University of Alabama

What you'll study

The programme combines core mathematical theory with hands-on computational techniques. Students take advanced courses in numerical analysis and scientific computing alongside applied topics such as partial differential equations, computational linear algebra, optimisation and stochastic modelling. Coursework is complemented by practical training in scientific programming (e.g. MATLAB, Python, or compiled languages), high-performance computing concepts, and software tools for simulation and data analysis.

Typical modules and themes include:

• Numerical Analysis and Error Estimation
• Scientific Computing and Algorithm Design
• Computational Linear Algebra
• Numerical Methods for Differential Equations (ODEs and PDEs)
• Optimisation and Numerical Optimisation Methods
• Probability, Statistics and Stochastic Simulation for Computational Problems
• High-Performance and Parallel Computing Techniques
• Mathematical Modelling and Simulation Applications
• Seminar in Computational Mathematics and Research Project or Thesis

Students can typically choose between a thesis option, which emphasises original research and prepares for doctoral study, and a non-thesis option, which emphasises coursework and a project suited to industry or applied roles.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics, applied mathematics, engineering, physics, computer science or a closely related quantitative discipline, with a solid grounding in calculus, linear algebra and differential equations. Demonstrated competence in mathematical proof and at least one programming language is expected.

Applications normally include official academic transcripts, a personal statement outlining research or professional interests, and academic or professional references. International applicants must demonstrate English language proficiency through an approved test unless exempt. Specific GPA thresholds, prerequisite course requirements and documentation details are provided by the University of Alabama graduate admissions information pages.

Career prospects

Graduates with an MS in Computational Mathematics are well placed for roles that require quantitative modelling, algorithm development and computational expertise. Common career paths include:

• Data scientist or data analyst roles in technology, healthcare and government
• Numerical analyst, simulation engineer or computational scientist in engineering firms and national laboratories
• Quantitative analyst or model developer in finance and risk-management
• Software developer focused on scientific computing, high-performance computing or algorithm design
• Research positions and preparation for PhD study in applied mathematics, computational science or related fields

The programme’s blend of theory and practical coding skills is attractive to employers looking for staff who can both formulate mathematical models and implement efficient computational solutions.

Why study at University of Alabama

The University of Alabama offers a supportive graduate environment with faculty research in applied and computational mathematics, opportunities for interdisciplinary collaboration with engineering and computer science departments, and access to campus computing resources. Students benefit from seminar programmes, opportunities for teaching and research assistantships, and a campus community in Tuscaloosa that provides connections to regional industry and national research networks. The department emphasises mentorship, rigorous training in both analysis and computation, and preparation for careers in industry or further academic study.