Assistant Research Professor
Core
Developing specialized machine learning models for autonomous thin-film materials synthesis, serving as the perceptual layer for a multi-agent AI framework guiding robotic systems.
Role type
Assistant Research Professor (Machine Learning for Autonomous Materials Synthesis)
Builds
AI systems for real-time predictive modeling and autonomous materials synthesis within the LATTICE cloud laboratory.
Domain
Materials Science / Computer Science / Applied Machine Learning
Deliverable
production ML models
Required skills
Python programming, applied machine learning, computer vision, scientific data analysis, model training/calibration/validation, edge-computing deployment
Preferred skills
deep learning for image analysis, multimodal or multi-task learning, PyTorch or JAX, domain knowledge in materials science/chemistry/physics
Technologies
Python, PyTorch, JAX, atomic force microscopy, reflection high-energy electron diffraction, spectroscopic ellipsometry, X-ray diffraction
Responsibilities
Lead development of ML models for instrument data interpretation; deploy models on edge-computing for real-time feedback; integrate models with Lifetime Sample Tracking platform; collaborate with domain scientists and AI researchers; contribute to scientific direction; mentor graduate students and postdocs.
Seniority
Senior, hands-on IC with mentorship