The Scientific Computing and Computational Mathematics Program at Stanford University was established in 1987 and is a graduate degree (MS and PhD) awarding unit comprising faculty from a variety of departments, including Mathematics, Computer Science, Operational Research, Statistics, Chemical Engineering, Mechanical Engineering and Electrical Engineering. It was established in recognition of the need for graduate-level training at the intersection of the disciplines of mathematics and computer science, which at the same time draws on applications of fundamental scientific or technological importance.
The core courses, which all MS and PhD students must complete, are two year-long sequences, one in Numerical Analysis and the other in Methods of Mathematical Physics. In addition, both MS and PhD students must complete a year of courses in a focussed application area, a year of courses in Computer Science (Parallel Computing or Data Structures and Algorithms are common choices) and further courses in Applied Mathematics and Numerical Analysis. The choice outside the core sequences is very broad, allowing the flexibility desirable in a Program of this scope, while the core sequences ensure a sound intellectual basis for the Program, and a commonality amongst the students.
PhD theses fall into two broad categories: theoretical studies of computational algorithms for problems in applied and computational mathematics, and the development and application of novel software for the solution of problems of scientific or engineering significance. Students in the former category typically work with faculty from Computer Science, Mathematics, Operations Research or Statistics while those in the second category work with advisors rooted in specific application domains; occasional joint supervision of research also occurs and is encouraged.
Of the PhD graduates of the Program a significant proportion (roughly 45%) have moved on to academic positions, typically in applied and computational mathematics environments. The remainder are distributed through government labs and industry.