Postdoctoral Scholar - Law Group - Materials Science and Engineering
Core
Postdoctoral scholar integrating machine learning for autonomous thin-film materials synthesis by molecular beam epitaxy (MBE) within a National Science Foundation Programmable Cloud Laboratory.
Role type
Postdoctoral Researcher (Materials Science & Engineering)
Builds
Autonomous MBE systems, AI/ML workflows for synthesis and characterization, cloud-lab interfaces
Domain
Materials Science, Semiconductor Physics, Machine Learning, Cloud Computing
Deliverable
production ML models
Required skills
Molecular beam epitaxy (MBE) synthesis, Machine learning, Python programming, Data integration
Preferred skills
Chalcogenide materials, Two-dimensional materials, III-V semiconductors, AI/ML workflow frameworks
Technologies
MBE systems, Python, Cloud platforms, Lifetime Sample Tracking database
Responsibilities
Integrate III-V and chalcogenide MBE systems into the LATTICE ecosystem, Develop in situ feedback and control for autonomous deposition tools, Create AI/ML workflows for synthesis and characterization, Support integration of experimental data into the Lifetime Sample Tracking database, Contribute to cloud-lab interfaces for external users, Collaborate with equipment vendors and AI researchers
