University of Memphis

What you'll study

The programme emphasises numerical and computational techniques used to analyse and solve problems arising in science, engineering and data-driven applications. You will study theory and practical implementation of algorithms, together with the mathematical foundations that justify them.

• Numerical Analysis: consistent and stable discretisation, error analysis, and algorithm design for ordinary differential equations and linear/nonlinear problems.
• Computational Linear Algebra: direct and iterative methods for large systems, eigenvalue algorithms, preconditioning and sparse matrix techniques.
• Scientific Computing and Software: numerical programming, algorithm implementation and optimisation using languages and tools such as MATLAB, Python (NumPy/SciPy) and, where appropriate, parallel computing frameworks.
• Partial Differential Equations and Numerical PDEs: finite difference, finite element and spectral methods for elliptic, parabolic and hyperbolic problems.
• Optimization and Inverse Problems: continuous optimization methods, constrained problems, and parameter estimation techniques common in modelling and data assimilation.
• Probability, Statistics and Data Analysis: stochastic modelling, Monte Carlo methods and basic statistical techniques for model validation.
• Mathematical Modelling and Applications: model formulation, nondimensionalisation and case studies from fluid dynamics, materials science, biology, or logistics.
• Graduate Seminar / Colloquium: presentation skills, current research topics and interaction with faculty and visiting researchers.

Students typically choose between a thesis option, involving original research under a faculty advisor, and a non-thesis option with additional coursework and a capstone or project. The programme is organised to provide a balance of rigorous analysis and hands-on computational experience; exact credit requirements are detailed in the department graduate handbook.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics, applied mathematics, engineering, physics, computer science or a closely related discipline. A strong undergraduate background in calculus, linear algebra, differential equations and basic numerical methods is expected.

• Academic transcripts demonstrating adequate preparation for graduate-level mathematics.
• Letters of recommendation (usually two or three) from academic or professional referees who can speak to mathematical ability and potential for graduate study.
• A statement of purpose outlining research interests, computational experience and career goals.
• A CV or résumé documenting relevant coursework, programming experience and any research or industry experience.
• Proof of English language proficiency for applicants whose native language is not English (tests accepted as specified by the university).

Standardised test requirements (such as the GRE) and minimum GPA expectations are set by the department and can vary; prospective students should consult the Department of Mathematical Sciences at the University of Memphis for the most current policy and any prerequisites that may be required before matriculation.

Career prospects

Graduates with a computational mathematics master’s are well placed for a range of technical careers where numerical modelling and data-driven problem solving are valued. Typical roles include:

• Data scientist, data analyst or machine learning engineer in technology and finance sectors.
• Computational scientist or numerical analyst within engineering, climate modelling, materials, and bioinformatics groups.
• Software developer focusing on scientific computing, simulation tools or high-performance computing.
• Quantitative analyst in finance, risk management and operations research.
• Research assistant or doctoral study in applied mathematics, computational science or related disciplines.
• Technical positions in government laboratories, energy companies and logistics firms that use modelling and optimisation.

The University of Memphis’s location also supports internship and collaboration opportunities with regional industries, research centres and healthcare institutions.

Why study at University of Memphis

The Department of Mathematical Sciences offers close faculty supervision and opportunities to work on applied computational research alongside groups in engineering, computer science and physics. Faculty research covers areas that include numerical analysis, scientific computing, optimisation and applied modelling.

• Access to computing facilities and collaborative labs for high-performance and parallel computing projects.
• Opportunities for interdisciplinary projects and internships with regional industry partners and research centres.
• A balance of theoretical grounding and practical training that prepares students for both industry roles and doctoral study.
• A supportive graduate community with seminars, workshops and chances to present research at conferences.

Prospective students should contact the Department of Mathematical Sciences for detailed information about course planning, faculty research interests and guidance on preparing a competitive application.