General Motors
Fall 2026 PhD Battery & Sustainability Intern - Physics-Based Battery Modeling
Warren, Michigan, United States of America · Hybrid · Internship · Posted Aug 17, 2026
- Experience
- No minimum number of years stated.
- Education
- Ph.D. student (expected graduation by 2028) in Physics, Mathematics, Chemical Engineering, Mechanical Engineering, Computational Materials Science, or a closely related field with a focus on electrochemistry or battery modeling.
About the job
Develop and validate first-principles, physics-based battery models to predict electrochemical performance, degradation, lifetime, and safety and inform cell design.
What you'll do
- Build and validate finite-element, microstructure, and coupled electrochemical-mechanical models; analyze electrode tomography data.
- Apply multiscale modeling to battery performance, degradation, and safety, and translate results into design and system-level guidance.
- Integrate models into simulation frameworks and publish or present research findings.
What they ask for
- Ph.D. student graduating by 2028 in a relevant field, focused on electrochemistry or battery modeling.
- Experience developing physics-based finite-element battery models and electrode microstructure simulations.
- Strong foundation in electrochemistry, solid mechanics, thermodynamics, and transport phenomena; experience developing coupled electrochemical, thermal, and mechanical models across scales.
- Strong proficiency in both C++ and Python; demonstrated research record including peer-reviewed publications and technical presentations.
Nice to have
- Experience with open-source tools, continuum-scale models, simulation integration, or high-performance computing.
- Experience in AI and data-driven predictive modeling for battery research; knowledge of electrode tomography techniques such as FIB-SEM and x-ray CT.
Tools
C++, Python, finite-element methods, P2D/DFN models, FIB-SEM, x-ray CT
AI focus
Preferred experience in AI and data-driven predictive modeling for battery research.
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