Tempe, AZ
Site: Arizona State University
Description:

Undergraduate Project 1 : Characterization of mesoscale architecture in CMCs. The student will learn to use a combination of confocal microscopy and x-ray micro-CT to capture and analyze images of the mesoscale architecture of CMC samples comprising manufacturing related architectural variability and defects. The student will extend an algorithm for microstructure generation, developed by AEOP 2024 students, to reconstruct CMC microstructure at the next material length scale, the mesoscale, and learn how to use advanced ML techniques to generate mesoscale SRVEs, which will be implemented in the high-fidelity models developed in the ARO project.

Undergraduate Project 2: Identifying and quantifying oxidative products and their effects on material properties. The student will use EDS to analyze the amount of oxidation and its effects on CMC coupons. This data will be used to gain more information on the chemical reactions present in CMCs after high temperature testing. This will be followed by TGA to capture the changes in chemical and physical properties as a function of temperature. The knowledge gained from Task 1 on mesoscale characteristics will be useful in determining how they impact the oxidation process; This will require collaboration between UG1 and UG2.

Undergraduate Project 3: Modeling CMC response under thermomechanical loading. The student will learn how to use commercial FE software, ABAQUS, and investigate the accuracy of available damage models. This will be followed by integration of the high-fidelity micromechanics and damage models, developed by the PI, with ABAQUS to model CMC response under various loadings.

Playa Vista, CA
Site: Army Research Laboratories – ARL West
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities. This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Playa Vista, CA
Site: Army Research Laboratories – ARL West
Description: Th

San Diego, CA
Site: University of California – San Diego
Description: In the project, we will focus on Discovering unknown symmetries from spatiotemporal data: Given rich spatiotemporal sensing data with unknown symmetries, we will develop DL frameworks that can automatically discover symmetry inductive biases from the data. Specifically, we will investigate adversarial training algorithms to discover the invariant sets from dynamical systems, Lie algebra convolutional networks to discover symmetry groups, as well as sparse regularization techniques to discover the intrinsic dimensions for efficient representation. We will work with video and trajectory data from cameras, LiDar, and navigational devices, using our symmetry-aware DL models as basic building blocks for dynamics learning and decision-making. We will demonstrate the practical values of our framework to solve challenging tasks including trajectory forecasting, motion planning, surrogate modeling, and video prediction.

Site: San Diego State University
Description: High school interns will work on spider silk collection, isotope labeling, and SSNMR data collecting with the assistance of a post-doc mentor, while the Undergraduate interns will work on isotope labeling and spider silk gland dissection to collect solution NMR data with the assistance of the staff research scientist.

Ft. Collins, CO
Site: Colorado State University
Description:

Intern project 1: Modeling the impacts of chemical conditions and community composition on xylan degradation. The intern for this project will apply modeling tools to soil microbial metabolic models to explore and predict how the chemical condition of the environment and/or the composition of the microbial community influence the microbial metabolic interactions and the resultant xylan degradation performance. Interesting predictions can benefit the construction of synthetic communities for the ARO project and will be tested experimentally by other team members of the ARO project. Through this intern project, the intern will learn and appreciate how computational modeling can aid biotechnology research and predict microbial metabolism based on science and engineering principles.

Knowledge and skills the intern will learn: basics in microbial metabolism, microbial interactions and ecology, metabolic modeling, artificial intelligence (reinforcement learning), and Python programming

Intern project 2: Modeling the effects of regulatory circuits for xylanase expression on xylan degradation The intern for this project will apply the same modeling tools as in Intern project 1 but with a different goal of modeling the impact of different regulatory circuits for controlling xylanase expression, including for example constitutive expression, xylose-negative feedback inhibition, quorum sensing activation. This helps evaluate potential engineering strategies to be used for the ARO project. Interesting predictions will be tested experimentally by other team members of the ARO project. Through this intern project, the intern will learn and appreciate how computational modeling can guide engineering efforts. Knowledge and skills the intern will learn: basics in microbial metabolism, synthetic biology circuits in regulation of gene expression, metabolic modeling, artificial intelligence (reinforcement learning), and Python programming

