Ph.D. Program

A PhD degree program in computational science is offered jointly by the University of California, Irvine (UCI) and the CSRC at San Diego State University. The doctoral program is designed to train future computational scientists who will go on to pursue careers as academic professionals, scientists, and engineers. Students learn to develop advanced computational tools, models, and simulations to solve challenging problems at the intersection of multiple scientific disciplines. The diverse resources provided by UCI and SDSU, combined with strong partnerships with government and industry, enable valuable training opportunities. Students perform multi-disciplinary research and benefit from hands- on experience developing solutions to real-life problems that span physics, bio-medical, defense, communications, healthcare, environmental safety, engineering, aerospace, seismic risk, and more.

The curriculum includes doctoral level coursework from both UCI and SDSU. Each student’s doctoral committee includes faculty from both UCI and SDSU. Programs of study include coursework in the following areas in addition to doctoral research:

• Mathematical & computational modeling
• Scientific computing
• Parallel programming & algorithm development
• Computational imaging
• Visual computing
• Mathematics
• Numerical analysis
• Statistical methods
• Data analysis, Monte Carlo methods
• Data science/data mining
• Learning theory
• Computational biology
• Probabilistic modeling
• Scientific writing

Program Learning Outcomes (PLOs):

The graduates of the Computational Science doctoral degree program must be able to:

1. Describe and formulate a problem statement that requires computational tools to solve
2. Compare, critically evaluate and choose from existing computational approaches or models, or develop new computational approaches or models for solving problems in physical, biological or engineering systems
3. Formulate solutions within the limitations of available computational resources and data to develop and validate computational models
4. Synthesize and assimilate data for improving the accuracy of computational models and the performance of computational methods
5. Assess the accuracy, robustness and efficiency of numerical approaches and algorithms
6. Use existing software and computational tools to conduct research and advance knowledge in an area of inquiry, and develop new tools as necessary that can be used, modified and advanced by others
7. Document and communicate (orally and in writing) computational research and results to varied audiences and users
8. Acquire, follow, and implement best practices in generating, handling, and analyzing data; develop the ability to critically question the design of algorithms and their purposes; abide by and promote scientific integrity and accountability

Assessment:

Students are assessed through the following means:

1. Research Report Exam
2. Dissertation Proposal Exam
3. Dissertation Defense
4. Publication of Peer-Reviewed Articles
5. Institutional Data (Time-to-Degree, Graduation Rates)
6. Employment Placement Rates
7. Student Surveys
8. Alumni Surveys

For more information, please contact:

Computational Science Graduate Advisor
Dr. Jose Castillo
jcastillo@sdsu.edu