, data pipelining, distributed processing, and data visualization. Applicants can expect to join a welcoming team environment centered around active learning, discovery, and delivery of concepts and ideas in rapid prototypes. | Computer Science, Software Engineering |
| Michael De Lucia |
Network Cyber & Computational Sciences (NCCS) | Hybrid | APG - Aberdeen Proving Ground, MD | Data Science and Machine Learning applications to Cyber Security | Machine Learning (ML) and data science have become integral parts of many domains (e.g., image analysis, networking protocols, network security, etc.), resulting in increased motivation for applications to cyber defense tools. Furthermore, the rapid rate of attacks and the immense volume of data significantly increase the demand on a small number of human analysts. This necessitates the use of data science and ML techniques to enable scalability and reduce the demand on human analysts. However, there are many challenges in the successful use of data science and ML for cyber security problems. Increasingly, supervised learning relies on a significant amount of quality labeled data. To avoid the requirement for a significant amount of labeled data, it is necessary to innovate semi-supervised methodologies in a resource-constrained domain for network communications in the cyber domain. In the network/communications domain, machine learning-based classifiers are generally trained within a closed environment. Specifically, datasets used for training and evaluation are static and do not vary. Conversely, network environments are dynamic over time. Adversaries' attacks become more sophisticated and change in response to defenders' actions, requiring a defender to retrain a classifier to reflect the new attacks in the intended environment for deployment. This research is focused on data science and ML applications to network traffic (i.e., network traffic analysis, network forensics). Example key research questions include the following: • How do we design ML-based network traffic classifiers using a limited amount of data? • How do we leverage ML for network traffic classifiers in a resource-constrained environment? • How can we apply ML to network forensics problems? |
Cyber Security, Computer Science, Computer Engineering |
| Venkateswara Dasari |
Network Cyber & Computational Sciences (NCCS) | Hybrid | APG - Aberdeen Proving Ground, MD | Generalized AI model optimization for inference acceleration | This research aims to develop innovative approaches for accelerating generalized AI model inference on resource-constrained heterogeneous edge computing platforms. The project seeks to achieve this goal by developing theoretical models that understand the trade-offs between accuracy, latency, and compression of optimized AI models, as well as investigating state-of-the-art model optimization approaches such as quantization, and model pruning to reduce computational complexity and to accelerate the inference. Additionally, the research will formulate mathematical foundations to guide optimization processes and ensure convergence to optimal solutions while satisfying constraints. This work covers both convolutional neural networks and large language models and aims to predict optimal AI model architecture through neural network architecture search (NAS) for inference acceleration. | Computer Science |
| Vincent Perry |
Network Cyber & Computational Sciences (NCCS) | On-site | APG - Aberdeen Proving Ground, MD | End-to-End Data Science Workflows on High Performance Computing Machines | The goal of this project is to investigate approaches for a distributed data processing and analysis pipeline on High Performance Computing (HPC) resources. The specific focus will be on containerizing services, GPU utilization, and exploring persistently running services. The project entails familiarizing with the current software stack, workflows, and analytic models. The interns will conduct a survey of data science capabilities, understand the HPC domain, implement data science services in a tool stack, and evaluate usability on the HPC resources. This entails prototyping various configurations for scaling up analytical workflows on the HPC systems and evaluating the approaches for effectiveness and performance. The interns will evaluate both model performance and runtime performance and suggest recommendations for future directions with model design and tools deployment. This internship will require extensive research be performed on analytics approaches and will require previous programming experience and the technical ability to quickly test and prototype applications. The intern will be in a unique position to collaborate with the DEVCOM ARL DSRC Data Science team, gaining exposure to a relevant Army use case for utilizing this technology and first-hand experience observing research and development for the Army. This project will provide the opportunity to experiment with state of the art data analysis, processing, and visualization tools on HPC resources. The internship will be a 10 week project where the intern researches capabilities, understands the HPC domain, and conducts experimentation and analysis. |
Computer Science, Data Science, or similar discipline |
| Suya You, Sean Hu |