Intern project 3: Modulating xylanase expression in Bacillus subtilis The intern for this project will modulate the expression of xylanase in B. subtilis using synthetic biology tools. Possible methods of modulation include constructing a library of differential constitutive expression levels using synthetic promoters and ribosomal binding sites, deregulation of catabolite repression, or a synthetic circuit based on xylose feedback or quorum sensing. The engineered B. subtilis strain will be tested in synthetic communities by other team members of the ARO project. Through this intern project, the intern will be introduced to the exciting field of synthetic biology. Knowledge and skills the intern will learn: basics in microbiology and molecular biology, synthetic biology approaches for modulating gene expression

Intern project 4: Characterizing xylan-degrading soil microbial communities The intern for this project will determine microbial functions and interactions by co-culturing soil microorganisms, the model organism B. subtilis, and/or its derivatives under selected xylandegrading conditions. The intern will learn to configure a liquid handling robot for high throughput culturing of microbial communities. The intern will characterize the growth, metabolite conversion, xylanase activity, and composition of a synthetic community of interest and its sub-communities. The data generated will be used for modeling the communities and designing engineering strategies by other members of the ARO project. Through this intern project, the intern will appreciate the complexity of microbial communities and interactions, and the opportunities in engineering them.

New Haven, CT
Site: Yale University
Description: We seek students to perform numerical simulations to quantify the local stress anisotropy of frictional granular beds under different stress conditions for 10 weeks during the summer 2025. One undergraduate student will be responsible for quantifying changes in local anisotropy in response to sub-critical stresses applied in different directions in 2D. The other undergraduate students will extend these studies to 3D packings of frictionless particles. The high school students will develop DEM simulations to investigate the stress history of packings of frictional and non-spherical particles in 3D.

Gainesville, FL
Site: University of Florida
Description: Macromolecules are conventionally considered to be thermal insulators. Interns selected for this opportunity will work to challenge this historic paradigm. Specifically, high school and undergraduate students will work to (1) develop synthetic methods to produce thermally conductive polymers and (2) establish processing methods to produce thermally conductive polymer materials in technologically relevant morphologies (e.g. conformal films or monoliths). Throughout this work, the supported junior researchers will gain experience in polymer design, synthesis, and processing.

Daytona Beach, FL
Site: Embry-Riddle Aeronautical University
Description: Particle-laden flows and flows over particle beds are ubiquitous in engineering and nature. The focus of the current work is understanding the interactions between a turbulent boundary layer and particle beds as well as the interactions within particle-laden flows. The student intern will carry out the following duties with regard to this project:

• 1) Carry out measurements in the boundary layer wind tunnel in the PI’s lab at Embry-Riddle Aeronautical University. The measurements will be within the turbulent boundary layer over a particle bed or within a particle-laden turbulent boundary layer.
• 2) The student will use advanced flow diagnostic techniques such as Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) to characterize the carrier phase as well as particle phase flow as appropriate. This will include the use of high-power or high-speed lasers and high-density or high-speed cameras.
  
• 3) The student will analyze the data using standard PIV/PTV data reduction approaches. As needed, the student will also explore new approaches such as data-driven techniques.

Chicago, IL
Site: ARL Central
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities. This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Champaign, IL
Site: Army Engineer Research and Development Center- Construction Engineering Research Laboratory
Description: The U.S. Army Engineer Research and Development Center (ERDC) is an integral component of the Office of the Assistant Secretary of Defense for Research and Engineering and helps solve our Nation’s most challenging problems in civil and military engineering, geospatial sciences, water resources, and environmental sciences for the Army, Department of Defense, civilian agencies, and our Nation’s public good.  ERDC research laboratories focus on five major areas:

• Military Engineering
• Geospatial Research and Engineering
• Engineered Resilient Systems
• Installations and Operational Environments
• Civil Works and Water Resources

STEM student trainees for this position may be selected to work in laboratories at the Waterways Experiment Station in Vicksburg, MS. This student trainee position will provide the opportunity for development and training in a research and development environment. Assignments become more responsible as the incumbent increases knowledge and skills through work experience and academic training. As a STEM student trainee, you will serve in a role in a professional discipline under close supervision with a mentor, team leader, and/or supervisor. Tasks will vary but may include the following:

• Preparing drawings, graphs, or charts using project data.
• Performing routine scientific and engineering computations using knowledge obtained from academic progress to date.
• Operating or adjusting various types of laboratory equipment and overseeing the function of the laboratory operation required.
• Collecting data for research purposes and using this data to prepare technical reports and publications with conclusions related to projects.
• Entering data into databases and tracking information to provide recommendations for continued project execution.

