Fellow in AI/ML for Scientific Applications, Foundation Models, and AI Systems
Kempner Institute for the Study of Natural and Artificial Intelligence Fellow in AI/ML for Scientific Applications, Foundation Models, and AI Systems
Summary
Research fellow at Harvard's Kempner Institute conducting AI/ML research on foundation models, agentic workflows, and tool-using AI systems for scientific applications, including life sciences. Day to day: implementing, training, evaluating, and fine-tuning deep learning models in Python with PyTorch or JAX under a Kempner investigator's direction.
You will conduct research under the direction of a Kempner Institute investigator. You will advance foundation models, agentic workflows, tool-using models, and AI systems for scientific applications, including life sciences. You will collaborate on foundational machine-learning and domain-informed research.
Responsibilities
- Conduct research under the direction of a Kempner Institute investigator
- Advance foundation models, agentic systems, and AI approaches for scientific applications
- Collaborate on foundational machine-learning and domain-informed scientific applications
Requirements
- Bachelor’s or master’s degree in a related quantitative field
- Modern AI/ML
- Deep learning
- PyTorch or JAX
- Research publications or substantial open-source research contributions
- Machine learning model implementation, training, evaluation, or fine-tuning
- Python
- Research code maintenance
- AI-assisted and agentic coding tools
- Technical communication