There’s no choice but to lead when you’re breaking new ground. Guide rapid development in an emerging field when you earn a Ph.D. in Data Science through the IU School of Informatics and Computing at IUPUI.
Graduates of our program—the first of its kind in both Indiana and the Big Ten—develop the skills to make pioneering research contributions to data science theory and practice in academic and the industrial sectors.
Data scientist = #1
Job ranking in America per Glassdoor, with $110,000 median base salary
From life science to product development, the demand is only growing for professionals who can apply principles of data science to specific areas. Our graduates learn to define and investigate relevant research problems in this interdisciplinary field.
The School of Informatics and Computing at IUPUI offers students a unique opportunity to work with faculty who are international leaders in their fields, and to collaborate with researchers from leading global health and life science research centers on campus and in Indianapolis.
Our students acquire the skills to develop inventive and creative solutions to data research problems—solutions that demonstrate a high degree of intellectual merit and the potential for broader impact. The Ph.D. curriculum also prepares students to make research contributions that advance the theory and practice of data science.
“We provide a rigorous, high-quality, competitive program that prepares intellectual leaders in a rapidly developing field.”
Karl MacDorman, associate dean of academic affairs and director of the data science program
Graduates learn to develop and evaluate novel approaches to collecting, organizing, managing, and extracting knowledge and insights from massive, complex, distributed, heterogeneous data sets. The program hones students’ ability to:
Deep technical skills and the ability to formulate and test hypotheses using massive and heterogeneous data provide the foundation for graduates who can become successful researchers either in academic settings or in industrial research and development laboratories.
This degree leads to positions within academia that include research, research support, and tenure-track positions in major universities.
Positions in industry include:
May include up to 6 credit hours of INFO-I 790 Informatics Research Rotation.
The student must complete a minor within a domain appropriate to the chosen specialization and/or research area. All courses must be graduate-level and taken outside the Data Science program.
A student must successfully complete a written and oral qualifying examination before the fifth semester of the program. The written exam has a breadth part and a depth part. The breadth part covers the program’s core courses. The depth part additionally covers material from the student’s research.
The oral exam takes place shortly after the student passes the written exam. The oral exam is based on the student’s response to the written exam and the core courses. The both the written and oral exams are prepared and evaluated by faculty in the school who are familiar with the content of the core courses.
The student must pass both the written exam and the oral exam before advancing to candidacy. The student may retake once either the written exam or oral exam, but not both, if they do not pass that part on the first attempt. For further details, consult with the data science program director.
A dissertation is a written elaboration of original research that makes creative contributions to the student’s chosen area of specialization. The student will enroll multiple times in INFO I890 Thesis Readings and Research (1-12 cr.) while completing the dissertation. All requirements must be completed within seven years of passing the qualifying exams. The dissertation process includes the following components:
Please refer to the IUPUI Graduate School Bulletin for more details on the dissertation process.
Students will demonstrate competency in research:
Students will demonstrate competency in data analytics:
Students will demonstrate competency in data management and infrastructure: