Rowan Ph.D. in Data Science

The Ph.D. in Data Science program will provide the essential skills required to analyze complex data sets and equip students with a broad understanding of data challenges and opportunities.

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Program Details

Alongside developing the skills necessary to enter the field of data science, the Ph.D. in Data Science Program sharpens students' research and inquiry skills in order to independently conduct research and answer questions within their area of concentration.

To meet this goal, courses in the Ph.D. in Data Science Program curriculum are organized around interdisciplinary focal areas in computer science, engineering, mathematics, and statistics. Courses offered within this framework include traditional lecture-style, e-learning, and special topics courses that introduce students to the latest theories, methods, and emerging issues; seminar series; and experiential learning through thesis research, (directed independent study and internship programs). Through this framework, students will gain proficiency in the application of scientific principles such as critical thinking, experimental design, data preprocessing and wrangling, data visualization, advanced statistical learning/data mining and machine learning, as well as a sense of professional and technical writing, and reporting, responsibility, and integrity.

Rowan University assesses the effectiveness of doctoral programs to ensure that participating students have the maximum opportunity to develop the foundational knowledge, skills and confidence to become creative independent researchers in their selected career path.

The Ph.D. in Data Science is a rigorous academic program that seeks to set up doctoral students for success as researchers, scientists, and data science professionals. In addition to developing strong foundational knowledge about the field of data science, students will acquire the following skills:

Expertise and experience to apply the theories and methodologies of data science to establish a basis for future research.
Mastery of ethical data practices, methods, and procedures.
Ability to conduct independent, original research and acquire resources necessary to successfully execute a depth knowledge of a research project.
Expository and oral communication skills.
Engagement in professional outreach to advance the field.
Ability to produce high-quality publishable research that advances understanding of important topics or problems.
Ability to lead others in educational activities and research and development projects.

Students seeking a Ph.D. in Data Science should have a Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or related field from an accredited institution of higher learning with a minimum undergraduate cumulative GPA of 3.0 (on a 4.0 scale). Depending on the undergraduate area of study, completion of additional foundation courses may be required.

Students in the Master's program can transfer to the doctoral program. To qualify for the transfer, Master's students must have a cumulative MS GPA of 3.3 with no grade lower than a B at the end of the spring semester of their first Master's year. If not, they may successfully complete the MS and then be allowed to transfer into the Ph.D. program, completing the remaining coursework and graduation requirements. Courses completed in the Master's program will be applied towards the Ph.D. Students in the Ph.D. program may choose to switch to the MS program if desired.