Clark University

What you'll study

The programme combines core graduate-level mathematics with intensive training in numerical methods, scientific computing and software development for large-scale problems. Typical topics include numerical analysis, numerical linear algebra, scientific computing, numerical solution of ordinary and partial differential equations, optimisation and computational methods for inverse problems. Coursework commonly covers probability and statistics for computation, computational geometry, and applied dynamical systems.

Students gain practical programming and software-engineering experience using languages and tools common in computational science (for example Python, MATLAB, C/C++ and parallel programming frameworks), and are exposed to high-performance computing techniques and reproducible computational workflows.

Study pathways usually include a combination of taught courses, a computational practicum or project, and an option to complete a research thesis under faculty supervision. Seminar series and reading courses allow students to explore specialised topics such as machine learning for scientific data, uncertainty quantification, or scientific visualisation.

Entry requirements

Applicants are expected to hold a bachelor's degree in mathematics, applied mathematics, computer science, engineering, physics or a closely related quantitative discipline. A strong foundation in undergraduate real analysis, linear algebra, calculus and introductory differential equations is normally required.

Typical application materials include official transcripts, a statement of purpose that describes research or professional interests in computational mathematics, and two or three academic or professional references. Evidence of programming experience and coursework in numerical methods or scientific computing strengthens an application. International applicants must meet the university's English-language proficiency requirements.

Career prospects

Graduates are prepared for roles that demand both mathematical rigour and computational fluency. Common career paths include data scientist or analyst, quantitative developer or quantitative analyst in finance, software engineer for scientific applications, computational scientist in industry or national laboratories, and technical roles in engineering firms. The programme also provides a solid foundation for students who choose to continue to doctoral study in applied mathematics, computational science or related fields.

Alumni work across sectors such as technology, finance, healthcare, energy, and government research agencies, where they apply numerical modelling, simulation, optimisation and data-driven methods to complex problems.

Why study at Clark University

Clark University offers a personalised graduate experience with relatively small class sizes and close mentoring from faculty who are active in both theoretical and applied computational research. The university emphasizes interdisciplinary collaboration, allowing students to work with colleagues in computer science, earth and environmental sciences, physics and engineering on cross-cutting computational projects.

Students benefit from access to campus computing resources and opportunities to participate in project-based learning, internships and partnerships with regional research institutions and industry. Clark's location in Worcester gives convenient access to the broader New England research and technology ecosystem for internships and employment exploration.

Overall, the programme is well suited to students seeking a balance of rigorous mathematical training and hands-on computational skills that translate directly into research and industry roles.