Hiring: Senior Research Scientist, Battery Materials Simulation Company: SandboxAQ Location: United States Job Posted Time: 2026-09-03 10:54:55 Employment Type: Hybrid Target Skills & Keywords : Epic Systems, Machine Learning, PyTorch, Python, R, TensorFlow About the job Experience: •5+ years of industry experience in computational battery materials research beyond the Ph.D. Required Skills: •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. •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 •Conduct advanced simulations using DFT, MD, enhanced sampling methods, and ML-based approaches for battery materials and electrochemical systems. •Model surface reactions, interfacial degradation mechanisms, and electrochemical processes, including cathode-electrolyte interfaces (CEI), solid-electrolyte interphases (SEI), solid-state electrolyte interfaces, and reaction pathways under operating conditions. •Develop and deploy computational workflows for high-throughput materials screening, reaction modeling, and materials optimization. •Lead high-fidelity data generation campaigns and develop ML force fields and surrogate models for battery materials and interfaces. •Employ data-driven approaches to analyze large computational and experimental datasets to uncover new insights into materials behavior. Qualifications: •Extensive experience modeling battery materials, including cathodes, anodes, liquid electrolytes, solid-state electrolytes, and electrochemical interfaces. •Extensive background modeling rare-event phenomena, charge-transfer kinetics, or degradation at the solid-electrolyte interphase (SEI). •Track record of developing or scaling generative models for materials synthesis, crystal structure generation, or unconstrained composition exploration. •Track record of publications in high-impact peer-reviewed journals and/or patents in battery materials, computational chemistry, or AI for materials science. •Demonstrated success in translating computational discoveries into real-world materials innovation. Compensation: •$134,400 - $252,000 / year •Competitive benefits and rewards package Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!