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Senior Research Scientist in Battery Materials Simulation (AI)

134Β 400 - 252Β 000$
Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
remote (Ρ‚ΠΎΠ»ΡŒΠΊΠΎ USA)/hybrid
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
senior
Английский
b2
Π‘Ρ‚Ρ€Π°Π½Π°
UK/US/Canada
Вакансия ΠΈΠ· списка Hirify.GlobalВакансия ΠΈΠ· Hirify Global, списка ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… tech-ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ
Для мэтча ΠΈ ΠΎΡ‚ΠΊΠ»ΠΈΠΊΠ° Π½ΡƒΠΆΠ΅Π½ Plus

ΠœΡΡ‚Ρ‡ & Π‘ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄

Для мэтча с этой вакансиСй Π½ΡƒΠΆΠ΅Π½ Plus

ОписаниС вакансии

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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 – $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.

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’