Senior Staff Computational Materials Engineer - MLIPs
Tasks
- Build atomistic reaction pathway models
- Build scalable data generation workflows
- Design train validate deploy MLIP models
- Develop digital twin simulation capabilities
- Drive evaluation and adoption of emerging simulation technologies
- Generate DFT training datasets
- Integrate MLIP into simulation platforms
- Mentor engineers and influence roadmaps
- Perform first principles calculations
- Present findings to stakeholders
- Provide technical leadership
- Quantify model uncertainty
- Run active learning for ML force fields
- Validate ML force-fields
Perks/Benefits
- N/A
Skills/Tech-stack
Atomistic modeling | DFT | Density Functional Theory | Frontier Molecular Orbitals | Gaussian | HPC | High Performance | High-Performance Computing | Interatomic potentials | MACE | Machine Learning | Machine Learning Interatomic Potentials | Molecular Dynamics | Performance Computing | Python | Quantum Chemistry | Quantum Espresso | Reaction Pathway | Reactive Molecular Dynamics | ReaxFF | SevenNet | Uncertainty Quantification
Education
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