Network Cyber & Computational Sciences (NCCS) | Remote | ARL West - Playa Vista, CA | Deepfake Detection | Deepfake - an emerging AI digital manipulation technology is being increasingly weaponized, posing a significant threat to our society and national security. The original concept of deepfake or AI-synthesized hyper-realistic images or videos, has been decried primarily in connection with involuntary depictions of people.. Recently, significant concerns have been raised about a far more nefarious threat, Deepfake geospatial data (i.e., satellite images, maps, digital terrain models, etc.), which drives deepfakes to another level. Geospatial data plays a pivotal role in Army mission planning and operations. Imagine a scenario in which an intelligent analyst or mission planning software is fooled by fake satellite image or map that shows a non-existent bridge in marching route, or a terrain model of fake road obstacles being transmitted to an autonomous vehicle to mislead its navigation system. Deepfakes are increasingly used to manipulate scenes and pixels/objects to create artifacts on geospatial data for malicious purposes. This project aims to develop novel techniques and solutions for detecting and defending against deepfake attacks on geospatial data. It will focus on theoretical research and practical algorithms, which enables deepfakes of geospatial data to be detected and defended respecting the functional and physical properties of real scenes. We have developed a breakthrough method for detection of deepfake face images to support mission-critical data integrity protection. This technique achieves a lightweight, low training complexity and high-performance deepfake face detection. We will enhance and extend this theory and framework for the detection and recognition of deepfake geospatial data including satellite images, maps, and digital terrain data. Anticipated outcomes include new theory and algorithm developments leading to publications in scientific forums and real-world utility and software for Army evaluations. |
Computer science, Electrical Engineering, Applied math |
| Charles Rong; Madan Dubey |
Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Investigate the electronic bandgap of 2-D materials as a function of structural characteristics and the applied transversal electric field | Investigate the electronic bandgap of 2-D materials as a function of the number of layers and the applied transversal electric field, study the optical bandgap of 2-D materials with respect to structural variation and external field change through photoluminescence and X-ray photoelectron spectroscopic measurements, or on related topics and employed methodologies. | Physical sciences and engineering |
| Charles Rong; Madan Dubey | Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Explore graphene/MoS2 heterostructures by fabrication and characterization of graphene/2-D materials contacts | Using graphene as the contact electrode for MoS2 will provide a new degree of freedom in reducing the resistance of ohmic in contacts, with an ability to tune the Fermi levels of semi-metal behavior by electrostatic doping and to tune the Schottky barrier height between graphene and other transition metal dichalcogenides to achieve reduced the ohmic contact resistance. | Physical Sciences and Engineering |
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| Charles Rong; Madan Dubey | Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Explore the design and initial fabrication and characterization of a graphene/MoS2 based power amplifier | Focusing on critical electric field and electron mobility enabled/exhibited by the graphene/MoS2 heterostructure, explore the possibility of those new characteristics suitable for individual, or ubiquitous applications in DC, RF, and pulsed operations. Perform an initial trial of fabrication of a device, and other related topics and methodologies will also be possible to explore. | Physical Sciences and Engineering |
| Charles Rong; Madan Dubey | Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Explore different forms of Molybdenum precursors in the growth and materials quality of MoS2 layers | Molybdenum containing compounds will be explored as precursors for the growth of MoS2 that forms mono and multiple layers of 2-D materials on substrate. Type of the molybdenum compounds, quantity of Mo to be used, and reaction conditions will play important roles with respect to reaction kinetics, mass transfer, and heat transfer. Optimization of the growth reaction parameters may generate larger sized MoS2 layer(s), and with lower levels of structural defects. Other related topics and methodologies will also be possible to explore. | Physical Sciences and Engineering |
| David Meyer |
Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Quantum Science and Technology | Assist in the development of quantum systems for sensing and quantum information applications. Such systems leverage unique effects of quantum mechanics to enhance detection of electromagnetic fields, gravity, and time or perform optimized computational operations. Work in this area spans a wide range of technical skills and disciplines, and will focus on developing critical component technologies including lasers and optical apparatuses, electronics, material growth, or experimental automation and control. | Physics, CompSci, Engineering |
