The Master in Computational Science and Engineering (M.C.S.E.), is a non-thesis degree program offered jointly by the departments of Computational and Applied Mathematics, Computer Science, Electrical and Computer Engineering and Statistics in the School of Engineering. The program is designed to provide training and expertise in modern and computational techniques with real-world applications in a wide range of industries. The M.C.S.E. graduate degree prepares students interested in technical and managerial positions such as computational scientist, computational engineer and big data analyst, as well as those looking to specialize in high-performance computing and software development techniques and scientific data analysis and visualization.
Students in the M.C.S.E. program select on of the four departments (Computational and Applied Mathematics, Computer Science, Electrical and Computing Engineering, and Statistics) as their home department/area of specialization. M.C.S.E. students take a core of courses from all four departments, but are expected to focus their course electives on courses in their home department.
Please note that the official requirements for the Master in Computational Science and Engineering degree will be updated for the 2020-2021 academic year. The revised requirements, implemented to support the overall aim of the program to create talent with depth and breath, will include substantial credit requirements from the students’ home department combined with requirements for breath across the departments involved in the program.
The official program requirements will be posted soon in the General Announcements. Upon matriculation, you must meet with an advisor to discuss your course work.
Fall admission — February 1
After you've reviewed the program and application requirements, click here to apply.
For additional information about the program contact firstname.lastname@example.org
The General Announcements (GA) is the source of the official Rice curriculum: M.C.S.E. In the event that there is a discrepancy between the GA and any other websites or publications, the GA shall prevail as the authoritative source.