Undergraduates majoring in or planning to major in physical science, biological sciences, chemistry, engineering, physics, mathematics, statistics, data science, computer science, cyber security, or information sciences will be considered for an internship. Must have a 2.5 or higher GPA on a 4.0 scale or equivalent. Must be a U.S. Citizen. Students must submit to at least a national background investigation (T1 Clearance) with a favorable outcome. High school students 16 years old and older.

Individual projects are available on this site and can be selected during the application process. Applicants can review project descriptions and include their preferences if interested.

Adelphi, MD
Title: Signal and Image Processing Capability Assessments for 3-D SAR Image Formation and Distributed RF Node Tracking and Communication
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: AI and Artificial Reasoning
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Advanced Ferroelectric-Based Sensing, Packaging and Integration
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Laser Spectroscopy of Ultra-Wide and Wide Bandgap Semiconductors
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Developing Speech-to-Text Models for Low-Resource Languages of Military Interest
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: Intern will use open development tools in a Linux environment to train deep neural network models from recorded examples of speech.

Title: Scene Context for Decision Making
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Electromagnetic Effects in Electronics
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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).

Title: Additive Manufacturing for Electronics
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Thermal/Mechanical Engineering Research
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Business Application Development
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Atmospheric Remote Sensing
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Human-AI Collaboration
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Sensor Analytics
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Sensor Analytics Intern
Location: Hybrid
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Atomic Layer Deposition of AlN
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Ultrawide Bandgap Power Switches
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Investigate the Electronic Bandgap of 2-D Materials as a function of structural characteristics and the applied transversal electric field
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Explore Graphene/MoS2 Heterostructures by Fabrication and Characterization of Graphene/2-D Materials Contacts
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Explore the Design and Initial Fabrication and Characterization of a Graphene/MoS2 Based Power Amplifier
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: Explore different forms of Molybdenum precursors in the growth and materials quality of MoS2 layers
Location: On-site
Site: ARL – Adelphi Laboratory Center
Description: 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.

Title: XR for Shared Mission Planning, Analysis, and Situational Awareness
Location: On-site
Site: ARL West
Description: 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

Aberdeen, MD
Title: Machine Learning for Energetic Materials
Location: Hybrid
Site: ARL – Aberdeen Proving Ground
Description: 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).

Title: Additive Manufacturing of Highly Filled Systems
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Data Science and Machine Learning applications to Cyber Security
Location: Hybrid
Site: ARL – Aberdeen Proving Ground
Description: 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?

Title: Enhancing Human Cognition with Foundational Models
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Composite Fabrication and Analysis
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Materials and Tool Development for Neuroscience Research
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Neuroscience and Neurotechnologies
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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?

Title: Hybrid Human-Technology Intelligence
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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?

Title: Human-Guided System Adaptation
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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?

Title: Injury Biomechanics
Location: Remote
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Open Source Full Stack Development for Sensor Fusion Testbed
Location: Hybrid
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Brain Inspired Artificial Intelligence Algorithms
Location: Hybrid
Site: ARL – Aberdeen Proving Ground
Description: 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!

Title: Structure-Property Relationships in Cemented WC-Co
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Application of Virtual Fields Method to Identify the Anisotropic Behavior of Laminated Composite Materials
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Tribology of Materials in Fuels
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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.

Title: Composite and Hybrid Materials
Location: On-site
Site: ARL – Aberdeen Proving Ground
Description: 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).

