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Job Description
The role involves designing and leading an AI-driven molecular simulation and materials informatics platform to advance next-generation battery materials, integrating AI models with computational chemistry and high-performance computing to support battery R&D and materials discovery.
Key Responsibilities
- Design and implement a scientific computing platform for battery materials integrating AI models, experimental data, and cloud infrastructure.
- Develop high-performance simulation services for large-scale molecular dynamics, phase-field, and related models.
- Create and evolve APIs and platform interfaces for simulation, machine learning, and data services.
- Develop and deploy AI/ML models for materials informatics, including force fields and surrogate models.
- Build and manage automated MD simulation workflows with job scheduling, monitoring, and data management.
- Translate research prototypes into reliable, production-grade simulation services.
- Collaborate with scientists to align platform features with R&D needs in battery materials.
- Develop simulation capabilities focused on dendrite growth, degradation, and electrolyte performance.
- Ensure integration of simulation and AI outputs with experimental workflows and data pipelines.
Requirements
- PhD in Materials Science, Computational Physics, Computational Chemistry, or a closely related field.
- At least 1 year of post-graduate experience in computational materials science, including molecular dynamics and/or phase-field simulation.
- Proven track record building production-grade scientific software in C and/or similar systems languages, ideally in an HPC context.
- Hands-on experience with AI and machine learning for materials informatics, such as ML force fields, surrogate models, or automated ML workflows.
- Demonstrated experience designing and implementing APIs, services, and platforms used by other engineers or scientists.
- Strong background in algorithm development related to materials behavior, e.g., dendrite growth, transport, microstructure evolution.
- Experience collaborating closely with experimentalists and domain scientists and translating their needs into robust engineering solutions.
Benefits & Perks
Highly competitive salary
Robust benefits, including comprehensive health coverage
Attractive equity stock options in a NYSE-listed company
Opportunity to contribute to a meaningful scientific mission with broad public impact
A dynamic, collaborative environment at the intersection of AI, computational science, and advanced battery technology
Significant opportunities for growth through collaboration with leading experts in AI, R&D, and engineering
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