Senior Materials Scientist - AI/ML for Materials Design
Mentor, OH, United States
USD 91K-142K (estimate) Senior-level Full Time
Tasks
- Apply physics informed machine learning and hybrid modeling
- Build scalable data ingestion feature engineering and model validation pipelines
- Collaborate across teams to translate model insights into product and process development
- Communicate technical findings via reports and presentations
- Deploy machine learning and deep learning models for materials design
- Design and curate model ready materials datasets
- Develop AI guided experimental design and closed loop optimization
- Develop multi fidelity modeling strategies
- Develop predictive AI enabled materials discovery frameworks
- Guide high value experiments using predictive models
- Implement active learning and data efficient modeling
- Integrate molecular mesoscale and continuum modeling with AI surrogate models
- Use inverse design to identify targeted materials formulations and structures
Perks/Benefits
- 401k eligibility
- Employee assistance program
- Health and wellness benefits
- Paid Holidays
- Paid parental leave
- Paid vacation
- Tuition reimbursement
Skills/Tech-stack
Active Learning | Bayesian optimization | Coarse Grained Modeling | Computer Vision | Data Pipelines | Deep learning | Dissipative particle dynamics | Element analysis | Feature Engineering | Finite Element Analysis | Finite element | JAX | Kinetics | Language Models | Large Language Models | Machine Learning | Materials informatics | Model Validation | Molecular Dynamics | Particle dynamics | Physics-informed machine learning | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Rheology | Scientific Computing | TensorFlow | Thermodynamics
Education
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