Graduate Catalog | 2025-2026
Data Science, Ph.D.
|
|
 Return to: Graduate Academic Programs (A-Z)
The Ph.D. in Data Science (DTSC) is transdisciplinary by design and lays emphasis on the mastery of the data science tools and methodologies and on responsible stewardship of data to cover the broad value of data science in various domains across society. Strong emphasis is placed on providing students the opportunity to demonstrate mastery of knowledge in multiple data science application domains.
The program provides research intensive doctoral-level education for students seeking Data Science careers in practice, research and teaching/academia. It is intended to produce researchers fluent in the emerging field of data science and to develop an environment for their education and training. The objectives of the Data Science Ph.D. include:
● Preparing research data scientists, professional data scientists, and scholars/academicians who will be leaders in developing, maintaining, and managing data ethically and effectually to sustain the economic and social vibrancy of North Carolina and the United States;
● Developing research data scientists who have a deep understanding of data, statistics, computing, and ethics frameworks such that they can build new knowledge across fields and society by appropriate data collection, methods development, and deep analysis;
● Providing a range of educational and research experiences for a diverse group of students to participate in research initiatives at UNC Charlotte, Private, Public, and International institutions; and,
● Preparing future data science educators, and scholars, who are at the frontiers of understanding and disseminating data science knowledge.
|
General Admission Requirements
The DTSC PhD program seeks the following for successful applicants to the program: - With the equivalent to a Master’s degree from a college or university accredited by an accepted accrediting body, in data science or in a related field, with a minimum undergraduate GPA of 3.0 and a minimum graduate GPA of 3.5 (on a 4.00 scale), or a baccalaureate degree from a college or university accredited by an accepted accrediting body, with an undergraduate GPA of 3.2 or above and overall outstanding academic credentials.
- English proficiency: Any applicant whose native language is other than English must demonstrate English proficiency. Either prior academic or work experience in an approved English-speaking country (per UNC Charlotte Graduate School guideline) or an acceptable score on the Test of English as a Foreign Language(TOEFL), International English Language Testing System (IELTS), or Duolingo English test:
- TOEFL iBT (Internet-based): 83 or higher;
- IELTS: Overall band score of 6.5 or higher;
- Duolingo English Test: 115 or higher.
- A satisfactory score (>50th percentile from the aptitude portion of the GRE). The GRE can potentially be waived if one of the following conditions is met.
- Earned a degree from an accredited U.S. college or university with a cumulative undergraduate GPA of 3.0 and above or graduate GPA of 3.5 and above.
- Hold a terminal degree (e.g., J.D., M.D., or Ph.D.).
- GRE/GMAT waiver request must be submitted in writing and approved by the Ph.D. program director before submitting the application. *Please note: a waiver of the GRE/GMAT requirement does not constitute an offer of admission into the program.
Prerequisite Courses/Background Applicants may apply without having all prerequisites listed below at the time of application, but all prerequisites are expected to be completed prior to matriculation. Proof of completion will be required for any incomplete prerequisites if an applicant is admitted and accepts the offer of admission. - Mathematics: A course or courses from an accredited college or university that covers concepts through multivariable calculus and functions in more than one dimension. Evidence of proficiency in matrix algebra via a linear algebra or similar mathematics courses from an accredited college or university.
- Statistics: A course or courses in Statistics from an accredited college or university that cover concepts in probability and statistical inference.
- Programming Experience: This experience can be demonstrated by completion of one or more computer programming courses from an accredited college or university or substantial experience working with one or more programing language (such as Python, R, Matlab, C++, or Java).
Advanced Standing Option To be eligible for the Advanced Standing Option for the Ph.D. in Data Science program, students must meet all the admission requirements listed above AND must demonstrate experience or courses in the following areas: - Statistics: One or more courses in advanced statistics.
- Machine Learning: One or more courses in machine learning, artificial intelligence, or other areas of algorithmic development.
- Visualization and communication with data: One or more courses or equivalent experience in the visualization communication data.
- Databases: One or more courses or equivalent experience with the management of data.
Students can be admitted to the doctoral program on a part-time basis, including the Advanced Standing option. For admission, applicants must meet both University Graduate School requirements as well as program specific requirements. Full details on University Graduate School requirements can be found in the most recent version of the University Graduate Catalog. Documents to be submitted for admission - Graduate School Application for Admission (online)
- Application Fee: A nonrefundable, nontransferable application processing fee is required for each application submitted.
- $75 USD for U.S. Citizens and Permanent Residents
- $85 USD for International Applicants
- Unofficial transcripts of all academic work attempted beyond high (secondary) school. An official (officially certified) final transcript must be submitted if an applicant is offered admission. International transcripts provided in a language other than English should be uploaded via the online application system, but an officially translated version should be uploaded as well.
- Official TOEFL, IELTS, or Duolingo English test score (for applicant whose native language is other than English and must demonstrate English proficiency).
- A personal and original statement of purpose (essay indicating research interests and motivation on study in the Ph.D. program at the School of Data Science, and one or more potential faculty advisors identified) in the range of 500 words, submitted online as part of the application material.
- Three letters of recommendation, at least two of which are highly preferred to be from faculty members (submitted online by recommenders)
- Official GRE/GMAT test scores.
- A resume (online).
- A writing sample from the most recent degree and a sample of their recent research activities and output (optional)
Application Deadlines Deadlines are in accordance with UNC Charlotte Graduate School deadlines. However, to ensure full consideration for financial support, applications must be received by February 1st, 5PM EST for Fall admission. Degree Requirements - Advanced Standing Option (42 credit hours)
Students admitted to the Advanced Standing option of the program must complete 36 credit hours of core requirements (18 credits of course work and 18 credits of Dissertation Research - DTSC 8900 ) and 6 credit hours of electives with the approval of their advisor and of the DTSC Program Director. In addition, students must take GRAD 8302 (Responsible Conduct of Research) and GRAD 8990 (Academic Integrity). Data Science Courses (18 credit hours)
Responsible Conduct of Research
Dissertation Research (18 credit hours)
Electives (6 credit hours)
6 credit hours of electives, provided that they would be relevant to the student’s program of study and research, with the approval of student’s advisor and of the DTSC Program Director. Degree Requirements - Standard Standing Option (72 credit hours)
Students admitted to the Standard Standing option of the program must complete 36 credit hours of core requirements (18 credits of course work and 18 credits of Dissertation Research - DTSC 8900 ) and 36 credit hours of electives with the approval of their advisor and of the DTSC Program Director. In addition, students must take GRAD 8302 (Responsible Conduct of Research) and GRAD 8990 (Academic Integrity). Data Science Courses (18 credit hours)
Responsible Conduct of Research
Dissertation Research (18 credit hours)
Electives (36 credit hours)
36 credit hours of electives, provided that they would be relevant to the student’s program of study and research, with the approval of student’s advisor and of the DTSC Program Director. Degree Total = 72 credit hours (42 credit hours for students with advanced standing)
|
Return to: Graduate Academic Programs (A-Z)
|