Catalyst Simulation Postdoctoral Researcher
closed
SandboxAQ
💵 $115k-$135k
📍Remote - United States
Summary
Join SandboxAQ, a high-growth company delivering AI solutions, as a Catalyst Simulation Postdoc. Lead the implementation of computational workflows to model catalytic materials' reactivity and dynamics. Collaborate with a team of experts using state-of-the-art atomistic modeling techniques. Support client engagements and develop hybrid optimization pipelines. Prepare reports and publications to communicate research findings. This 1-3 year, remote position offers a competitive salary, bonuses, equity, and benefits.
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, with the ability to integrate these with machine learning approaches
- Significant domain experience modeling chemical reaction networks for at least one of the following catalyst material classes, as indicated by at least one relevant high-impact publication: porous materials, homogeneous transition metal complexes, heterogeneous transition metal or metal oxide surfaces
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 that combine physics-based catalyst simulation approaches, modern machine learning methods, experimental reactor measurements, and experimental catalyst characterization techniques
- Prepare reports, presentations, and publications to communicate research findings to internal, academic, and industry partners
Preferred Qualifications
- Experience developing machine learning force fields for solid-state systems is a plus
- Experience providing in silico support to experimental groups working on catalyst design and/or optimization is a plus
Benefits
- The US base salary range for this full-time position is expected to be $115k - $135k per year
- This role may be eligible for annual discretionary bonuses and equity
- Medical/dental/vision
- Family planning/fertility
- PTO (summer and winter breaks)
- Financial wellness resources
- 401(k) plans
- Competitive salaries
- Stock options depending on employment type
- Generous learning opportunities
This job is filled or no longer available