University of South Alabama

What you'll study

The programme emphasises numerical analysis, algorithm development and the practical use of computing tools to solve continuous and discrete mathematical problems. Core topics typically include numerical linear algebra, numerical solution of ordinary and partial differential equations, scientific computing, optimisation and approximation theory. Students also study computational aspects of probability and statistics, mathematical modelling and advanced topics in applied analysis.

• Numerical Analysis and Error Analysis
• Numerical Linear Algebra and Iterative Methods
• Numerical Methods for Ordinary and Partial Differential Equations
• Scientific Computing and High-Performance Computing Techniques
• Computational Optimisation and Inverse Problems
• Mathematical Modelling and Simulation
• Programming for Scientific Applications (Python, MATLAB or equivalent)
• Electives in applied probability, statistics, data analysis or advanced applied mathematics

The department normally offers both thesis and non-thesis tracks. The thesis route focuses on an original research project under faculty supervision and suits those considering doctoral study; the non-thesis route typically emphasises additional coursework and a capstone or project-oriented practicum. Students may take electives in allied departments such as engineering, computer science or statistics to tailor the degree to specific application domains.

Entry requirements

Applicants are expected to hold a bachelor’s degree in mathematics, applied mathematics, engineering, physics, computer science or a closely related discipline. A strong undergraduate record in core mathematical subjects—calculus, linear algebra, differential equations and elementary real analysis—is important. Some computational background or programming experience is normally required.

• Official transcripts from all post-secondary institutions attended.
• Evidence of satisfactory preparation in core undergraduate mathematics courses.
• A personal statement outlining academic interests and goals.
• Letters of recommendation, typically two or three, from academic or professional referees.
• International applicants must provide proof of English proficiency where required by the university.

Some applicants without a formal mathematics degree but with strong quantitative and programming preparation may be considered; such candidates may be asked to make up prerequisite coursework. GRE requirements, funding offers and additional documentation follow the university’s general graduate admissions policies.

Career prospects

Graduates with a master’s in computational mathematics develop skills that are in demand across many sectors. Typical career paths include roles as quantitative analysts, data scientists, computational scientists, numerical software developers, and modelling and simulation engineers. Employers span technology firms, engineering consultancies, finance and insurance companies, national and regional laboratories, and government agencies.

The degree also provides solid preparation for continued academic study at the doctoral level for students interested in research careers in applied mathematics, computational science or interdisciplinary areas that combine mathematics with engineering or the physical sciences.

Why study at University of South Alabama

The University of South Alabama’s Department of Mathematics and Statistics offers a focused graduate environment with opportunities for close faculty mentoring and hands-on computational work. Students can benefit from interdisciplinary connections across the College of Engineering and College of Arts and Sciences, allowing projects that address real-world problems in engineering, the sciences and industry.

Facilities include access to departmental computing resources and software used in research and coursework, and students often collaborate with faculty on applied research projects. The programme’s size and structure support personalised advising and flexibility in course selection, enabling students to align their studies with specific career objectives or research interests.