Title: Intelligent Systems Research Opportunity
Location: Hybrid
Site: Graces Quarter, ALC, APG
Description: 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

Ft. Detrick, MD
Site: United States Army Medical Research Institute of Infectious Diseases
Description: Students will have the opportunity to work alongside subject matter experts who specialize in virology, bacteriology, and diagnostic studies to learn about how USAMRIID deter and defend against current and emerging biological threat agents. Work in the laboratory includes exposure to fundamental principles that are necessary to safely operate in a BSL-2 laboratory. Students have the opportunity to learn from not only a scientist’s point of view but also a managerial perspective of the day-to-day operations that are necessary to conduct research at U S Army facility.

Edgewood, MD
Site: U.S. Army Combat Capabilities Development Command – Chemical Biological Center – Aberdeen Proving Ground
Description: The U.S. Army Combat Capabilities Development Command Chemical Biological Center (Chemical Biological Center) is the primary Department of Defense technical organization for non-medical chemical and biological defense. DEVCOM Chemical Biological Center (CBC) has a unique role in technology development that cannot be duplicated by private industry or research universities. It fosters research, development, testing, and application of technologies for protecting warfighters, first responders, and the nation from chemical and biological warfare agents. DEVCOM Chemical Biological Center is currently developing better ways to remotely detect these chemical and biological materials – before the warfighter or first responder ever enters the threat zone. DEVCOM Chemical Biological Center is also developing a new generation of technologies to counter everything from homemade explosives to biological aerosols to traditional and non-traditional chemical hazards.

Boston, MA
Site: ARL – Northeast
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities.This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Picatinny, NJ
Site: Combat Capabilities Development Command Armament Center
Description: AEOP Interns will get world-class leadership in engineering, science excellence, quality, and innovation, and we are relied upon to objectively evaluate armament solutions so that we know our true progress and how it relates to our adversaries. This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available.

White Sands, NM
Site: White Sands Missile Range
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities. This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Site: DEVCOM – Analysis Center
Description: The U.S. Army Combat Capabilities Development Command (DEVCOM) Analysis Center (DAC) informs Army modernization and readiness decisions by conducting thorough analyses enabled by tool development and data curation. The objective of the DEVCOM Analysis Center (DAC) Summer Internship Program is to provide the next generation of cyber leaders an opportunity to learn about the research process as it applies to the cyber domain as well as to allow high school students to provide meaningful contributions to real-world research efforts in cyberspace. The internship program is multi-week (12-14 weeks) starting late May 2025 and it ends in August 2025. Interns will do applied research and document some of the latest cybersecurity vulnerabilities including wireless and password cyber-attacks, both new and most common methods used for exploitation and mitigation.  The Intern will ensure this applied research and documentation contains material from peer-reviewed and open-source publications, public knowledge databases, and community discussion groups related to these types of cyber-attacks.  Additionally, the high school Intern will utilize the research and documentation to develop a training program on a topic that will be selected in coordination with the Lab Coordinator.  Finally, the Intern will provide a report describing the procedures to execute and mitigate these attacks in a cohesive way.This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available.

West Point, NY
Site: United States Military Academy
Description: At West Point, research is organized and executed through centers and institutes. These centers and institutes and the Academic Research Division provide the infrastructure necessary to tackle the Army and nation’s most challenging problems. Ongoing research is focused on solving current and future Army challenges using a diverse, interdisciplinary team of experts.

Research Triangle Park, NC
Site: Research Triangle Park
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities.This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Austin, TX
Site: ARL South
Description: The U.S. Army Combat Capabilities Development Command Army Research Laboratory, known as DEVCOM ARL, is the Army’s research laboratory. Nested strategically within DEVCOM and the Army Futures Command, ARL’s mission is to Operationalize Science. A hallmark of ARL’s mission is collaborative partnerships to broaden Army access to expert talent and accelerate transitions of science-enabled capabilities.This site operates on a rolling application basis. Due to the high volume of applications, not all candidates may receive an immediate response. However, all applications will remain under consideration for future opportunities as they become available. Applicants must be 16 to apply.

