Summer Internship in AI-Driven Materials & Electrical Modeling Engineering I1060H-1
About The Position
In this role, you will contribute to the development of next-generation materials for microcapsule coating systems by integrating AI-driven research approaches with physical modeling and experimental validation. You will work on building an automated research loop that connects materials design, simulation, and electrical testing to accelerate innovation. This is a highly interdisciplinary role combining materials science, electrical characterization, and computational modeling. You will gain hands-on experience in both laboratory testing and simulation environments, while collaborating with cross-functional teams.
Requirements
- Currently pursuing a BS degree in Applied Physics, Electrical Engineering, Computer Science, Applied AI, or a related field
- Strong programming skills in at least one language (Python, MATLAB, or C++)
- Familiarity with data analysis and modeling techniques
- Basic understanding of electrical properties of materials (e.g., conductivity, dielectric behavior)
- Strong analytical thinking and problem-solving skills
- Good communication and organizational abilities
- Willingness to work in a hands-on lab environment and follow safe laboratory practices
Nice To Haves
- Exposure to simulation tools for physics-based modeling
- Interest in combining AI/ML with physical systems or materials research
- Experience with experimental data acquisition or electrical testing setups
- Curiosity to explore interdisciplinary problems and build practical solutions
Responsibilities
- Prepare and test material samples for electrical property characterization
- Perform electrical measurements and analyze material performance under different conditions
- Develop physics-based models and simulators to predict electrical properties across varying geometries and structures
- Support the development of AI-assisted research workflows for materials optimization
- Assist in correlating experimental results with simulation data to guide material design decisions
- Document experimental procedures, data, and results in a clear and organized manner
- Communicate data analysis findings effectively and present summaries and conclusions to team members
Benefits
- Medical coverage
- 8 hours of ITO (Intern time off) per payroll
- Unlimited sick time
- 401(k)
- Hybrid/Flexible work schedule – depending on position
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What This Job Offers
Career Level
Intern
Number of Employees
251-500 employees