| James Cahill |
Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Technologies for Integrated Photonic Oscillators | This project will support our ongoing efforts to bring the exciting field of optical frequency division to the form factor of an integrated chip. Optical frequency division uses optical frequency combs (OFCs) to divide the frequency of an optical frequency reference (such as an optical resonator or optical atomic transition) to a microwave output signal, whose frequency is usable in conventional circuits. One of the enduring challenges in bringing this technology to the chip scale is generating on-chip OFCs with repetition rates that are sufficiently small (e.g., <40 GHz) to work with conventional electronics while simultaneously minimizing the required power (i.e., optical power in the case of microresonator OFCs and RF power in the case of electro-optic modulator OFCs). In this project, the student will work towards generating microwaves with frequencies <40 GHz using on-chip OFCs that require practical amounts of power. This project may involve characterizing OFC devices, building fiber-optic characterization circuits, making precision frequency noise measurements, and other related tasks. | Physics, Electrical Engineering, Optical Engineering, or a similar field |
| Joydeep Bhattacharyya |
Photonics, Electronics, & Quantum Sciences (PEQS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Acoustic and Seismic Sensing and Signal Processing | Further research is needed to advance the understanding of novel acoustic and seismic sensing strategies, including signal-to-noise optimization through software and hardware developments. The project may include advanced work towards data handling, including machine learning solutions to multimodal sensor fusion. | Physics, Engineering Science, Engineering Mechanics |
| Joydeep Bhattacharyya |
Photonics, Electronics, & Quantum Sciences (PEQS) | Hybrid | ALC - Adelphi Laboratory Center, MD | Acoustic and Seismic Sensing and Signal Processing | Further research is needed to advance the understanding of novel acoustic and seismic sensing strategies that also includes signal-to-noise optimization though software and hardware developments. May include advanced work towards data handling to include machine learning solutions to multimodal sensor fusion. | Physics, Engineering Science, Engineering Mechanics |
| Oluseyi Ayorinde |
Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Demonstrating Speech Recognition using ARL-developed AI chip | This project aims to hire one student to create a demonstration of an ARL-developed AI chip performing speech recognition. The AI chip is designed using a 12nm finfet process and has state-of-the-art AI inference efficiency. The student will connect the AI chip development board to a microphone input to capture speech commands, and an output screen to display the commands correctly. The development board will also be connected to source meters to show power consumption of the speech inference. The student will be located at DEVCOM ARL headquarters in Adelphi, MD. The project mentor will be remote, but visit regularly, and other team members will work at DEVCOM ARL headquarters. | Electrical Engineering, Computer Engineering, Computer Science |
| Sang-Yeon Cho |
Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Meta-Optic Integrated Circuits | This summer research project focuses on developing meta-optic components for integration into photonic circuits. Participants will utilize various optical materials and advanced numerical modeling techniques to investigate the unique capabilities of meta-optics in manipulating light at subwavelength scales, with the ultimate goal of enhancing the performance and functionality of photonic integrated circuits. | Electrical Engineering, Physics, Mechanical Engineering |
| Robert Burke; Nick Strnad | Photonics, Electronics, & Quantum Sciences (PEQS) | On-site | ALC - Adelphi Laboratory Center, MD | Atomic Layer Deposition of AlN | Atomic layer deposition of high-quality thin films of the electronic device material AlN is not well developed yet. Several systematic AlN ALD experimental runs will be conducted, and the resulting thin films will be characterized in terms of thickness uniformity, surface roughness, and crystallinity for piezoelectric, optoelectronic, and dielectic applications in densely integrated chips. | Materials Science, Chemistry, Physics |
| Paul Kunz | Photonics, Electronics, & Quantum Sciences (PEQS) | Remote | ARL South - Austin, TX | Quantum Sensing with Atoms and Optics | Assist in the development of quantum systems for sensing and quantum information applications. Such systems leverage unique effects of quantum mechanics to enhance detection of electromagnetic fields, gravity, and time or perform optimized computational operations. Work in this area spans a wide range of technical skills and disciplines, and will focus on developing critical component technologies including lasers, photonics, RF electronics, or experimental automation and control. | Physics, CompSci, Engineering |
| Oluseyi Ayorinde |
