M.Sc. in Applied and Computational Mathematics

Applied and Computational Mathematics:

M.Sc. students must complete at least 36 credit hours, within the following guidelines:

• Course-work of 18 credit hours, including two core courses of 6 credit hours (3 credit hours each), three elective courses of 9 credit hours and a Project-Based Learning course of 3 credit hours.
• Thesis-work of 18 credit hours.

M.Sc. students have to pass successfully 6 courses with three credit hours each before applying for the Thesis.

Courses

Core Courses:

• ACM 501: Partial differential equations
• ACM 502: Numerical analysis

Elective Courses:

Students should select 3 courses of 9 credit hours (3 credit hours each). Students can select, with the aid of their academic advisors, elective courses from other science or engineering disciplines.

• ACM 503: Advanced numerical methods for differential equations
• ACM 504: Applied linear algebra
• ACM 505: Dynamical systems
• ACM 506: Fractional differential equations I
• ACM 507: Scientific computing
• ACM 508: Applied functional analysis
• ACM 509: Mathematical and computational modeling in science and engineering

Project-Based-Learning Courses:

M.Sc. students have to participate in the following teamwork project, which is based on self-learning. Students have to present innovative concepts and competitive solutions.

• ACM 701: Project-based learning in applied and computational mathematics.

M.Sc. Thesis:

The M.Sc. candidate should prepare and defend a Thesis based on high-valued research work in one research topic in the fields of applied and computational mathematics.

• ACM 801: M.Sc. Thesis

About the Department

Applied and Computational Mathematics (A.C.M.) is an interdisciplinary program of graduate study. A.C.M. involves both mathematics and a partner discipline such as engineering, biological science, chemistry, sustainable energy or physics, and other diverse fields. The program provides an integrated study of Mathematics; including research experiences, seminar-based learning skills and writing scientific papers and reviews on topics relevant to A.C.M.

Depending on their research area, students will receive high-quality research experience in various A.C.M. aspects including nonlinear dynamics, numerical analysis, and scientific computing, computational methods for electromagnetics, etc. M.Sc. and Ph.D. programs in A.C.M. provide the expertise in mathematical and computational modeling analysis necessary to the University’s contribution to some of today’s most prominent research areas.

The research subjects are supplemented by several courses from different science and engineering programs. It aims to prepare researchers as well as market-ready, well-trained professional graduates in different aspects of computational methods for solving challenging problems arising from scientific and engineering applications.