Postdoctoral Scholar: AI-Driven Thin-Film Materials

Penn State University; University Park (IL); On-site; USD 52,000 - 78,000; Full time

Benefits offered by this job

Competitive benefits package

Job summary

Penn State University in University Park, PA seeks a postdoctoral scholar in Materials Science and Engineering to advance machine learning for autonomous thin-film materials synthesis within the LATTICE project.

You will build ML models to interpret data from AFM, RHEED, ellipsometry, XRD, deploy on edge computing, and collaborate with domain scientists, AI researchers, and future users of the framework.

Qualifications

• PhD in a relevant field with a strong record of research in applied machine learning, computer vision, or scientific data analysis.
• Experience with deep learning for image analysis and multimodal data is preferred.
• Strong programming in Python; familiarity with PyTorch or JAX is advantageous.

Responsibilities

• Develop ML models to interpret data from instruments like AFM, RHEED, ellipsometry, and XRD.
• Deploy models on edge-computing infrastructure for real-time feedback during deposition.
• Collaborate with LATTICE domain scientists, AI researchers, and future users of the framework.
• Integrate models with the Lifetime Sample Tracking data platform.

Skills

Machine learning

Applied ML

Computer vision

Scientific data analysis

Python

Education

PhD in Materials Science and Engineering

PhD in Computer Science

PhD in Electrical Engineering

PhD in Physics

Tools

PyTorch

JAX

Edge computing

X-ray diffraction

Atomic force microscopy

Job description

Penn State University in University Park, PA seeks a postdoctoral scholar in Materials Science and Engineering to advance machine learning for autonomous thin-film materials synthesis within the LATTICE project.

You will build ML models to interpret data from AFM, RHEED, ellipsometry, XRD, deploy on edge computing, and collaborate with domain scientists, AI researchers, and future users of the framework.