Senior Research Scientist in Battery Materials Simulation (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
TL;DR
Senior Research Scientist (AI/Battery Materials): Developing computational workflows and AI-driven approaches to accelerate the design of next-generation battery materials with an accent on DFT, Molecular Dynamics, and ML force fields. Focus on modeling surface chemistry, interfacial degradation mechanisms, and high-throughput materials screening.
Location: Remote (Must be based in the US, UK, or Canada)
Salary: $134,400 β $252,000 (depending on geographic tier)
Company
SandboxAQ is a high-growth company delivering AI solutions, including Large Quantitative Models (LQMs), to address challenges in life sciences, cybersecurity, and materials science.
What you will do
- Conduct advanced simulations using DFT, MD, and ML-based approaches for battery materials and electrochemical systems.
- Model surface reactions, interfacial degradation (CEI, SEI), and electrochemical reaction pathways under operating conditions.
- Develop and deploy computational workflows for high-throughput materials screening and optimization.
- Lead high-fidelity data generation campaigns and develop ML force fields and surrogate models.
- Provide technical direction for battery research roadmaps and mentor junior scientists in ML and physics-based modeling.
- Collaborate with cross-functional teams, academic partners, and industrial customers to deliver materials innovation.
Requirements
- 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.
- Proficiency in DFT and atomistic simulation tools (e.g., VASP, Quantum ESPRESSO, CP2K).
- Strong programming skills in Python and experience with modern ML frameworks (PyTorch, TensorFlow, or JAX).
- Experience with Bayesian optimization, active learning, and cloud/HPC environments.
- Must be based in the United States, United Kingdom, or Canada.
Nice to have
- Extensive background modeling rare-event phenomena or charge-transfer kinetics at the SEI.
- Track record of developing generative models for crystal structure generation or composition exploration.
- Publications in high-impact peer-reviewed journals or patents in battery materials and AI for materials science.
- Experience leading technical programs and mentoring scientists in an industrial or national laboratory setting.
Culture & Benefits
- Competitive base salary, equity, and performance-based incentives.
- Comprehensive health, dental, and vision insurance.
- 401(k) with company match and generous parental leave.
- Flexible hybrid work arrangements, generous PTO, and a culture respecting focus time.
- Direct exposure to CHIPS Act-funded programs and dedicated learning budgets for professional growth.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β