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Staff Materials Research Scientist – PFAS Alternative Discovery

sandboxaq

Hybrid Senior 🇬🇧 English
Python generative molecular design ML property prediction DFT molecular dynamics

Job description

About the role

The PFAS team within SandboxAQ’s Chemical Simulation group develops PFAS‑lean or PFAS‑free substitutes for semiconductor process materials. We combine generative machine‑learning, physics‑based simulations and experimental validation to move candidate molecules from prediction to qualified use. The Staff Materials Research Scientist will bridge our AI‑driven discovery workflow with external co‑development partners.

Key responsibilities

  • Own the partner‑facing validation loop, translating partner problems into target specifications, constraints and qualification criteria.
  • Run the generative chemistry discovery workflow, assess predicted compounds for plausibility and fit, and rank them into decision‑ready shortlists for experimental validation.
  • Apply semiconductor domain judgment to ensure workflow outputs are directionally correct and meet performance, EHS and process constraints.
  • Close the experimental feedback loop by converting partner results into actionable technical improvements for internal teams.

Required profile

  • PhD in Chemistry, Chemical Engineering, Materials Science or related field with deep specialization in semiconductor process materials or fluorochemistry.
  • 6+ years post‑PhD experience in industrial R&D developing, formulating or qualifying semiconductor process chemicals, including PFAS‑lean alternatives.
  • Hands‑on experience with semiconductor unit processes (lithography, etch, CMP, cleaning, thermal management) and related EHS specifications.
  • Proven ability to lead engagements with external industrial partners and translate experimental results into computational requirements.

Required skills

  • Proficiency in Python for running and configuring computational discovery workflows.
  • Experience with generative molecular design, high‑throughput virtual screening and ML‑based property prediction.
  • Familiarity with physics‑based simulations such as DFT and molecular dynamics.

What we offer

  • Competitive base salary commensurate with experience, plus 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 that respects focus time.
  • Direct exposure to CHIPS Act‑funded programs, senior scientific leadership, mentorship and dedicated learning budgets.

Questions fréquentes

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Source : ats:ashby

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Published 1 week ago

Expires 1 month from now

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