Senior Research Scientist, Battery Materials Simulation

SandboxAQ·United States·26 июня

Senior Research Scientist, Battery Materials Simulation

🏢 ОфисSeniorПолная занятость

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Наша компания

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.

О роли

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

Чем предстоит заниматься

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

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

Guide project scoping, execution, and delivery while working closely with cross-functional teams

Provide technical direction for battery research roadmaps, translate high-level project goals into technical milestones, and mentor junior scientists in best practices for both ML and physics-based modeling

Collaborate with internal teams, academic collaborators, government partners, and industrial customers to deliver impactful materials innovation

Effectively communicate research findings through scientific publications, conference presentations, client-facing presentations, and technical reports

Наши требования

Ph.D. in Materials Science, Chemical Engineering, Chemistry, Physics, Computer Science, or a related field

5+ years of industry experience in computational battery materials research beyond the Ph.D

Strong theoretical foundation in thermodynamics, kinetics, electrochemistry, and materials science

Proficiency in DFT and atomistic simulation tools (e.g., VASP, Quantum ESPRESSO, CP2K)

Familiarity with state-of-the-art machine learning force fields and frameworks (e.g. MACE, TensorNet, NequIP, Allegro, or FairChem)

Experience modeling surfaces, interfaces, reaction pathways, and electrochemical systems

Experience training and evaluating ML models for materials property prediction and materials discovery

Experience with Bayesian optimization, active learning, and autonomous discovery workflows

Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)

Experience working with cloud and high-performance computing environments

Demonstrated ability to independently drive complex technical projects

Excellent communication and collaboration skills

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)

Experience developing and deploying ML force fields for battery materials and reactive systems

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

Experience leading technical programs and mentoring scientists in an industrial or national laboratory setting

Experience collaborating with experimental teams to validate computational predictions and accelerate materials development

Demonstrated success in translating computational discoveries into real-world materials innovation

WHY JOIN US?

We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth

Мы предлагаем

Competitive base salary commensurate with experience, plus equity and performance-based incentives

Comprehensive health, dental, and vision insurance

401(k) with company match

Generous parental leave

Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery

Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth

SANDBOXAQ WELCOMES ALL

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges

Read: Guidance for candidates on using AI Tools in interviews

SandboxAQ

United States

ГрейдSenior

ЗанятостьПолная занятость

РегионСША

ФорматОфис

ИсточникСкрыто

Опубликовано26 июня

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