Catalyst Simulation Postdoc

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Requirements:

• Currently enrolled or recently completed a STEM PhD Program in Chemical Engineering, Materials Science, Physics, Chemistry, Computational Science, or related fields.
• Intermediate to advanced skill in programming languages (e.g. Python).
• Proficiency in density functional theory (DFT), molecular dynamics (MD), kinetic modeling, and other computational techniques.
• Significant experience modeling chemical reaction networks for catalyst material classes with relevant high-impact publication.
• Experience developing machine learning force fields for solid-state systems is a plus.
• Experience providing in silico support to experimental groups on catalyst design or optimization is a plus.

Responsibilities:

• Lead design and implementation of new computational workflows simulating reactivity and dynamics of catalytic materials at atomic, mesoscale, and continuum scales.
• Support client engagements on the research and development of novel catalysts.
• Collaborate with cross-functional teams to create hybrid optimization pipelines combining physics-based simulations, machine learning methods, and experimental techniques.
• Prepare reports, presentations, and publications to communicate research findings to internal, academic, and industry partners.