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.
While working toward a PhD, University of Virginia GSAS doctoral students can learn and apply new data science techniques to their research. If you have interest in supplementing your Graduate School of Arts & Science PhD with an M.S. in Data Science, or if you’d like more information, email us at firstname.lastname@example.org.
- Prospective students must plan to take a leave of absence from the Graduate School of Arts & Science PhD program for the full 11 months.
- Meet with GSAS PhD adviser and ask them to sign the Intent to Apply Form (see below).
- Upload the completed Intent to Apply Form (see below) to your M.S. in Data Science application; you cannot apply without the completed form.
- Must pay full tuition and fees for the MSDS program
For questions about the program, email us at: email@example.com.
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 PhD.
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-PhD Fellowship in Data Science during their second or third* years of enrollment in their PHD 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 independently, but will not be considered for this fellowship.
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.
Proposals are due on November 1. Fellowship nominees will be notified by the Graduate School by December 1 and must complete the application for admission to the M.S. in Data Science by December 15. The application fee will be waived for nominees. If their application is accepted, they will be notified of a provisional admission decision by January 15 and complete any remaining pre-requisite training during the spring semester.