General Motors
2027 Summer Intern - Research and Development - Computational Materials Science: Continuum Scales and Materials Discovery
Warren, Michigan, United States of America · Hybrid · Internship · Posted Oct 12, 2026
- Education
- Pursuit of an advanced degree (M.S. or Ph.D.) in Materials Science and Engineering, Mechanical Engineering, Computational Science, Applied Mathematics, Physics, Chemistry, or a closely related field.
- Visa sponsorship
- GM does not provide immigration-related sponsorship now or in the future. The role requires a U.S. Person (U.S. citizen, U.S. permanent resident, asylee, or refugee).
About the job
Conduct collaborative research using continuum-scale computational materials science to discover and evaluate materials for future vehicle and manufacturing applications.
What you'll do
- Develop and apply models, simulations, and data-driven workflows to predict materials behavior and screen candidate materials and processing conditions.
- Collaborate with experimental researchers and engineering teams to validate models and connect findings to manufacturing and vehicle performance needs.
- Document and communicate research through reports, presentations, publications, software documentation, and invention disclosures.
What they ask for
- Must be a current student pursuing an advanced degree (M.S. or Ph.D.) in a listed or closely related field.
- Strong foundation in materials thermodynamics, kinetics, mechanics, transport, numerical methods, and structure–property relationships.
- Experience developing or applying continuum-scale models and proficiency in scientific programming and data analysis.
- Able to work full-time, 40 hours per week during the summer months.
Nice to have
- Ph.D. strongly preferred.
- Experience with ICME, materials discovery, computational thermodynamics, scientific machine learning, or experimental validation.
Tools
Python, C/C++, Fortran, MATLAB, Julia, finite-element analysis, phase-field modeling, crystal plasticity
AI focus
Use data-driven methods, scientific machine learning, optimization, and high-throughput computation to screen materials and support materials discovery.
Model-written summary · the original posting is authoritative