7018 Applied Physics and Mathematics Building
All courses, faculty listings, and curricular and degree requirements described herein are subject to change or deletion without notice.
Michael Holst, Professor of Mathematics
Julius Kuti, Professor of Physics
The CSME program at UC San Diego recognizes the nation’s growing and continuing need for broadly trained advanced computational scientists in academia, industry and government laboratories. Offering study leading to a MS degree in Computational Science and a PhD in a home department with a specialization in Computational Science, graduates from the CSME program will be well positioned to compete effectively for the best jobs in these areas. The PhD component provides a new specialization in Computational Science, available to doctoral candidates in participating academic departments at UC San Diego.
Computational science refers to the use of computer simulation and visualization for basic scientific research, product development and forecasting. It is an interdisciplinary field that combines mathematics (mathematical modeling, numerical analysis) and computer science (architecture, programming, networks, graphics) with one of the scientific or engineering disciplines.
The CSME program draws upon the expertise of faculty from Bioengineering, Biological Sciences, Chemistry and Biochemistry, Computer Science and Engineering, Electrical and Computer Engineering, Mathematics, Mechanical and Aerospace Engineering, Physics, Scripps Institution of Oceanography, Structural Engineering as well as research staff from the San Diego Supercomputer Center.
Proficiency Requirements: All students must demonstrate advanced undergraduate-level proficiency in numerical analysis and in computer algorithms and data structures. Subject to petition and approval by the CSME Executive Committee, proficiency may be demonstrated by taking UC San Diego’s courses in both subjects while enrolled in the graduate program (four units per course):
Alternatively, proficiency in the material contained in these courses may be satisfied by having previously taken these or equivalent courses at other institutions, or through other evidence of sufficient knowledge of this material. Demonstrating proficiency without taking these courses at UC San Diego is subject to approval by the CSME Executive Committee on an individual basis.
The MS program in CSME leading to an MS in Computational Science is designed to be a two-year program centered around lecture and laboratory courses that focus on obtaining mastery of the primary tools used in computational science. The requirements for the MS degree are as follows:
Proficiency Requirements: Please refer to those outlined above.
|1.||8||MATH 174/274 Numerical Methods and MATH 275 Numerical PDE or
MAE 290A Numerical Methods and MAE 290B Numerical PDE
|2.||4||MATH 176 Datastructures and Algorithms or
CSE 100 Datastructures and Algorithms
|3.||4||PHYS 243 Stochastic Methods|
|4.||8||PHYS 141/241 Computational Physics I: Probabilistic Models and Simulations and PHYS 142/242 Computational Physics II: PDE and Matrix Models|
|5.||4||PHYS 244 Parallel Computing or
CSE 260 Parallel Computing
|6.||8||MATH 210A and B Mathematical Methods in Physics and Engineering or
MATH 270A and B Numerical Mathematics or
MATH 271A and B Numerical Optimization or
MATH 272A and B Numerical Partial Differential or
PHYS 105A and Phys 105B Mathematical and Computational Physics or
PHYS 130A and Phys 130 B Quantum Physics or
Two courses from the following list:
MATH 273A Scientific Computation
MATH 273B Scientific Computation
MATH 273C Scientific Computation
PHYS 225 General Relativity
BIPN 146 Computational Neurobiology
Other science courses as approved by the CSME Executive Committee
|7.||2||CSME Journal Club (2 quarters)|
|38||Total Required Units|
Qualifying Requirements: MS students must pass the final exams in three qualifying exam courses. It is expected that most students will register for and take these courses (four units per course), but the CSME Executive Committee may allow an exceptionally well-prepared student to take the final exams without taking the courses. The three qualifying exam courses have been selected to provide a general broad set of tools in computational science and are as follows:
The list of alternative courses is as follows (four units per course).