Vicksburg, MS
Site: U.S. Army Engineer Research and Development Center
Description: Under the guidance of mentors, you will conduct research alongside staff and primary researchers. Through your participation in the AEOP program at ERDC laboratories, you will be introduced to a real-world laboratory environment as well as modern research technologies and techniques. This experience will inspire you to continue to pursue STEM disciplines as a career pursuit. Research Areas Includes:

• Military installation and contingency bases sustainability
• Enhancing socio-cultural understanding in theater operations
• Improving civil work facilities and infrastructure
• Resilient Facilities and Infrastructure
• Smart Sustainable Materials
• Installation Decision Support
• Urban and Stability Operations

Site: U.S. Army Engineer Research and Development Center
Description: GSL is seeking students interested in pursuing a degree in a STEM field. Students will be exposed to our mission to create innovative solutions to support the nation’s security, defense, public safety, and infrastructure. Our work centers on a unique combination of laboratory experimentation, materials characterization, full-scale field testing, and high-performance computational analysis. We use these techniques to develop innovative solutions in the following areas:

• Force projection and maneuver support
• Force protection and weapons effects
• Civil works and infrastructure
• Operational support and technology transfer

Our research areas include:

• Airfields and pavements
• Concrete and materials
• Geotechnical engineering and geosciences
• Impact and explosion effects
• Mobility systems
• Structural engineering
• Structural mechanics
• Survivability engineering

Silver Springs, MS
Site: WRAIR – Walter Reed Army Institute of Research
Description: WRAIR has two main centers – Center for Infectious Disease Research and Center for Military Psychiatry and Neuroscience. WRAR’s mission: To discover, design, develop, and deliver globally impactful solutions for military-relevant infectious diseases, brain health, and performance optimization through innovative research. Visit Army Home (health.mil) for more information on the research done at WRAIR.

WRAIR provides undergraduate students seeking summer internship opportunities to participate in research at WRAIR while being mentored by experienced Army researchers. A wide range of opportunities are available, especially in the areas of infectious disease and brain health research. The 8-12 week internship concludes with submitting an abstract and a public poster presentation.

WRAIR also provides opportunities for academically advanced high school students to participate in hands-on research experiences in research laboratories under the direction of scientists-mentors during the summer. HSAP students gain scientific experience and present their research at the STEM Expo at the end of the summer program.

Atlanta, GA
Site: Georgia Tech
Description: Students will manufacture and characterize origami structures. Students will also use origami simulation software (origamisimulator.org allows students to take data very quickly, while MERLIN and software developed within the group permit more specialized simulations). Students will also be exposed to the analytic theories and given chances to contribute to them.

Site: Georgia Tech
Description:

Project 1 – Shock Wave Interactions – Goal: Compute distance (x) versus time (t) plots for plate-on-plate impact experiments on Fe-Mn targets. Understanding shock wave interactions giving rise to reflections and release waves, and resulting in build-up of internal tensile stresses is essential before designing target geometries for planar-parallel plate-impact experiments. In this project, the intern will develop distance (x) versus time (t) plots, (often called x-t diagrams) illustrating how impact-generated shock waves propagate in materials and interact with interfaces between impedance mismatched regions, producing reflected waves and spall failure. The x-t diagrams will be developed considering Fe-11Mn, Fe-7Mn, Fe-4Mn and pure-Fe targets impacted by pure-Fe flyer, using available measured/predicted properties. Information provided by x-t diagrams in monolithic and layered Fe-Mn alloys will be valuable for correlating the effects of microstructural and geometric complexities investigated in our current project, while providing experience for the student intern and USMC-WP cadet, learning about shock wave interactions.

Project 2 – Multi-probe PDV Velocity Profile Analysis – Goal: Data collection and analysis of PDV probe signals from gas gun experiment to obtain velocity profiles. Large data sets collected with PDV interferometry during gas gun impact experiments to obtain velocity profiles require robust data analysis while ensuring uncertainty quantification. In this project, the AEOP intetravelingadet (travelling to GT for week of experiment) will perform a plate-on-plate impact experiment (set-up prepared ahead of time) using PDV probes backing multiple Fe-Mn alloy samples. The data collected data will be analyzed using SIRHEN (developed at Sandia) and HiFiPDV (developed at GT) software packages to determine best fits and uncertainty for the velocity profiles. The goal will be to ensure resolution across the wave profile capturing the rise and release of shock wave, peak (steady) state, velocity spall pull-back and strength, and decompression/recompression slopes, and evaluate uncertainty with multiple PDV probes. The project will provide valuable experimental and data analytics skills to the interns.

