Introduction to the team: The Batteries vertical sits at the intersection of ChemSim and AI Sim, where SandboxAQ uses physics-based simulation, proprietary datasets, and Large Quantitative Models (LQMs) to discover and optimize next-generation battery materials. Our goal is to compress slow, empirical battery R&D into an AI-driven workflow spanning prediction, simulation, and materials discovery for high-impact applications including solid-state batteries, Cobalt-free cathodes, beyond Li-ion cell chemistries, and resilient energy storage systems.
Introduction to the role: We are seeking a highly skilled Senior Research Scientist in Battery Materials Simulation to join our growing team. The ideal candidate will have deep expertise in applying advanced simulation techniques, including Density Functional Theory (DFT), Molecular Dynamics (MD), and machine learning (ML), to battery materials discovery and optimization.
This role will focus on developing computational workflows and AI-driven approaches to accelerate the design of next-generation battery materials, including cathodes, anodes, electrolytes, interfaces, and interphases. Experience modeling surface chemistry, interfacial degradation mechanisms, and electrochemical reaction pathways is highly desirable.
As a senior member of the team, the candidate will provide technical leadership, mentor junior scientists, and drive the execution of strategic research programs in collaboration with internal and external partners.
See how SandboxAQ is helping build America’s semiconductor supply chain from the materials up