Colorado State University

What you'll study

This programme combines rigorous graduate-level mathematics with practical training in numerical methods and high-performance computation. Typical course topics include numerical analysis, numerical linear algebra, computational methods for partial differential equations, scientific computing, optimisation, and applied probability and statistics. Students also study supporting areas such as programming for scientific computing, parallel and distributed computing, and mathematical modelling.

The degree is offered with options that accommodate both research-oriented and professionally oriented students. Many students follow a thesis route involving original research under a faculty advisor, while others take a coursework or project option that emphasises advanced coursework and a substantial computational project or practicum. Coursework typically includes a mix of core graduate mathematics classes and elective seminars or specialised computational courses.

• Numerical Analysis and Approximation Theory
• Numerical Linear Algebra
• Computational Partial Differential Equations
• Scientific Computing and Software for Numerical Methods
• Optimisation and Inverse Problems
• Parallel Computing and High-Performance Computing
• Mathematical Modelling and Applied Dynamical Systems

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in mathematics, applied mathematics, computer science, engineering or a closely related field, with substantial coursework in calculus, linear algebra and undergraduate analysis. Prior exposure to numerical methods and programming (for example in MATLAB, Python or C/C++) is highly desirable.

Typical application components include official transcripts, a statement of purpose describing research or career goals, two to three letters of recommendation, and a current curriculum vitae or résumé. International applicants must meet Colorado State University’s English language proficiency requirements and provide the required documentation. Some applicants may be advised to take preparatory or bridge courses if their undergraduate training lacks required prerequisites.

Career prospects

Graduates with a master’s in Computational Mathematics are well placed for careers that require advanced quantitative and computational skills. Common career paths include roles as data scientists, quantitative analysts, computational scientists or engineers, software developers for scientific and technical applications, and roles in modelling and simulation in sectors such as energy, aerospace, finance, defence, and environmental science.

The degree also provides a solid foundation for further research: many graduates continue to PhD programmes in applied mathematics, computational science, statistics or engineering, or take research positions in national laboratories and industry R&D groups.

Why study at Colorado State University

Colorado State University’s mathematics department offers a balance of theoretical strength and applied, computation-focused research. Students benefit from faculty active in numerical analysis, scientific computing and computational modelling, and have access to university research computing resources for large-scale simulations and parallel computing work.

The university’s collaborative environment connects mathematics students with complementary centres and departments — such as engineering, atmospheric science and computer science — creating opportunities for interdisciplinary projects and internships. The Fort Collins campus location and CSU’s industry and national-laboratory links provide additional options for applied projects, practicum experiences and employment connections in sectors that rely on high-performance computational skills.