Computational Materials Scientist
Tasks
- Collaborate with multi disciplinary experimentalists modelers and infrastructure teams
- Collaborate with vendor software providers
- Design chemistry and materials for screening and optimization
- Develop molecule and chemistry featurization and machine learning workflows
- Evaluate machine learning interatomic potentials for property prediction
- Fine tune machine learning interatomic potentials
- Hypothesize and test mechanisms to identify root cause
- Present technical findings concisely
- Provide inputs and guidance for process feature and reactor models
- Recommend atomic scale structure and processing changes
- Scope materials discovery tools and prioritize methods
- Validate and correlate model results with real world data
Perks/Benefits
- N/A
Skills/Tech-stack
Ab Initio | C# | ChemProp | Density Functional Theory | Fortran | Graph Neural Networks | Interatomic potentials | Language Models | Large Language Models | Linux | Machine Learning | Machine Learning Interatomic Potentials | Molecular Dynamics | MongoDB | Monte Carlo | Neural Networks | PyTorch | Python | RDKit | SMILES | SQL | Scikit-learn
Education
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