Project 3 – Spall Damage Post-mortem Evaluation – Goal: Microstructural quantification of spall-induced damage in soft-recovered additively manufactured 9628 Steel. This project will involve gas gun plate impact experiment performed on AF9628 steel additively fabricated in Prof. Bennett’s lab at USMA-WP. The intern will perform the experiment along with USMC-WP cadet (visiting GT for the week of experiment). CT scans will be obtained on samples (before and following impact) using a Zeiss Metrotom 800 X-Ray Microscope and image analysis software will be used to calculate the volume fraction of spall damage, which will be correlated with initial grain size and pre-existing heterogeneities. Optical and scanning electron microscopy will also be performed to identify the microstructural features associated with void nucleation sites. The overall goal will be to build the protocol for characterization/quantification of microstructural features for correlations with shock conditions to validate damage models. In the process, the intern and cadet gain valuable skillsets associated with experiments and data processing.

Project 4 – Spall Strength Correlations from Material Properties and Microstructure – Goal: Compiling database for predictions of spall strengths using commonly available mechanical properties and microstructure. Measurements of spall strength require impact experiments that are destructive, time consuming, and quite involved. Theoretical models for calculating spall strengths are limited and do not account for microstructure effects. Data available on spall strengths measured using gas-gun impact experiments for 16 iron-based alloys including pure (wrought) iron, plain carbon and HSLA steels, and stainless and several advanced steels reveals that complex ferrous alloys generally have higher spall strength values than pure iron and plain carbon steels. However, it is uncertain if the differences are due to effects of microstructure on the different mechanisms of plastic deformation (preceding spall) or those influencing spall initiation and failure processes. In this project, the AEOP intern will build on this database of properties to include high performance TRIP/TWIP steels, and single and dual-phase alloys with complex compositions and develop correlations of spall strength with various elastic, plastic, and fracture properties, and as a function of microstructural parameters. Continuation of the project following the internship will offer opportunities to utilize machine learning tools to predict spall strengths correlated with the microstructure and process variables.

Kennesaw, GA
Site: Kennesaw State University
Description: Interns will conduct research in the mathematical sciences related to fractals. They will develop new numerical methods to solve certain differential equations on fractals and see the connection between the differential equations and the scattering of electromagnetic waves by fractal structures. They will get to visualize the simulations they produce in the state-of-the-art Immersive Visualization Environment research supercluster lab, consisting of a dome shape display with a 5-meter diameter and 210-degree horizontal field of view. Students will also be exposed to other relevant scientific skills for competitive entry into STEM programs and careers, such as developing an effective research poster and delivering an engaging scientific presentation.

Site: Kennesaw State University
Description: For the undergraduate engineering student, this project provides a unique opportunity to develop hands-on expertise in cutting-edge technologies, such as EEG, ECG, and eye-tracking systems, alongside real-time data processing frameworks like Apache Kafka. The experience gained from integrating complex hardware systems, conducting rigorous calibrations, and ensuring precise data synchronization will significantly enhance their technical skill set, preparing them for careers in fields such as biomedical engineering, data science, and human-computer interaction. Furthermore, the practical knowledge of how to design and manage sophisticated experiments will strengthen their ability to undertake independent research, potentially leading to opportunities for advanced study or innovation in their future professional endeavors.

Ames, IA
Site: Iowa State University
Description:

Study 1: Design, synthesis, and grafting of 2D frameworks for detection and retention of CWAs and industrial toxins.
Study 2: Achieve the electrojet printing of activated and doped MOFs and functional materials on soft, nonconductive, and porous textile substrates.
Study 3: Identify the efficiency of filtration and decontamination for MOF-grafted fibers and textiles for CWAs and industrial toxins (in collaboration with Dr. Gregory Peterson at the Army Research Laboratory)

Specifically, the students will:

• Learn the principles of electrojet printing and its application in advanced materials research.
• Participate in the preparation and optimization of MOF-based inks suitable for e-jet printing.
• Investigate the interactions between MOF-based inks and textile substrates, focusing on ink adhesion, resolution, and electrical properties.
• Contribute to the development of scalable methods for printing functional materials on textiles.