Graduate School of Arts & Science PhD students at the University of Virginia who wish to use data-driven approaches in their careers should consider the MSDS/GSAS-PhD dual degree program. 

Graduate School of Arts & Science (GSAS) Ph.D. students at the University of Virginia who wish to use data-driven approaches in their careers should consider the MSDS/GSAS-PhD dual degree program.  

If you are interested in supplementing your Graduate School of Arts & Science Ph.D. with an M.S. in Data Science, or if you’d like more information, email us at  

To Apply: 

  1. Prospective students must plan to take a leave of absence from the Graduate School of Arts & Science PhD program for the full 11 months. 
  2. Meet with your GSAS PhD adviser and ask them to sign the Intent to Apply Form, located at the bottom of this page. 
  3. Upload the signed Intent to Apply Form to your M.S. in Data Science application. Your application will not be considered without the signed form. 

MSDS/GSAS-PhD Fellowship in Data Science

The Graduate School of Arts & Sciences and the School of Data Science are pleased to announce an opportunity for up to three doctoral students to receive an incremental year of fellowship support for the purpose of obtaining a master’s degree in Data Science en route to completing the Ph.D. 

This fellowship program supports students whose dissertation research and professional goals will derive specific and significant benefit from formal training in Data Science.  Students enrolled in an Arts & Sciences doctoral program are eligible to apply for the MSDS/GSAS-Ph.D. Fellowship in Data Science during their second or third* years of enrollment in their Ph.D. program.  

This fellowship will cover tuition, fees, health insurance, and provide a living stipend equivalent to the support provided by the Graduate School of Arts & Sciences for the length (11 months) of the M.S. in Data Science program

* PhD students in their first or fourth year and beyond may apply to the MSDS program but will not be considered for this fellowship.

Proposal Instructions

Proposals will include the following components: 

  • A statement of purpose of three to five pages outlining the relevance and necessity of master’s level training in Data Science to the student’s field of study, prospective dissertation topic, and career goals, citing specific elements of the curriculum for the M.S. in Data Science;

  • An academic plan endorsed by the student’s advisor and Director of Graduate Studies detailing the previous satisfaction of prerequisites for admission to the M.S. in Data Science and a timeline for the integration of any remaining pre-requisite training into the student’s doctoral curriculum; and

  • Two letters of reference from faculty advisors describing their understanding of the training in Data Science that the student will receive and how it will be integrated into the student’s dissertation research. 

  • The above components may be used as part of nominees’ MSDS application materials. 


Timeline Proposals are due on November 1. Fellowship nominees will be notified by the Graduate School by December 1 and must complete the MSDS residential application by the posted priority deadline. The application fee will be waived for nominees. If their application is accepted, they will be notified of a provisional admission decision by February 1 and complete any remaining pre-requisite training during the spring semester.  


  • For questions about applying to this fellowship please contact Tracy Mourton, Associate Director of Graduate Student Enrollment and Engagement, at
  • For questions about the M.S. in Data Science application, please contact Sadie Royal Collins, Director of Academic Operations & Admissions at