Assistant Research Professor
About The Position
The Materials Research Institute (MRI) at The Pennsylvania State University is seeking an Assistant Research Professor for a term position. This role will focus on applying machine learning to autonomous thin-film materials synthesis. The work involves representation learning for scientific data, multimodal data fusion, and real-time predictive modeling as part of the LATTICE (Layered and Thin Film Technologies with Intelligent Cloud Experimentation) project, an NSF Programmable Cloud Laboratory. The successful candidate will develop specialized machine learning models to interpret scientific data from various instruments (e.g., atomic force microscopy, X-ray diffraction) for an AI system that guides autonomous materials synthesis and interacts with robotic systems. These models will be deployed on edge-computing infrastructure for real-time feedback and integrated with the Lifetime Sample Tracking data platform. The position requires close collaboration with domain scientists, AI researchers, and future users of the LATTICE framework. The candidate will also contribute to the scientific direction of the ML/AI efforts and mentor graduate students and postdoctoral scholars.
Requirements
- Ph.D. in Materials Science and Engineering, Computer Science, Electrical Engineering, Physics, or a related field.
- Postdoctoral or equivalent research experience demonstrating an independent record of publication in applied machine learning, computer vision, and/or scientific data analysis.
- Extensive programming experience in Python.
Nice To Haves
- Experience with deep learning for image analysis.
- Experience with multimodal or multi-task learning.
- Experience with deployment of ML models in real-time or edge-computing environments.
- Domain knowledge of materials science, chemistry, or physics.
- Familiarity with PyTorch or JAX.
Responsibilities
- Lead the development of specialized machine learning models for AI systems to interpret scientific data from instruments.
- Train, calibrate, and validate models against specific data modalities produced by LATTICE instrumentation.
- Deploy machine learning models on edge-computing infrastructure for real-time feedback during deposition.
- Integrate machine learning models with the Lifetime Sample Tracking data platform.
- Collaborate closely with LATTICE domain scientists in thin-film growth and characterization, and AI researchers developing the agentic workflow framework.
- Contribute to the scientific direction of the LATTICE ML/AI effort.
- Mentor graduate students and postdoctoral scholars as appropriate.
Benefits
- Comprehensive medical, dental, and vision coverage.
- Robust retirement plans.
- 75% tuition discount for employees, eligible spouses, and children.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
