Battery Simulation & Computational Scientist Internship

Who You Are

Are you a thoughtful, creative, and code-savvy simulation scientist or engineer? We are looking for someone who sits at the intersection of computer science and electrochemistry. You might be a software engineer with a passion for physics, or a theorist with a talent for building robust software infrastructure.

Sila Nanotechnologies is seeking a Battery Simulation & Computational Scientist (Intern) to:

• Architect and implement physics-based battery models using PyBaMM.
• Bridge the gap between theoretical equations and production-grade software code.
• Leverage key insights from our battery models to accelerate learning cycles and reduce the cost of empirical R&D.

Responsibilities and Duties

• Commit to a 6+ month internship (Remote or Onsite); this is not a position for students only available for summer months.
• Analyze electrochemical data to build, parameterize, and apply new numerical models.
• Fit electrochemical models to experimental data and evaluate model performance across a range of different electrochemical test techniques.
• Support infrastructure development, helping to build the backend pipelines and tools that bring physics-based models to a wider audience.
• Work closely with scientists and cross-functional teams to discover and communicate knowledge for the long-term development of our next-generation battery materials.
• Invest in our values and champion them as we grow.

Knowledge and Skill Requirements

• BSc (or preferably MSc/currently enrolled in a Ph.D. program) or equivalent research experience in Computer Science, Applied Mathematics, Chemical Engineering, Materials Science, or a related field.
• Strong experience using PyBaMM (Python Battery Mathematical Modeling) is required.
• Mastery of Python, including standard scientific libraries (NumPy, SciPy, Pandas).
• Experience interacting with databases using SQL or Snowflake.
• Proficient with Git and collaboration platforms (GitHub or GitLab).
• Ability to navigate and execute workflows in Linux or macOS terminal environments.
• Knowledge of electrochemical theory and the application of the P2D (Pseudo-Two-Dimensional) or Doyle-Fuller-Newman models.
• Public contributions to the PyBaMM repository or related sister projects on GitHub.
• Proficiency in using AI coding tools (e.g., Claude Code, Copilot) and knowledge of effective prompting techniques to accelerate development.
• Experience building CI/CD pipelines, containerization (Docker), or some exposure to full-stack development.

Physical Demands and Working Conditions

• Move long distances (such as from building to building) and be stationary for extended periods of time
• Operate a computer and other office equipment, such as a laptop, copier/printer, etc in a fixed location
• This role is open to Remote candidates.