Purdue University

What you'll study

The Computational Mathematics option emphasises theory and algorithms for solving continuous and discrete problems on computers. You will study core topics such as numerical analysis, numerical linear algebra, scientific computing, partial differential equations, optimisation and uncertainty quantification. Courses typically cover topics like finite element and finite difference methods, spectral methods, high-performance computing for numerical algorithms, iterative solvers and preconditioning, numerical methods for stochastic models, and computational inverse problems.

Programme structure usually includes advanced coursework, applied project work and a choice of a research thesis or a non-thesis (project/coursework) pathway. Students design a course plan in consultation with a faculty advisor that balances rigorous mathematical foundations with hands-on computational experience, including programming and use of parallel computing environments. Electives draw from related departments (for example, computer science, engineering or statistics) to support interdisciplinary applications.

Entry requirements

Applicants are expected to hold a bachelor’s degree in mathematics, applied mathematics, computational science, engineering, physics or a closely related field, with substantial coursework in undergraduate real analysis, linear algebra and multivariable calculus. Additional recommended preparation includes courses in differential equations, numerical analysis, probability/statistics and programming experience (e.g. Python, C/C++, MATLAB).

Typical application materials include official academic transcripts, a statement of purpose describing research and career objectives, letters of recommendation from academic or professional referees, and a CV. International applicants must demonstrate English proficiency; acceptable scores and requirements are set by the university. Standardised tests (such as the GRE) may be optional or considered on a case-by-case basis—check the department's admissions page for current guidance.

Career prospects

Graduates of the Computational Mathematics pathway go on to a variety of careers in industry, government and academia. Common roles include computational scientist, numerical analyst, data scientist, quantitative analyst, modelling and simulation engineer, software developer for scientific applications, and research staff in national laboratories. Many students continue to PhD programmes in mathematics, applied mathematics, computational science or related disciplines. The strong computational and programming skills developed also transfer well to technology and finance sectors, as well as interdisciplinary research teams in engineering and the physical sciences.

Why study at Purdue University

Purdue's Department of Mathematics has a strong tradition in both pure and applied mathematics, with faculty active in numerical analysis, scientific computing and interdisciplinary applications. The university's broad engineering and computer science strengths create ready opportunities for collaboration on applied research projects. Students benefit from access to campus research computing resources and opportunities to work on problems that require high-performance computing and advanced numerical methods.

Located in a major research university environment, the programme provides both rigorous mathematical training and practical computational experience, supported by faculty mentorship and connections to research centres and industry partners. This combination prepares graduates for technical careers and further academic study in computational and applied mathematics.