Postdoctoral Scholar - Law Group - Materials Science and Engineering
Core
Developing machine learning workflows for autonomous thin-film materials synthesis using molecular beam epitaxy (MBE) within a National Science Foundation Programmable Cloud Laboratory.
Role type
Postdoctoral Scholar (Research & Development)
Builds
Autonomous MBE deposition tools and cloud-lab interfaces for external users
Domain
Materials Science / Semiconductor Physics / AI for Science
Deliverable
production ML models
Required skills
Molecular beam epitaxy (MBE) synthesis, Machine learning, Python programming, Data integration
Preferred skills
Chalcogenide materials, 2D materials, III-V semiconductors, AI/ML workflow frameworks, Machine automation
Technologies
MBE systems, Python, LATTICE cloud platform, Lifetime Sample Tracking database
Responsibilities
Integrate III-V and chalcogenide MBE systems into the LATTICE ecosystem, implement in situ feedback and control for autonomous operation, develop AI/ML workflows for synthesis and characterization, support integration of experimental data into tracking databases, collaborate with equipment vendors and AI researchers
Seniority
Postdoctoral (Early-career Researcher)