Stephanie Law
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Postdoctoral Scholar in Molecular Beam Epitaxy and AI/ML for Thin-Film Materials Synthesis Pennsylvania State University in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Postdoctoral scholar position at Pennsylvania State University as part of the NSF-funded LATTICE Programmable Cloud Laboratory. Funding details such as stipend or duration are not stated in the post.
Country
United States
University
Pennsylvania State University

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About this position
Stephanie Law at Pennsylvania State University is hiring a postdoctoral scholar for the LATTICE Programmable Cloud Laboratory at the University Park campus.
This position focuses on molecular beam epitaxy (MBE), thin-film materials synthesis, and AI/ML-enabled autonomous experimentation. The scholar will help integrate existing III-V and chalcogenide MBE systems into the LATTICE ecosystem, with emphasis on in situ feedback and control, autonomous operation of deposition tools, and machine-learning workflows for synthesis and characterization.
Additional responsibilities include integrating experimental data and model outputs into the Lifetime Sample Tracking database and contributing to cloud-lab interfaces for external users. The role involves collaboration with equipment vendors, AI researchers, data scientists, and future users of the platform.
Eligibility highlights: MBE experience is required. Experience with data science or machine learning workflows is beneficial.
Funding: This is a postdoctoral scholar appointment associated with an NSF Programmable Cloud Laboratory. The post does not list stipend, duration, or other financial details.
How to apply: Use the application link provided in the post and review the Workday job posting for full details.
Funding details
Postdoctoral scholar position at Pennsylvania State University as part of the NSF-funded LATTICE Programmable Cloud Laboratory. Funding details such as stipend or duration are not stated in the post.
What's required
Molecular beam epitaxy experience is required. Experience with data science or machine learning workflows is beneficial. The postdoctoral scholar will work on autonomous thin-film materials synthesis, so familiarity with in situ feedback/control, deposition tools, and materials characterization is advantageous.
How to apply
Apply through the linked job posting. Review the position details and submit an application via the provided Workday link.
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