Computational Chemist - Machine Learned Force Fields, Material Discovery
… · Remote · United States ·
COMPENSATION
Salary available to subscribersListed on the employer's job board (Ashby)
- PhD in Comp Chem/ML
- Python + PyTorch/JAX
- ML Force Fields focus
- Equity + Benefits
Join the PFAS team within the company's Chemical Simulation group to develop substitutes for semiconductor process materials. You will own the machine learned force fields pipeline, from generating first principles data to training and validating potentials. The work combines generative ML, physics-based simulation, and experimental validation to replace PFAS incumbents.
What you'll do
- Design high-throughput quantum chemistry campaigns for training data
- Build automated, reproducible data generation workflows on cloud/HPC
- Train, validate, and deploy machine learned interatomic potentials
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