Research Fellow (Computer Engineering/Computer Science/Applied Mathematics)
Core
Conduct research on efficient AI-for-Science systems using foundation models and parameter-efficient adaptation to enable scientific reasoning.
Role type
Research Fellow (AI for Science)
Builds
Automated research workflows integrating autonomous discovery pipelines with deep learning architectures
Domain
AI for Science, Machine Learning, Optimization
Deliverable
production ML models
Required skills
foundation models, parameter-efficient adaptation (LoRA), optimization methods, deep learning, Python, PyTorch, software prototyping, experimental design, hypothesis formulation
Preferred skills
PhD in Computer Engineering/CS/Applied Mathematics, prior ML systems development experience, convex optimization background
Technologies
PyTorch, Python
Responsibilities
Develop software prototypes for automated research workflows, collaborate on translational applications, publish in top-tier conferences, supervise graduate students
Seniority
Mid-Senior, hands-on IC