Photonics, Electronics, & Quantum Sciences (PEQS) | Remote | ARL West - Playa Vista, CA | Neuron Place-and-Route (NPR) Development | Interns will work with DEVCOM ARL scientists to expand the capabilities of the Neuron Place and Route (NPR) tool, developed by DEVCOM ARL, which is used to map deep neural networks (DNNs) to the DEVCOM ARL-developed Field Programmable Neural Array (FPNA) chip. This intern will work on developing a graphical user interface (GUI) for the tool, as well as adding additional features. | Computer Science, Electrical Engineering, Computer Engineering |
| Daniel Magagnosc |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Laser Micromachining for High-Throughput Mechanical Testing | Accelerating materials discovery is key to delivering novel materials solutions. One rate limiting step in the materials development chain is the evaluation of mechanical properties, particularly ductility and fracture properties. To address the challenge, high-throughput sample fabrication and testing methodologies must be developed. One potential solution is femtosecond laser micromachining of millimeter scale specimens. In this opportunity, the participant will support development of laser machining protocols employing the unique laser facilities at DEVCOM ARL and demonstrate the high-throughput capacity by testing the machined specimens. The outcomes of this research will contribute to current and future DEVCOM ARL materials development programs. | 1 |
| David McLeod |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Composite and Hybrid Materials | Students will gain experience in synthesizing and characterizing a variety of composite and hybrid materials, which may include carbon-carbon composites and 2D polymer films (exact project will depend on U.S. Army needs at the time and student interests). | Chemistry, Materials Science, Engineering |
| David McLeod |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Composite and Hybrid Materials | Students will gain experience in synthesizing and characterizing a variety of composite and hybrid materials, which may include carbon-carbon composites and 2D polymer films (exact project will depend on Army needs at the time and student interests). | Chemistry, Materials Science, Engineering |
| Efrain Hernandez |
Science of Extreme Materials (SEM) | Hybrid | APG - Aberdeen Proving Ground, MD | Towards the Gold-Standard Solution to the PFHub Benchmark | The intern will explore different initial solutions to the Phase Field Hub's benchmark problem 1a. This problem has been shown to lack periodicity, which can be detrimental to spectral methods. The intern will use a python-based solver and explore alternative solutions. | computer science or engineering or physics |
| Faheem Muhammed |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Composite Fabrication and Analysis | This opportunity focuses on providing students with a foundational background in fabricating and characterizing fiber-reinforced composites to evaluate their material properties. Students will engage in the production of these composites using various resin transfer molding techniques. They will also gain significant experience in data reduction and model development using tools such as MATLAB, Python, COMSOL, ABAQUS, and/or Excel to correlate fabrication parameters with performance outcomes. Throughout this opportunity, students will gain hands-on experience in thermal and mechanical characterization through methods like differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and tensile testing. Additionally, students will have access to microscopy techniques, including scanning electron microscopy (SEM) and micro-computed tomography, to analyze the microstructure and surface characteristics of the composites. Further training opportunities in techniques such as mercury intrusion porosimetry, pycnometry, X-ray diffraction, electron spectroscopy, and wet chemistry synthesis/purification will also be available. This hands-on project is expected to provide valuable experience in composite fabrication, materials characterization, and data-driven analysis, effectively preparing students for careers in the composites industry. | Chemistry or Engineering (Chemical, Materials, or Mechanical) |
| Harvey Tsang |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Convergent Manufacturing of Electronic Material | The project involves designing, fabricating, and testing electronic devices manufactured with novel convergent manufacturing techniques. These techniques utilize novel CAD/CAM software and equipment. The electronic devices will be evaluated for their material properties in extreme environments. | Post-Bachelors |
| Ian McAninch |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Additive manufacturing of highly filled systems | The primary focus of the researcher will be to formulate and additively manufacture high solids loaded resins and polymers for application to structural or energetic materials. The researcher would characterize the thermal and mechanical properties of the polymer via DSC, DMA, mechanical testing, rheology, and/or microscopy. Depending on the student’s interest, aspects of the research can be to prepare and scale up chemical reactions and separations to produce monomers and polymerizable oligomers for light curing and thermal curing additive manufacturing techniques with DEVCOM-ARL expert chemists. The researcher would then characterize these chemicals using FTIR, NMR, and other techniques. |
