Simmons University

What you'll study

This programme emphasises core mathematical foundations alongside hands-on computational techniques. Typical modules focus on numerical analysis and scientific computing, applied linear algebra, numerical solution of differential equations, optimisation and inverse problems, and computational methods for partial differential equations. Students also study probability and statistics for computational work, algorithms and complexity, and gain practical experience in programming languages and tools commonly used in scientific computing (for example Python, MATLAB or equivalent).

Coursework usually combines lectures, problem-solving seminars and laboratory sessions where students implement algorithms and run simulations. Many programmes include a capstone project or master's thesis, in which students apply computational methods to a substantive problem in applied mathematics, physics, engineering, biology, finance or a related field. Electives commonly allow specialisation in areas such as data modelling, machine learning for scientific applications, high-performance computing, or mathematical modelling of physical systems.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in mathematics, applied mathematics, statistics, computer science, engineering or a closely related discipline with substantial quantitative content. Typical preparation includes multivariable calculus, linear algebra, differential equations and an introductory course in programming.

• Official transcripts demonstrating academic preparation in mathematics and computing.
• A personal statement outlining academic interests, relevant experience and reasons for pursuing computational mathematics.
• Academic references from instructors or supervisors who can speak to mathematical and analytical ability.
• Some practical computing experience or coursework in programming is expected; applicants without formal computing courses may be asked to demonstrate equivalent experience.

Career prospects

Graduates with a master’s in computational mathematics are prepared for quantitative and technical roles across many sectors. Common career paths include positions as data scientists and analysts, quantitative analysts in finance, algorithm developers, simulation and modelling specialists, scientific software engineers, and research associates in industry or academia. The programme’s computational emphasis also provides a strong foundation for further doctoral study in applied mathematics, computer science or engineering.

Because the curriculum stresses practical coding, numerical methods and problem-solving, alumni are competitive for roles that require translating mathematical models into implementable software and interpreting computational results for decision-making.

Why study at Simmons University

Simmons University offers a collaborative learning environment with small class sizes that allow close interaction with faculty. Located in the Boston area, the university provides access to a broad regional ecosystem of technology companies, research institutions and healthcare organisations, which can support internships, collaborations and applied projects.

The mathematics and statistics faculty at Simmons typically combine research and applied experience, and the university emphasises interdisciplinary work — enabling students to apply computational mathematics in areas such as data science, public health, environmental modelling and finance. Dedicated career services and on-campus resources help students identify internships and employment opportunities while completing their degree.