Who should apply?
As the nation's first standalone School of Data Science to offer a Ph.D. program, we are seeking candidates who wish to study cutting-edge techniques that rely on data to further science. Ph.D. students are expected to be the next generation of data science researchers and experts, contributing to and pushing the discipline forward.
The Ph.D. in Data Science is a rigorous program, and applicants must demonstrate their ability to succeed in our educational environment. We are seeking candidates from a variety of majors, disciplines, and backgrounds, so no specific program of study is required. However, completion of prerequisite courses is required prior to matriculation.
Successful Ph.D. students will be:
- Intellectually curious and prepared to engage in the intensive study of data science.
- Proficient in high-level quantitative and technical skills (i.e., fluent in discrete mathematical and statistical concepts and proficient in a programming language).
- Passionate about understanding how data is captured and communicated to make informed decisions.
- Motivated, studious and mature; willing to contribute to our community as teaching assistants, researchers, and colleagues.
Prerequisite Courses and Minimum Qualifications
We welcome applicants from all undergraduate majors or programs of study who have earned their bachelor's degree prior to matriculation from a three- or four-year accredited institution.
The Ph.D. in Data Science program requires several prerequisite courses. You can still apply without having all prerequisites, but they must be completed prior to matriculation. Proof of completion will be required for any incomplete prerequisites if an applicant is admitted and accepts their offer of admission.
The following are required upon matriculation:
- A course or courses from an accredited college or university that covers concepts through multivariable calculus and functions in more than one dimension. In the U.S., this is typically a three-course sequence (Calculus I, Calculus II, Calculus III).
Matrix Algebra or Linear Algebra
- Evidence of proficiency in matrix algebra via a linear algebra or similar mathematics course from an accredited college or university, or completion of Linear Algebra for Data Scientists (NEW PROGRAM offered online by the School of Data Science).
- At least one course from an accredited college or university that covers concepts in probability and statistical inference.
- This experience can be demonstrated by completion of a course in computer science from an accredited college or university or substantial experience working with a programming language (such as Python, R, Matlab, C++, or Java). We will ask you to detail this experience in your application.
The following materials are required for review of your application:
Essay and Short Answer Prompts
- Why do you want to get a PhD, and why did you choose the field of data science? (500 word limit, required)
- Tell us about a data science experience that you have directly contributed to and learned from. Describe the project, your role, and what was accomplished. (250 word limit, required)
- You can study data science anywhere in the world. Why do you want to study at the University of Virginia? (200 word limit, required)
- What data science problem are you passionate about solving? (200 word limit, required)
- You may provide insights into any negative aspects of your application or extenuating circumstances in this optional addendum. (200 word limit, optional)
Upload all unofficial transcripts from your entire post-secondary academic record, including all undergraduate- and graduate-level coursework.
- If you earned an undergraduate degree from an institution (or institutions) in which English is the primary language, unofficial transcripts are sufficient.
- If you earned an undergraduate degree from an institution (or institutions) in which English is not the primary language of instruction, a course-by-course credential evaluation is required to help us better understand your educational background and capabilities. SpanTran is a NACES-member company that has created a custom application for the School of Data Science to ensure you get the right kind of evaluation at a discounted rate. You can access their application by clicking here. For a full list of credential evaluators, visit NACES.
If admitted to the School of Data Science and you decide to accept your offer, you will be required to submit official transcripts and proof of degree conferral prior to enrolling. Send official transcripts electronically to firstname.lastname@example.org or by mail to:
School of Data Science Admissions
P.O. Box 401109
Charlottesville, VA 22904
Physical Address (for DHL and FedEx)
School of Data Science Admissions
1001 Emmet Street North
Charlottesville, VA 22903
The Ph.D. in Data Science does not review standardized test scores (i.e., GRE, GMAT, MCAT) in its holistic evaluation of applicants.
English Language Tests
- If you earned an undergraduate degree from an institution (or institutions) in which English is the primary language, you need not submit English Language Test scores, and the TOEFL/IELTS requirement will be automatically waived.