Engineering (any), Chemistry, materials science |
| Jian Yu | Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Advanced Manufacturing Process | Convergent Manufacturing (CM) is the term used to describe fabrication of multifunctional devices and structures and can incorporate any number of manufacturing technologies and materials to fabricate these products. CM is expected to revolutionize the design, fabrication and application of electronic packaging and antenna structures. An objective of this project to establish process-material-design relationships for convergent manufacturing of conformal electronics embedded into 3D printed structures. The researcher will: develop feedstock materials, including conductors, dielectrics, and insulators; develop manufacturing processes, such as aerosol deposition, inkjet printing, SLA, FFF, injection molding, ultrasonic welding, robotic milling and drilling, and plasma modification; develop manufacturing parameters to prepare the materials/parts. | Aerospace, Chemical, Electrical, Mechanical, Industrial, etc. all engineering and Core STEMs (Math, Physics, etc.)) |
| Jian Yu | Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Science of Manufacturing: Metal Additive Manufacturing | 3D Printing, known as Additive Manufacturing (AM), is transforming the manufacturing industry. ARL is creating great strides in AM science and technology (S&T) to solve the Army challenges and mission readiness. Effective numerical and experimental methods for quantifying properties of the AM parts during the printing process are critical for enabling AM applications. Understanding the relationships between processing, microstructure, and properties of these material is critical to drive development of future metallic feedstock alloys. | All STEM |
| Joseph Labukas |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Mechanisms of Material Degradation | The focus of projects in our laboratory is on degradation of a wide range of materials including metals, ceramics, plastics, and composites through chemical, biological, and physical mechanisms. Research in this laboratory will broaden the scientific understanding of the researcher, expose them to a variety of highly-technical instruments and techniques common throughout many laboratories, and provide a learning environment that fosters scientific curiosity and discovery. | Chemistry, Biology, Biochemistry, Materials Science, or similar. |
| Krista Limmer |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Development of High-Performance Army-Relevant Steels | Enhanced protection and lethality steel alloys are being developed to provide warfighters with a strategic advantage in an increasingly complex military engagement domain. The materials being developed today will support warfighters tomorrow, and there are numerous projects where cadets can participate in vetting these future materials. Cadets will experience the full range of research and development activities, including metallurgical design concepts, laboratory-scale processing and characterization, industrial production, and application-specific performance evaluation. | Materials Engineering, Mechanical Engineering, Chemical Engineering, Physics, Chemistry |
| Krista Limmer |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Development of High-Performance Army-Relevant Steels | Enhanced protection and lethality steel alloys are being developed to provide warfighters with a strategic advantage in an increasingly complex military engagement domain. The materials being developed today will support warfighters tomorrow, and there are numerous projects where cadets can participate in vetting these future materials. Cadets will experience the full range of research and development activities, including metallurgical design concepts, laboratory-scale processing and characterization, industrial production, and application-specific performance evaluation. | Materials Engineering, Mechanical Engineering, Chemical Engineering, Physics, Chemistry |
| Lionel Vargas- Gonzalez |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Advanced Ceramics for Extreme Conditions | Opportunities exist for foundational and early applied research and development (R&D) efforts towards enabling the next generation ceramics and ceramic composites for Army systems. Research activities include: 1) novel synthesis and processing techniques for opaque and transparent ceramics and composites with optimal structure/properties for extreme environments and high-rate impact, 2) advanced manufacturing science for development of heterogeneous multi-scale ceramics and interfaces with high fracture and failure tolerance, 3) high-throughput simulation, machine learning and design optimization for processing-structure-property relationships, and 4) high-throughput non-destructive evaluation and characterization for materials discovery. | Materials Science and Engineering |
