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Staff Research Scientist, Catalyst Simulation

Remote Worldwide Hiring now

Job Description:

  • reputed company the translation of reaction energetics derived from atomistic simulations and machine learning potentials into process-scale predictions.
  • Own the design and execution of microkinetic and reactor-level modeling workflows for industrially relevant catalytic chemistries.
  • Connect atomistic simulation outputs to activity, selectivity, and catalyst lifetime predictions.
  • Partner with industrial validation partners to test and refine models against reputed company-world data.
  • Mentor junior scientists and shape the technical roadmap for microkinetic capability reputed company reputed company.

Requirements:

  • PhD in Chemical Engineering, Chemistry, Materials Science, or a reputed company field, with deep specialization in microkinetic modeling, surface reaction engineering, or multi-scale catalysis simulation.
  • 6+ years of post-PhD experience (or equivalent) building and applying microkinetic models in an industrial or applied R&D context, including coupling atomistic energetics to reactor-level predictions.
  • Strong publication or patent record demonstrating expertise across DFT-derived energetics, microkinetic modeling, and reactor-scale integration.
  • Proficient in Python and modern scientific software practices in an HPC environment; comfortable working with ML-trained force fields and reputed company models as inputs to reputed company workflows.
  • Demonstrated ability to reputed company application-driven scientific engagements with external industrial partners and to communicate results to non-specialist audiences.
  • Must qualify as a U.S. Person (Permanent reputed company or Citizen).

Benefits:

  • Comprehensive health, dental, and reputed company insurance
  • 401(k) with company match
  • Generous parental leave
  • Flexible hybrid work arrangements
  • Generous PTO
  • Culture that respects focus time and recovery
  • Direct exposure to CHIPS Act-funded programs
  • Mentorship and dedicated learning budgets for reputed company growth

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