Cost & earnings at University of Mississippi What students borrow here, and what they go on to earn
The Bachelor of Arts/Bachelor of Science in Mathematics with a Computational Mathematics emphasis at the University of Mississippi combines core mathematical theory with practical computational skills. It suits students who enjoy rigorous problem solving and want preparation for careers or further study in scientific computing, data analysis, engineering, finance or actuarial work.
The computational mathematics pathway builds a solid foundation in pure and applied mathematics while emphasising numerical methods and algorithmic implementation. You study the core calculus and linear algebra sequence alongside courses in differential equations, real analysis and probability and statistics. Computational-focused modules introduce numerical analysis, scientific computing, numerical linear algebra, mathematical modelling and optimisation.
Admission to the University of Mississippi is based on a candidate's overall academic record. For the computational mathematics pathway, successful applicants typically present a strong high-school transcript with substantial achievement in mathematics and related STEM subjects. Preparation such as AP Calculus, IB Higher Level Mathematics, or college-level calculus is recommended.
Applicants should demonstrate quantitative readiness through coursework and, where submitted, standardised test scores. International applicants are expected to meet the university's English language requirements and provide equivalent documentation of secondary education preparation. Transfer applicants will usually need to show college-level mathematics progress and a clear course-by-course record.
Graduates with a computational mathematics focus are equipped for roles that require mathematical modelling, numerical computation and data analysis. Common career paths include:
The Department of Mathematics and Statistics at the University of Mississippi offers a curriculum that balances rigorous theory with hands-on computational practice. Undergraduates have access to faculty-led research, computing labs and opportunities for capstone projects that collaborate with other departments such as computer science and engineering.
The campus supports experiential learning through internships and career services that connect students with regional and national employers. Small-to-medium class sizes in upper-level courses allow close faculty mentorship, and the programme prepares students both for immediate entry into technical roles and for competitive graduate study in computational and quantitative disciplines.
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