Sr Staff Engineer, Battery Modeling
About The Position
As an engineer on the RD&E modeling team, you will bridge physical chemistry, advanced characterization, and computational modeling to accelerate the development of high-performance lithium-ion battery materials and cells. You are a cross-functional problem solver who thrives at the intersection of wet-lab characterization and high-performance computing, leveraging advanced models to turn raw empirical and theoretical data into actionable material & cell design rules. Working closely with synthesis, formulation, and commercial teams, you will quantify property-performance relationships for active materials and coproducts to drive technological differentiation.
Requirements
- Ph.D. in Chemistry, Materials Science, Chemical Engineering, or a related physical science discipline.
- Deep experience integrating quantum chemistry methods (DFT, electronic structure calculations) with experimental materials characterization
- Deep experience in physics based model development and application for lithium ion batteries
- High proficiency in Linux environments, CLI tools, bash scripting, Python, and numerical solvers for physical chemistry workflows.
- Hands-on background in electrochemistry for lithium ion batteries or related field
- Solid grasp of standard (BET, TGA, Raman, SEM) and advanced spectroscopic/synchrotron techniques (XAS, XPS, EPR) applied to silicon or carbon-based active materials.
Responsibilities
- Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.
- Develop and operationalize electrochemical tests at the half and full cell level to extract material-level kinetics and physics for Li-ion active materials.
- Build and maintain automated data processing, simulation, and modeling workflows using Linux command-line tools, bash scripting, and Python for both material and cell-level modeling
- Translate computational insights into physical material design improvements while guiding internal teams and external customers on cell-level design optimization for maximum power and energy efficiency.
- Leverage empirical historical datasets to create model scenarios to inform design opportunities for energy:power differentiation.
Benefits
- competitive Total Rewards package that can include benefits, perks, equity, and bonuses
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
