Translational Artificial Intelligence Fellowship

Core responsibilities:

• Designing, developing, and deploying modern AI/ML models to analyze complex biological and biomedical datasets
• Integrating and modeling multi-omics data to enable phenotype-driven prediction and insight
• Developing AI models to address translational questions including drug efficacy and safety prediction, mechanism-of-action inference, and biomarker discovery
• Working in close collaboration with experimental scientists, clinicians, and platform teams to refine hypotheses and validate AI predictions

This role creates positive change by accelerating discovery and enabling real-world application of AI technologies in healthcare and biology, working at the intersection of AI, rich multi-omics data, and human-relevant disease models to solve big problems in healthcare and the environment.

Required qualifications:

• PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field
• Strong foundation in modern AI/ML techniques including deep learning, foundation models, and generative approaches
• Experience working with complex biological datasets and multi-omics data
• Ability to work collaboratively with experimental scientists, clinicians, and industry partners

Compensation and benefits:

• Annual stipend of $93,933
• Comprehensive medical, dental, vision, and other benefits through Harvard University
• Access to Harvard's libraries and research core facilities
• Robust administrative and operational support for office and lab needs
• Tuition reimbursement for continued learning
• Newly constructed office and laboratory space in Boston's Fenway District with multiple amenities
• Flexible work arrangements available for some positions