Computational Material Science Intern - Spring 2027 - Santa Clara, CA

• Perform electronic structure calculations to investigate the fundamental mechanisms behind experimentally observed material behaviors.
• Train and fine-tune machine learning interatomic potentials to support large-scale molecular dynamics simulations of complex material systems.
• Build and maintain materials databases using open-source datasets and internally generated high-throughput computational results.
• Conduct descriptive analytics to identify trends, relationships, and opportunities within large materials datasets.
• Analyze, summarize, and communicate research findings through technical presentations, reports, publications, and stakeholder discussions.
• Collaborate with data scientists, materials researchers, and experimental teams to accelerate materials discovery efforts.

• Experience with state-of-the-art generative AI models for battery material discovery and screening.
• Strong foundation in electrochemistry, organic chemistry, and surface kinetics.
• Experience with molecular dynamics simulations and materials informatics workflows.
• Familiarity with MATLAB and additional scientific computing environments.
• Passion for empirical research and solving complex scientific challenges using data-driven approaches.

• Must be currently pursuing a PhD in Materials Science, Chemistry, Physics, Chemical Engineering, or a closely related field.
• Demonstrated research excellence through publications, conference presentations, patents, or other significant research contributions.
• Advanced understanding of inorganic and/or organic chemistry, reaction kinetics, and surface reactions.
• Experience performing electronic structure calculations using tools such as VASP, Gaussian, or similar computational chemistry platforms.
• Experience automating high-throughput calculations on high-performance computing (HPC) systems.
• Experience with machine learning and statistical modeling techniques.
• Advanced Python programming skills with experience using machine learning frameworks such as TensorFlow and scientific computing libraries including NumPy, SciPy, and pandas.
• Strong analytical, problem-solving, and quantitative research skills.
• Excellent written and verbal communication skills.
• Ability to work collaboratively in a multidisciplinary research environment.

People are our most valuable assets, and Nissan seeks to maximize the power of each individual member of our team. When everyone belongs, the power of NISSAN is undeniable. Nissan aims to improve business results through a workplace and business that meets the needs of our employees and customer base.

Nissan is committed to creating a culture where everyone belongs and employees, customers, and partners feel respected, valued, and heard. We have Business Synergy Teams (BSTs) across the Americas that are open to all employees and seek to connect employees through common interests and foster a company culture where all employees feel supported and included.

Nissan also values inclusion in our business as we respect and recognize the diversity of our customer base and the communities where we do business. We are committed to procuring innovative goods and services, retailing our products, and communicating from a position that will help us continue to offer our customers competitively designed, market-driven products.

Join us as we carry our commitment to our employees and customers into the future.