The Scientific Computing track of the Computing degree trains students to perform cutting edge research in all of the aspects of the scientific computing pipeline: mathematical and geometric modeling; advanced methods in simulation such as high-performance computing and parallelization; numerical algorithm development; scientific visualization; and evaluation with respect to basic science and engineering. Students will apply this knowledge to real-world problems in important scientific disciplines, including combustion, mechanics, geophysics, fluid dynamics, biology, and medicine. Students will integrate all aspects of computational science, yielding a new generation of simulation scientists who are performing fundamental research in scientific computing, as well as being interdisciplinary bridge-builders that facilitate interconnections between disciplines that normally do not interact. Our mission is to provide advanced graduate training in scientific computing and to foster the synergistic combination of computer and computational sciences with domain disciplines. The School of Computing at the University of Utah is uniquely qualified to train students seeking expertise and experience in scientific computing. Many of the faculty actively conduct collaborations with other faculty both at the University of Utah and at other universities. The School of Computing has scientific computing research efforts in a wide variety of areas, including adaptive methods, inverse and imaging problems, numerical analysis, distributed and parallel computing, problem solving environments, integral methods, sinc function methods, Monte Carlo algorithms, computational complexity and computational science applications. A collaborative base provides students with tremendous flexibility to seek out science which interests them, and strong mentoring from scientific computing track faculty enables students to mature as scientists.

ADMISSIONS
Only Ph.D. degrees in Computing are offered for the Scientific Computing Track. Undergraduate degrees in engineering, science, applied mathematics and computer science are all excellent backgrounds from which to approach scientific computing and apply to the program. Financial support is typically offered for Ph.D. students through teaching assistantships, research assistantships and fellowships.

CURRICULUM
The Scientific Computing curriculum consists of 24 semester hours of classroom training combined with 26 hours of mentor-guided research. The classroom training consists of required and elective courses. The purpose of the required courses is to provide a student with a broad perspective of the computational scientific cycle outlined above; the purpose of the elective courses is to allow the student, with the help of his or her scientific mentor, to develop of course of study which best facilitates his or her Ph.D. research topic.

• PhD in Computing, Scientific Computing Track

For more information about the Scientific Computing Track and Admission, please contact Mike Kirby (kirby 'at' cs.utah.edu).

Scientific Computing Track Faculty