Oregon State University

What you'll study

This programme emphasises mathematical foundations for computation together with applied numerical techniques. Typical core topics include numerical analysis, scientific computing, numerical linear algebra, and numerical solution of ordinary and partial differential equations. You will also study complementary subjects such as optimisation, scientific machine learning, probability and statistics, algorithms, and mathematical modelling for physical systems.

Students can usually follow a thesis (research) option or a non-thesis (coursework/capstone) option. A typical progression mixes advanced coursework, a computational project or thesis, and seminars. Coursework focuses on theory and implementation: error analysis and stability of algorithms, discretisation techniques, spectral and finite element methods, time-integration schemes, and parallel and GPU computing for large-scale problems. Electives allow you to tailor the degree toward applications in fluid dynamics, materials, geosciences, bioinformatics or data science.

Learning is hands-on: assignments and projects commonly require implementation of algorithms in languages and environments used in research and industry (for example Python, MATLAB, C++, or parallel programming frameworks). Students have opportunities to work on interdisciplinary research with faculty in engineering, physical sciences and computing.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics, applied mathematics, statistics, computer science, engineering or a closely related quantitative discipline. A solid background in calculus, linear algebra, differential equations, and introductory real analysis or advanced calculus is expected, together with experience in programming and numerical methods.

Typical application materials include official transcripts, a statement of purpose describing mathematical and computational experience and objectives, curriculum vitae, and two or three letters of recommendation from academic or professional referees. Admissions decisions consider the overall academic record and preparation for graduate-level mathematics. Some applicants with strong quantitative and programming experience but non‑traditional backgrounds may be considered.

International applicants must demonstrate English language proficiency in accordance with the university’s graduate admissions policy. Additional departmental requirements or recommendations (for example preparation in specific advanced undergraduate courses) may apply; contact the department for programme-specific advice.

Career prospects

Graduates with a master’s in computational mathematics move into a variety of careers in industry, government and academia. Common roles include:

• Computational scientist or numerical analyst working on modelling and simulation for engineering, energy, environmental science or defence sectors.
• Data scientist, quantitative analyst or machine learning engineer applying mathematical modelling and algorithmic skills to large datasets.
• Software developer specialising in scientific software, high-performance computing or algorithm implementation.
• Research assistant or doctoral candidate in mathematics, applied mathematics or computational science.
• Technical roles in finance, technology and manufacturing that require strong quantitative and computational expertise.

The programme’s emphasis on practical implementation and interdisciplinary collaboration also supports internships and research placements with regional technology companies, national laboratories and research centres.

Why study at Oregon State University

Oregon State’s mathematics programme is located within a large research university with strong connections across engineering, physical and life sciences. The department has active research groups in numerical analysis, scientific computing and applied mathematics, giving students access to supervisors working on contemporary computational problems.

Students benefit from on-campus computing resources and opportunities for interdisciplinary projects with neighbouring departments and research centres. The department’s culture emphasises collaborative research and hands-on training, preparing graduates for both industry roles and further academic study. Faculty-led projects, seminars and partnerships with regional companies and national research labs create pathways to applied experience and employment after graduation.