Now Accepting Proposals for Placement of a Microsoft–Duke AI Health Fellow for Projects within the School of Medicine

AI Health is currently considering requests for placement of a Microsoft-Duke AI Health Data Science Fellow for projects proposed by Departments/Divisions within the Duke University School of Medicine. The Microsoft–Duke AI Health Data Science Fellowship is a is a 2-year training program in data science with direct application for healthcare. Funded in part by a grant from the Microsoft Corporation, Microsoft-Duke AI Health Fellows will also receive support from AI Health and the Duke Department of Biostatistics and Bioinformatics, with overall program supervision provided by the Duke Clinical Research Institute’s Center for Predictive Medicine. Investigators will be asked to secure a modest amount of support for project costs.

How to Submit a Proposal for Placement of an Microsoft-Duke AI Health Fellow

A Placement Request Form should be completed and emailed to  by 5:00 PM on January 4, 2021. The email should include the subject line “Microsoft-Duke AI Health Fellowship Proposal.” Proposed projects will be evaluated by a panel of clinical and quantitative experts on the basis of impact, feasibility, ripeness for project start in spring 2021, and educational opportunities for Fellows. Final selections will reflect alignment with department and School of Medicine priorities. Fellows will be placed based on the merits of the proposed project, but applicants should address potential for subsequent projects.

About the AI Health Data Science Fellowship Program

The Microsoft-AI Health Fellowship is part of the larger Duke AI Health Data Science Fellowship Program. Designed for early-career data scientists with strong backgrounds in quantitative disciplines, the program is part of a multidisciplinary, campus-spanning initiative that applies machine learning and quantitative sciences to rich sources of healthcare and administrative data, using the insights gained to improve healthcare delivery, quality of care, and the health of individuals and communities.

Data Science Fellows are integrated into multidisciplinary teams, where they are mentored by and work under the direction of the team’s quantitative lead, who offers advanced expertise in data science and machine learning. Fellows also receive guidance and mentoring from the team’s clinical lead(s), who provide insight into the clinical and operational contexts in which projects are embedded, and in some cases receive mentoring from a staff statistician. Data science teams also include a project manager and may include an informaticist.

Each team focuses on a well-defined research question or problem related to healthcare delivery, quality of care, or clinical operations. Working in this intense but supportive environment, trainees acquire essential skills in healthcare analytics and modern machine learning methods, while also benefiting from in-depth exposure to real-world clinical problem-solving. The Data Science Fellow works as a fully integrated member of these multidisciplinary teams, which are assembled jointly with input from AI Health, the Department of Biostatistics and Bioinformatics, Duke University Health System, and Duke School of Medicine clinical leadership.

AI Health Fellows typically work on 2 to 3 projects each year and are encouraged to collaborate across complementary projects as opportunity and topic focus align.