Program Information
The CSS Ph.D. Program is designed to train students to integrate computational and statistical methodologies to formulate, model, analyze, and solve research problems of interest to the natural, physical, and social sciences, including biology, chemistry, physics, engineering, geography/GIS, pharmacy, medicine, economics, and finance. Broadly speaking, the program has strong research components in biostatistics, bioinformatics, and computational methods. More specifically, the program leads to research in a variety of areas that may include: artificial neural networks and fuzzy logic modeling, biological modeling, bioinformatics, biostatistics, computational biology, computational chemistry, computational mathematics, computational statistics, computational physics, computational finance, computer science, data visualization and data mining, ecological modeling, spatial-temporal data modeling, and transport processes.
Available Options for Graduate Degrees
| Doctor of Philosophy |
60 Credit Plan |
Core Requirements
- Pass qualifying exams over emphasis-area-specific preparatory courses Credits: 0-12
- (must be taken three times for credit) Credits: 3
- Dissertion Support Elective Credits: 6-12
- Credits: 27-45
For further details about program requirements review the department’s webpage and the program handbook online.
Additional Admission Requirements
GRE: Not required
TOEFL: For the PhD program, a department requirement of 575 paper-based or 230 computer-based
General Requirements
Graduate students should consult with their advisor before registering for graduate work.
See Doctor of Philosophy Degree Requirements
Additional Graduation Requirements
-
Must pass a qualifying exam based on the core sequence of the student’s emphasis area
-
Must pass written and oral comprehensive exams, as designed by the student’s advisory committee.
Course Offerings
Mathematics and Statistics (MATH, STAT, CSS) Course Offerings
