Computational Material Science Intern - Spring 2027 - Santa Clara, CA
Core
PhD-level intern performing electronic structure calculations, training machine learning interatomic potentials, and building materials databases to accelerate next-generation automotive materials and battery development.
Role type
PhD-level computational materials science intern
Builds
Next-generation materials for automotive applications and battery technology
Domain
Automotive industry + computational materials science
Deliverable
production ML models
Required skills
electronic structure calculations, machine learning interatomic potentials, high-throughput HPC automation, Python programming, TensorFlow, NumPy, SciPy, pandas, statistical modeling
Preferred skills
generative AI for material discovery, molecular dynamics simulations, materials informatics workflows, MATLAB
Technologies
VASP, Gaussian, TensorFlow, NumPy, SciPy, pandas, MATLAB, HPC systems
Responsibilities
Perform electronic structure calculations to investigate material behaviors; Train and fine-tune machine learning interatomic potentials; Build and maintain materials databases; Conduct descriptive analytics on large datasets; Analyze and communicate research findings; Collaborate with data scientists and experimental teams
Seniority
PhD student, research intern