Senior Battery Cell Modeling Scientist - Simulation

SES AI Corporation is an advanced battery technology company headquartered in Boston, Massachusetts, focused on developing lithium-metal (Li-Metal) and lithium-ion (Li-ion) battery solutions for electric transportation and energy storage applications. The company operates three core business units: Drones, which supplies high-energy and high-power density NDAA-compliant cells for drones, urban air mobility, and robotics; ESS (Energy Storage Systems), which provides integrated hardware and software solutions for data centers and commercial and industrial customers; and Materials, which leverages AI-driven discovery to supply next-generation battery materials. Central to its operations is the Molecular Universe platform, an AI-for-Science SaaS platform that powers material discovery, battery management, and workflow automation across all business units.

Senior Battery Cell Modeling Scientist - Simulation

 

Responsibilities

• Responsible for building cell mathematical simulation models (physical models and data-driven models) to predict the performance of Li-ion batteries/Li-metal batteries under various working conditions, including dynamic performance, lifetime decay, electrochemical and thermal response, and safety-related cell behavior

• Design and advance experiments to obtain parameters/data required to build cell models

• Work with cross-functional teams to develop, deploy, test, and maintain models

• The electrochemical/thermal data of the cell under different working conditions are generated by using the certified physical model of the cell to provide data support for the establishment of the data-driven model

• Establish a standardized process for cell physical modeling to reduce the resources/time required for modeling

• Provide documentation related to model and algorithm development

• Work with the battery team to determine and achieve battery performance life goals

 

Qualifications

• Master’s degree or above, more than 5 years of battery related research/work experience

• Basic knowledge of cell electrochemistry (P2D), thermal, mechanical modeling and simulation. Familiar with electrochemical principle, simulation parameter measurement method and corresponding equipment

• Familiar with various battery-related models/algorithms, and have experience in using cell model software (COMSOL, Ansys, PyBaMM, etc.)

• Experience in building data-driven models (statistical analysis, machine learning, AI)

• Proficient in code development tools, such as Python or Matlab