Fall 2026 PhD Battery & Sustainability Intern - Physics-Based Battery Modeling

General Motors; United States; Hybrid; USD 25,000 - 38,000; Full time

Job summary

General Motors is seeking a Fall Intern to advance first-principles, physics-based battery models that capture the underlying mechanisms governing electrochemical performance and degradation. Your work will span multiphysics modeling across scales to improve cell design for GM EVs.

You will develop and validate methods for various chemistries and formats, build coupled electrochemical-thermal-mechanical models, and translate results into design guidance while collaborating with world-class

Qualifications

• 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.
• Experience developing physics-based finite-element battery modeling and electrode microstructure simulation for battery applications.
• Strong foundation in electrochemistry, solid mechanics, thermodynamics, and transport phenomena.
• Experience developing coupled Multiphysics models (electrochemical, thermal, mechanical) across scales.
• Strong C++ and Python proficiency (both required) for scientific computing, modeling, and data analysis.

Responsibilities

• Develop and validate physics-based methods to battery models across a range of chemistries, cell designs, and formats.
• Develop and implement finite-element method to complex battery electrode microstructures and process x-ray tomographic understanding of electrode materials.
• Build coupled electrochemical and mechanical models to capture electrochemical and mechanical responses, mass transport, and heat generation in battery electrodes.
• Investigate degradation mechanisms through Multiphysics mechanistic modeling.
• Apply modeling to understand and predict performance, lifetime, and safety behavior under real-world operating conditions.
• Translate model outputs into actionable guidance for cell design, materials selection, and system-level decisions.
• Integrate models into multi-scale and system-level simulation frameworks and develop simulation toolkits.
• Lead and contribute to deep technical problem solving, grounded in physical intuition and rigorous analysis.
• Influence technical direction through scientifically grounded arguments and modeling insight.
• Publish and present your work through peer-reviewed journals, conferences, and internal reviews.
• Contribute to intellectual property and patents in battery modeling and design.

Skills

C++ proficiency

Python proficiency

Analytical skills

Communication skills

Research dissemination

Education

PhD in Physics/Engineering or closely related field

Tools

Finite-element modeling

Multiphysics frameworks

Job description

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Research Administration Building at our Global Technical Center in Warren, MI three times per week, at minimum.

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard - from breakthrough hardware and battery systems to intuitive design, intelligent software, and next‑generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

Why GM Battery Research & Development?

At GM, your work won’t sit on a shelf – you’ll see it power real vehicles on the road. You’ll move ideas from first principles, validated models, vehicle impact, working at the intersection of fundamental physics, advanced simulation, and real-world EV systems.

• Work alongside leading experts in electrochemistry, materials science, and Multiphysics modeling
• Solve fundamental battery science problems across transport phenomena, kinetics, and degradation
• Leverage advanced experimental data, high-fidelity instrumentation, and high-performance computing
• Develop and apply state-of-the-art physics-based models grounded in first principles
• Be supported to publish and present original research in leading journals and conferences
• Collaborate with tier 1 research universities, national labs, suppliers, and federally funded research programs
• Seeing your models directly influences battery design, safety, and performance in GM EVs
• Grow within a deep technical environment across expert and research leadership tracks

The Role

As a Fall Intern, you will develop and advance first-principles, physics-based battery models that capture the underlying mechanisms governing battery behavior. Your work will focus on understanding and predicting electrochemical performance, degradation, and improved cell design through rigorous Multiphysics modeling across scales.

• Develop and validate physics-based methods to battery models across a range of chemistries, cell designs, and formats
• Develop and implement finite-element method to complex battery electrode microstructures and process x-ray tomographic understanding of electrode materials
• Build coupled electrochemical and mechanical models to capture electrochemical and mechanical responses, mass transport, and heat generation in battery electrodes
• Investigate degradation mechanisms (e.g., volume expansion, particle fracture) through Multiphysics mechanistic modeling
• Apply modeling to understand and predict performance, lifetime, and safety behavior under real-world operating conditions
• Translate model outputs into actionable guidance for cell design, materials selection, and system-level decisions
• Integrate models into multi-scale and system-level simulation frameworks and develop simulation toolkits
• Lead and contribute to deep technical problem solving, grounded in physical intuition and rigorous analysis
• Influence technical direction through scientifically grounded arguments and modeling insight
• Publish and present your work through peer-reviewed journals, conferences, and internal reviews
• Contribute to intellectual property and patents in battery modeling and design

Your Skills & Abilities (Required Qualifications)

• 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
• Experience developing physics-based finite-element battery modeling and electrode microstructure simulation for battery applications
• Strong foundation in electrochemistry, solid mechanics, thermodynamics, and transport phenomena
• Experience developing coupled Multiphysics models (electrochemical, thermal, mechanical) across scales
• Strong C++ and Python proficiency (both required) for scientific computing, modeling, and data analysis
• Strong analytical and quantitative problem-solving skills grounded in physical principles
• Demonstrated research track record including peer-reviewed publications and technical presentations
• Ability to clearly communicate complex technical findings to both specialized and cross-functional audiences
• Proven ability to influence technical direction through expertise and analysis
• Commitment to advancing the state of the art in battery science and modeling

What will give you a competitive edge (Preferred Qualifications)

• Experience battery electrode microstructure modeling using finite-element methods
• Experience with development of open-source tools for Multiphysics battery simulations
• Familiarity with continuum-scale modeling frameworks (e.g., P2D/DFN models or similar, solid mechanics)
• Experience integrating physics-based models into larger simulation environments or design workflows
• Background leveraging high-performance computing for large-scale simulations
• Contributions to externally recognized research collaborations
• Good understanding of battery material/electrochemical properties
• Knowledge of battery electrode tomography measurement techniques such as FIB-SEM and x-ray CT scan and process related microstructure data
• Experience in AI and Data-driven predictive modeling for battery research

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