| Nicholas Ku |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Densification of Binder Jet Additive Manufactured Ceramics | Binder jet is an additive manufacturing technique capable of forming advanced ceramics parts with geometric complexity. A major challenge with this process lies in the densification of binder jet parts, as powder feedstocks amenable to binder jetting are often not sinterable. This project aims to explore densification methods beyond solid-state sintering of binder jet ceramics, such as polymer infiltration and pyrolysis (PIP). Ceramics of interest are carbide and boride materials. Process parameters of interest include the binder jet powder feedstock, the polymer chemistry and rheology, the infiltration process, and the thermal processing. | MSE, ChemEng |
| Nicholas Ku |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Structure-Property Relationships in Cemented WC-Co | Cemented tungsten carbide (WC) is an ideal material for cutting tool applications due to its high hardness and wear resistance. The material is comprised of hard WC grains cemented together by a matrix cobalt (Co) phase. The bulk material properties are controlled by aspects of the microstructure, such as the WC grains size/distribution and Co content. This project aims to develop advanced powder processing approaches to engineer complex cemented microstructures. The mechanical properties of these samples will be characterized to develop relationships between the cemented microstructure and bulk material properties relevant to the applications of interest. | MSE, MechEng |
| Paul Moy | Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Application of Virtual Fields Method to Identify the Anisotropic Behavior of Laminated Composite Materials | Laminated composites plays an important role for the Army across many applications due to their high strength-to-weight ratios and design flexibility. These materials are widely used in personnel protection, sabots, and UAVs. However, characterizing the mechanical properties of these materials remains a challenge, particularly due to their anisotropic behavior. This project focuses on the implementation of inverse methods based on the Virtual Fields Method or VFM to enhance the identification of material properties of laminated composites. VFM allows for the extraction of mechanical parameters from measured displacement/strain fields from Digital Image Correlation (DIC) obtained during experimental testing. By applying this approach, we will develop a robust framework that integrates experimental data with computational modeling. The outcomes of this research will not only enhance the fundamental understanding of laminated composites but also provide valuable insights for the design of safer and more efficient composite structures across multiple industries. |
Mechanical Engineer, Materials Engineer |
| Tucker Moore |
Science of Extreme Materials (SEM) | On-site | APG - Aberdeen Proving Ground, MD | Ultra High Temperature Ceramic Processing | Ultra-high temperature ceramics (UHTCs) with melting points of over 3000°C are promising materials for a variety of high temperature applications. However, they are difficult to form into complex shapes and are typically made by sintering into a basic shape with applied pressure followed by expensive diamond grinding. In this project, the student will work on fabricating UHTCs into near net shape parts by pressureless sintering. | Materials Science and Engineering; Ceramic Science and Engineering |
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| Krista Limmer |
On-site | APG - Aberdeen Proving Ground, MD | Rate Controlled Tempering Effects | This summer internship project will develop skills related to understanding and utilizing fundamental structure processing property relationships in steel. The project will integrate modeling-informed experimental design with applied heat treatments and characterization. Technical training on new tools and techniques will be provided throughout the summer internship in addition to professional development opportunities and experiences within DEVCOM ARL and across APG. | Materials Science, Metallurgical Engineering, Materials Engineering, Mechanical Engineering | Experience with metallography, electron microscopy, mechanical testing, knowledge of metallurgy and thermodynamics |
| Michael Nicholas |
Science of Extreme Materials (SEM) | Hybrid | ARL Northeast - Boston MA | Cold Spray | Preface: DEVCOM ARL has developed an emerging technology known as ‘Cold Spray’ which offers unique materials and structures solutions not possible by conventional technologies. Cold Spray enables materials and coatings with improved properties and increased functionality while reducing weight, improving performance, durability and cost reduction for application to individual soldier support equipment, armor, armaments, aircraft, ground combat vehicles and combat support equipment. Duties: The incumbent will perform research and development in Supersonic Particle Deposition (SPD) or Cold Spray, specifically with the complexities associated with the flow and consolidation of micro particulates within a supersonic gas stream. The incumbent will be responsible for performing development work in Cold Spray for alternative coatings for Disc Brake applications. This work will involve conducting studies to optimize SPD process parameters and to Test & Evaluate Alternative Disc Brake Stator & Rotor Composite Coatings (produced from a soft phase matrix material and a hard phase) to provide wear & corrosion protection and eliminate/minimize brake dust. The incumbent will also be involved in SPD system design and modification to improve the process beyond current capabilities. Emphasis will be in optimizing the coating adhesion and microstructure through process development to provide an even coating and homogeneous second phase particle distribution. The incumbent will perform materials characterization including metallography and mechanical testing of the experimental coating. The coatings materials being analyzed include: Matrix materials (Ti-6Al-4V and 430L), Hard Phase Materials (WC, SiC and TiC) |
