Job Description
The role involves leading research and development of advanced battery electrolytes, integrating experimental chemistry with AI-driven optimization to develop next-generation energy storage solutions across various applications.
Key Responsibilities
- Lead complex electrolyte R&D programs focused on next-generation battery systems, ensuring alignment with safety, cyclability, and high-temperature performance requirements.
- Manage multi-disciplinary teams of chemists, data scientists, and engineers to achieve innovation milestones.
- Define the materials innovation roadmap related to electrolyte formulation and interfacial science.
- Oversee the engineering of the Solid Electrolyte Interphase (SEI) and additive optimization programs.
- Lead cell-level validation and integration of new electrolytes into prototype batteries.
- Generate experimentally validated battery component data to guide AI model training, ensuring data quality and reproducibility.
- Utilize molecular informatic tools to accelerate component optimization and bridge experimental data with AI-generated candidates.
Requirements
- Ph.D. in Materials Science and Engineering, Chemical Engineering, Electrochemistry, or a closely related materials chemistry field.
- Proven background as an electrochemical researcher and R D leader experienced in directing technical programs and managing multi-disciplinary research teams.
- Deep expertise in fundamental materials chemistry, interfacial science, additive optimization, and Solid-Electrolyte Interphase (SEI) engineering.
- Extensive experience in cell-level validation and advanced characterization techniques, demonstrating an ability to integrate new materials into prototype cells.
- Demonstrated experience in data-driven experimentation and structuring chemistry data for AI model consumption.
- Experience overseeing SEI Solid Electrolyte Interphase engineering and additive optimization programs, leveraging expertise in fundamental materials chemistry.
- Experience leading cell-level validation and integrating new electrolytes into prototype cells.
- Ability to produce high-quality, experimentally validated battery component data, guiding AI model training by ensuring data quality, experimental reproducibility, and comprehensive parameter space coverage.
- Experience utilizing molecular informatic tools to accelerate battery component optimization cycles, effectively bridging experimental data with AI-generated candidates.
Benefits & Perks
highly competitive salary
robust benefits package including comprehensive health coverage
attractive equity stock options program
opportunity to contribute to meaningful scientific projects with broad public impact
work in a dynamic, collaborative, and innovative environment
significant opportunities for professional growth and career development
access to state-of-the-art facilities and proprietary technologies
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