Syracuse University

What you'll study

The Computational Mathematics pathway combines rigorous theory with practical computing. Core topics typically include numerical analysis, numerical linear algebra, approximation theory, and the numerical solution of ordinary and partial differential equations. Students learn algorithm design and analysis, high-performance computing practices, and computational methods for optimisation and inverse problems.

• Core courses — numerical methods, computational linear algebra, error analysis and scientific computing.
• Advanced topics — finite element and finite difference methods for PDEs, spectral methods, computational optimisation, stochastic simulation and uncertainty quantification.
• Programming and tools — training in scientific programming (Python/Julia/Matlab/C++), parallel computing, and use of libraries for numerical linear algebra and simulation.
• Electives — machine learning for scientific computing, computational statistics, data assimilation, computational geometry, or domain-specific courses in physics/engineering/finance.
• Capstone options — a supervised research thesis or a project-based practicum that applies computational techniques to a real problem, often in collaboration with faculty or external partners.

Entry requirements

Applicants are expected to hold a bachelor’s degree in mathematics, applied mathematics, computer science, engineering, physics or another quantitatively oriented field. Strong preparation in calculus, linear algebra, differential equations and basic programming is required.

• A complete academic transcript showing relevant quantitative coursework.
• Letters of recommendation that address your mathematical and computational potential.
• A statement of purpose outlining your interests in computational mathematics and career or research goals.
• A current CV/resume highlighting relevant projects, internships or research.
• International applicants must demonstrate English language proficiency by standard tests unless exempt; specific test requirements are provided by the university.

Career prospects

Graduates with a master’s in Computational Mathematics are prepared for a wide range of technical careers. Employers value the mix of rigorous mathematical reasoning and practical computing experience.

• Data scientist, machine learning engineer or analytics specialist in technology and start-ups.
• Quantitative analyst or modeller in finance, insurance and risk management.
• Computational scientist or numerical analyst in engineering firms, government laboratories and research institutes.
• Software engineer focused on high-performance computing, simulation, or algorithm development.
• Further academic study toward a PhD in mathematics, computational science or related fields.

Why study at Syracuse University

Syracuse University offers a mathematics programme with personalised attention from faculty who work at the interface of analysis and computation. The department emphasises collaborative research and provides opportunities to work with researchers in engineering, computer science and physical sciences. Students benefit from access to institutional computing resources and local industry and laboratory collaborations that support project-based learning and internships.

The programme’s location and the university’s professional development services also support networking and career planning, helping students transition into roles across academia, industry and government.