- If you earned an undergraduate degree from an institution (or institutions) in which English is not the primary language of instruction, you must self-report TOEFL or IELTS scores. Official scores are only required if admitted to the program. TOEFL and IELTS scores are valid for two years after test date.
Send official TOEFL scores via ETS to institution code B875 (no department code needed). The minimum TOEFL (iBT) score requirement is 100 (including minimum section scores of 22 in speaking, 22 in writing, 23 in reading and 23 in listening).
Request that your test scores be sent electronically via the IELTS system by contacting your IELTS center directly. No paper Test Report Forms will be accepted. No institution code or department code is needed. The minimum IELTS score requirement is 7.0 (including minimum section scores of 6.5).
Letters of Recommendation
Three letters of recommendation are required as part of the online application. Once you have saved the contact information for a reference, the individual will receive email instructions to submit a letter of recommendation on your behalf. It is preferable (but not required) for at least two letters to be from an individual with substantial knowledge of your academic accomplishments.
Résumé or Curriculum Vitae
A résumé or curriculum vitae helps us get to know an applicant beyond their formal academic coursework. There is no preference for students with or without professional work experience; in fact, we hope your resume will demonstrate your preparedness for graduate study, including involvement in activities outside of school or work (such as leadership, service, family responsibilities, civic engagement), coding or research projects, and any other accomplishments you’d like to share.
A non-refundable application fee of $85 is required prior to submission of the application.
Fee Waivers (U.S. Citizens and Permanent Residents)
Per UVA policy, we provide application fee waivers for US citizens and permanent residents who meet the Application Fee Waiver Eligibility criteria and submit an Application Fee Waiver Request Form. In addition, application fees are waived for full-time UVA employees who have worked more than 90 days at the University (contact the admissions team for the employee fee waiver code). You cannot be granted a fee waiver after payment of the application fee. An application will not be considered submitted until the fee is paid.
Fee Waivers (International Applicants)
The School of Data Science is committed to diversity which we define as excellence expressing itself through every person’s perspective and lived experience. We acknowledge that financial disparities exist that may discourage prospective students from applying. In hopes of creating and increasing access to our graduate programs, we currently provide application fee waiver to citizens from the countries listed below.
- Burkina Faso
- Central African Republic
- Democratic Republic of the Congo
- Lao People's Democratic Republic
- Sao Tome and Principe
- Sierra Leone
- Solomon Islands
- South Sudan
- United Republic of Tanzania
For technical questions about the application, contact email@example.com. For all other questions, connect with us.
Application Cycle for Fall 2023
Applications for the 2023-2024 academic year will be available mid-August 2022. The application process is competitive, and applicants are encouraged to submit all required materials by the Jan. 6 priority deadline in order for their application to be considered complete, ready for review, and considered for funding.
Prospective students are encouraged to start an application, request letters of recommendation, and review prerequisites and application requirements.
Aug. 15, 2022
Open Houses (In-Person)
Oct. 22, 2022 | RSVP
Nov. 11, 2022 | RSVP
Priority Application Deadline
Jan. 6, 2023 (11:59 pm ET)
The priority deadline is for those wishing to be considered for early admission and full funding. Applications received after Jan. 6 will be considered on a space-available basis with rolling decisions through the final deadline of Mar. 20.
Prospective Ph.D. Students' Day
Feb. 10-11, 2023
The School of Data Science will invite selected candidates to Charlottesville, VA, to visit UVA and SDS, connect with current and other prospective Ph.D. students, and to engage in round-robin admission interviews with Data Science faculty.
Priority Decision Released
By Mar. 10, 2023
Final Ph.D. Application Deadline
Mar. 20, 2023 (11:59 pm ET)
Final Decisions Released
Early April 2023
Decision and Deposit Deadline
Apr. 15, 2023 (11:59 pm ET)
Funding Your Degree
Doctoral students typically receive financial support, including twelve-month living support and full remission of tuition, fees, and the premium for single-person coverage through the University of Virginia’s student health insurance plan. Tuition and fees are set annually by the University of Virginia Board of Visitors in early spring.