Structure and expectations

Fellowship positions typically last two years, with the possibility for extension. Each fellow has a quantitative faculty mentor who oversees their training and cultivates expertise in specific data science methods and their application to health. Fellows also receive project-specific clinical mentorship to support their training in healthcare applications and ensure their work addresses real healthcare needs. The AI Health Fellowship leadership provides training activities and maintains a collaborative, inclusive learning environment promoting outstanding, trustworthy AI Health research.

Fellows learn and uphold best practices in project, data, and code management; project documentation and reproducibility; and effective collaboration in an academic medical center environment. They attend and present their work at biweekly research meetings, AI Health seminars, Health Data Science Poster Showcases, and other events.