Mechanical or Materials Engineer |
| Steven Hubbard |
STEM Outreach | Hybrid | ALC - Adelphi Laboratory Center, MD | Business Application Development | Participate as a developer in the Digital Business Office helping to create enterprise applications for the lab. The Application Developer is responsible for designing, developing, and maintaining business applications using the ServiceNow platform. This role focuses on enhancing business processes by implementing customized solutions, improving data workflows, and providing insights through advanced reporting and data visualization. The project will focus on learning development processes, such as Agile Scrum methodologies, and developing in Low Code/No Code platforms such as ServiceNow and Tableau. The developer will also be assigned to support one of the development teams to test new application functionality and report findings to the project stakeholders. | Computer Science, Information Technology, or a related field encouraged but not required |
| Jonah Sengupta |
Terminal Effects (TE) | Hybrid | APG - Aberdeen Proving Ground, MD | Open Source Full Stack Development for Sensor Fusion Testbed | This project will entail developing new software for sensor deployment in DEVCOM ARL experimental facilities and off-site test events. Accurate, synchronized data capture is incredibly important for algorithm development in applications of AiTR, tracking, and situational awareness. The sensor testbed includes a range of infrared and neuromorphic cameras. These all leverage a variety of proprietary software interfaces which are not compatible many Army systems. This project entails using open-source software, like Aravis and PyHarvester, to create an open source software stack to configure and stream data from these cameras. Scripts from prior projects can be leveraged for initial development. In addition to backend development, a graphical user interface needs to be designed to allow the end-user to run the testbed. Finally, the project will entail designing methods to store large scale camera datasets and customize metadata for later use. | Computer Science, Electrical Engineer, Computer Engineer |
| Karin Rafaels |
Terminal Effects (TE) | Remote | APG - Aberdeen Proving Ground, MD | Injury Biomechanics | This position involves developing experimental procedures, analysis techniques, and advanced modeling approaches in a greater effort to measure, understand, or predict the biomechanics of biological tissue in high-rate impact scenarios. The work performed in this position will support a larger effort to improve computational human body models designed for simulating impact events by contributing to more biofidelic constituent materials and models and reproducing more realistic loading conditions. | Biomedical Engineer, Mechanical Engineer, Computer Science, Mathematics, Applied Mathematics, Physics |
| Ben Topper |
Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Airgun control system overhaul | DEVCOM ARL has several airguns located at Adelphi Laboratory Complex (ALC). The current 7-inch airgun system is controlled by series of disparate and improvised devices and interfaces. Modifications and "band-aid" repairs to the system over several decades has led to an amalgam of interfaces and controls that are outdated and non-obvious. These “quirks” result in a system that is unnecessarily complex to operate and potentially makes the system less reliable and less safe to operate. This proposed effort would task a summer student with learning about the operation of this system and then working with DEVCOM ARL mentor and team to conceive, design and implement a modern comprehensive control system. Specific tasks would likely include: • Identify and diagram of current airgun system • Removal of existing unnecessary airgun control hardware. Any hardware/systems that can continue to be used should be characterized and documented. • Propose modernized control and instrumentation setup to include system diagrams, market research, modeling and peer review • Hands-on modifications and installation of a new, unified airgun control and triggering system. This system should control all airgun firing operations, diagnostic instruments, and safety measures and should operate with minimal differences in setup and procedures between atmospheric and positive pressure shots. |
Mechanical Engineering |
| Brian C. Barnes |
Weapons Sciences (WS) | Hybrid | APG - Aberdeen Proving Ground, MD | Machine Learning for Energetic Materials | Summer researchers will have the opportunity to investigate R&D of artificial intelligence and machine learning (AI/ML) methods to be applied to problems for energetic materials (explosives and propellants). | Chemistry, Computer Science, Physics, Chemical Engineering, Mechanical Engineering, Computer Engineering, Mathematics, Statistics, or related |
