Case Western Reserve University

What you'll study

The programme combines core theoretical coursework with applied and computational topics. Core modules typically cover real and functional analysis, partial differential equations, and numerical analysis. Applied courses available include mathematical modelling, scientific computing, optimization and control, stochastic processes and time-series analysis, dynamical systems, and computational methods for PDEs.

Students normally choose from electives that reflect links to neighbouring departments — for example courses in computational science, machine learning, statistics, mathematical finance or engineering applications. The curriculum emphasises hands‑on computation and data work, using programming languages and libraries common in research and industry (such as Python, MATLAB or C++), and includes a seminar series highlighting current research.

Programme formats commonly include a coursework-only option and a thesis or capstone project option. A typical capstone involves an extended modelling or computational project, often undertaken in collaboration with faculty from mathematics, engineering or other applied disciplines; students who choose the thesis route undertake an original research project under faculty supervision.

Entry requirements

Applicants should hold a recognised bachelor’s degree in mathematics, applied mathematics, physics, engineering, computer science or a closely related quantitative discipline. Successful candidates typically have completed undergraduate courses in calculus, linear algebra, differential equations, multivariable calculus, and introductory real analysis; coursework in probability, numerical methods or programming is strongly recommended.

Admissions decisions are based on the overall profile: academic transcripts, statement of purpose describing preparation and goals, letters of recommendation, and a résumé or CV. International applicants must demonstrate English language proficiency through approved tests unless exempt. Some applicants may be asked to submit GRE scores where required; specific requirements can vary and applicants should consult the department for current guidance.

Career prospects

Graduates enter a wide range of roles where quantitative and computational skills are in demand. Typical career paths include data scientist, quantitative analyst, software engineer with a numerical focus, operations researcher, modelling and simulation specialist, and roles in applied research within industry or national laboratories. The programme also prepares students for doctoral study in applied mathematics, computational science, statistics or related fields.

Case Western students benefit from connections to regional industry, healthcare institutions and research centres, which support internships and project collaborations that enhance employability in sectors such as finance, energy, engineering, healthcare analytics and technology.

Why study at Case Western Reserve University

Case Western Reserve University offers a compact, research-active mathematics department with strengths in analysis, numerical methods and interdisciplinary applications. Students have opportunities to work with faculty on applied problems and to collaborate across strong neighbouring schools of engineering, medicine and data science.

The university’s location in Cleveland provides access to industry partners, research hospitals and national laboratories, enabling applied project work and internship possibilities. Small class sizes and accessible faculty mentoring support tailored supervision for capstone projects or theses, while campus resources — computing facilities, libraries and a career centre — help students develop technical skills and prepare for professional transitions.