AI Scientist - Generative Modeling for Materials Science
Skills
- Proficiency in Python and machine learning engineering workflows
- Experience with deep learning frameworks (PyTorch, TensorFlow)
- Strong understanding of modern generative modeling: diffusion, flow, flow-matching
- Familiarity with geometric deep learning and graph neural networks
- Basic materials science, physics, and chemistry knowledge to inform model design
- Experience with model validation and deployment in research or production settings
- Ability to collaborate with experimental scientists and interpret lab results
- Strong written and verbal communication and presentation skills
Responsibilities
- Design and implement generative models (diffusion, flow-based, flow-matching) for materials design problems
- Develop physics-informed data representations and inductive biases tailored to materials and chemistry
- Create datasets, evaluation frameworks, and validate models against experimentally realized materials
- Collaborate with software engineers to productionize models and integrate into internal pipelines
- Partner with R&D leadership, product managers, and automation teams to translate scientific needs into modeling strategies
- Communicate results via technical reports, presentations, and publications; mentor junior researchers
Education
- PhD in Materials Science, Computer Science, Physics, Chemistry, or related field preferred
- MS in a relevant quantitative discipline or equivalent industry experience considered
- Strong track record of research or applied work in machine learning or scientific domains
Benefits
- Equity / stock options
- Comprehensive health, dental, and vision insurance
- Paid time off and flexible leave policies
- 401(k) retirement plan or equivalent
- Access to on-site autonomous lab and experimental resources
- Professional development and conference support
- Relocation assistance when applicable
Average salary estimate
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