| Chi-Chin Wu |
Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Understanding of Plasma Surface Treatment of Aluminum Nanoparticles (nAl) via Materials Characterization and Simulation Modeling | The intern is expected to perform characterization for untreated and surface-treated aluminum nanoparticles using experimental and/or simulation modeling approaches. Experiments will aim to study properties including but not limited to porosity, particle size distribution, surface chemistry, morphology, and chemical composition using different techniques and equipment available in the group and at DEVCOM ARL. Simulation models will be attempted using the COMSOL Multiphysics available at DEVCOM ARL and in collaboration with industrial partners. | Engineering and Sciences majors, such as Materials Science and Engineering, Chemical Engineering, Mechanical Engineering, Chemistry, Physics |
| Elliot Wainwright |
Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Internal Fireball Reactions, Intensity, and Temperature (IFRIT) | The project involves implementing a newly designed and constructed DEVCOM ARL hyperspectral imaging system as a novel diagnostic to understand the internal structure of the fireball produced by aluminized explosives. The investigation will focus on optimum pinhole array configurations (spacing, hole size, etc.) of the system for expected fireball scenes. The system will be calibrated using the optimum pinhole array and a blackbody furnace. Students will collect internal fireball data from metallized and conventional HE charges with simple detonation experiments. Time permitting, data processing/management routines will be established. | Mechanical Engineering, Chemical Engineering, Materials Science & Engineering, Applied Physics, Physics, Electrical & Computer Engineering |
| Elliot Wainwright |
Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Shock impact of metal reactive materials | Laser-driven flyer plates (LDFP) can be utilized as a small-scale platform to induce high-pressure and shock conditions to powder beds. LDFP uses a focused, high-power laser to propel a small impactor into a sample of interest. This project is focused on using LDFP to impact a wide range of metal powders of varying composition to understand the mechanical and chemical response of the material under shock loading. Project will include learning the LDFP system, collecting data for a variety of samples, processing the data, and compiling the results into a final report. | Materials Science & Engineering, Mechanical Engineering, Chemical Engineering, Physics, Applied Physics, Chemistry |
| Hao Kang | Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Advanced Vertical Takeoff and Landing (VTOL) Aircraft Technologies | This project will focus on developing algorithms, methods, and analysis tools for aeromechanics predictions, performance assessment, acoustics, flight mechanics, and design space exploration of VTOL vehicles for sizes ranging from small unmanned aerial systems (UAS) to large vehicles. These algorithms and methods include, but are not limited to, physics-based modeling and simulation, high-fidelity modeling and analysis, reduced-order modeling and approaches, AI/ML-based algorithms, and optimization algorithms. This project also focuses on developing new technologies to achieve revolutionary improvements in vehicle performance across different flight regimes. These technologies include, but are not limited to, active flow control, passive and active structural shape control, adaptive morphologies, and AI/ML for flight control and improved aeromechanical behaviors. This project will explore innovative vehicle and reconfigurable concepts for large VTOL platforms and micro/small autonomous air vehicles. Develop design tools for innovative vehicle platforms and reconfigurable concepts. | Aerospace engineering |
| Jennifer Gottfried |
Weapons Sciences (WS) | On-site | APG - Aberdeen Proving Ground, MD | Microscale characterization of energetic material reactions | DEVCOM ARL's microscale characterization laboratory is seeking motivated graduate students to spend the summer obtaining data on various reactive materials and other energetic materials. Relevant techniques include sensitivity measurements (electrostatic discharge, impact, and friction), the laser-induced air shock from energetic materials (LASEM) method, and confined laser ignition experiments. We use various spectrometers, high-speed cameras, and other diagnostics to obtain as much information as possible about the high-temperature reactions of the materials, using the smallest possible quantities (on the order of milligrams). Experience with Matlab, lasers, spectroscopy, and/or cameras is encouraged but not required. | chemistry, physics, engineering, or related STEM field |
| James Humann |
Weapons Sciences (WS) | Remote | Remote, and/or APG - Aberdeen Proving Ground, MD | Multiagent Robotics design and path planning | Multiagent robotic development requires simulation development, mechanical design, and path planning algorithm development. We currently use a mixture of ground robots, tethered drones, and traditional drones. | Computer Science, Mechanical Engineering, Electrical Engineering, Computer Engineering, Aerospace Engineering |
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