University of Mississippi

What you'll study

The programme combines core graduate-level mathematics with specialised courses in computation. Typical topics include numerical analysis, numerical linear algebra, numerical solution of ordinary and partial differential equations, optimisation, scientific computing, and computational modelling. Coursework emphasises algorithm development, error analysis and implementation using modern programming environments such as Python, MATLAB and compiled languages where appropriate.

Students normally take a mix of lectures and seminars and have the option to undertake a supervised research project or master’s thesis that applies computational methods to a concrete problem (for example in fluid dynamics, materials modelling, inverse problems or data-driven simulation). Electives allow cross-training in related areas such as probability and statistics, applied analysis, parallel computing and machine learning.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics or a closely related discipline (for example applied mathematics, physics, engineering or computer science) with a strong foundation in calculus, linear algebra and differential equations. The department looks for evidence of quantitative preparation and readiness for graduate-level work.

Typical application materials include official academic transcripts, a personal statement outlining research interests and goals, and letters of recommendation from academic or professional referees. International applicants must demonstrate English language proficiency through an approved test unless exempt. The department may request additional documentation such as a résumé/CV or examples of prior coursework or programming experience.

Career prospects

Graduates with a master’s specialising in computational mathematics are prepared for roles that require advanced quantitative and computational skills. Common career paths include positions as data scientists, numerical analysts, computational scientists, software engineers for scientific applications, and quantitative analysts in finance. Alumni also go on to doctoral programmes in applied mathematics, computational science or related engineering disciplines.

Employers range from technology companies and financial firms to national laboratories, engineering consultancies and research institutions. The programme’s emphasis on algorithm development and practical implementation equips graduates to contribute to multidisciplinary teams that solve data- and simulation-intensive problems.

Why study at University of Mississippi

The University of Mississippi’s Department of Mathematics and Statistics offers a supportive environment with opportunities for close mentoring by faculty working in numerical analysis, applied analysis and computational science. Students can collaborate across departments with engineering, physics and computer science, enabling applied research projects and interdisciplinary training.

Access to institutional computing resources, including the state’s supercomputing centre, supports coursework and research that require high-performance computation. Small cohort sizes and availability of teaching and research assistantships help students gain hands-on experience and build a professional CV for industry or further academic study.

Overall, the programme is well suited to students seeking a mathematically rigorous master’s education that leads directly to computational careers or provides a strong foundation for doctoral study.