Job Description
The starting base pay for this role is between $25/hr and $39/hr at the time of posting.
Key Responsibilities
- 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.
Requirements
- 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.
- 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.
Ready to Apply?
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