Lesley University

What you'll study

This programme combines rigorous mathematical foundations with practical computational techniques. Core topics typically include numerical analysis and algorithms, scientific computing, numerical linear algebra, computational methods for differential equations, optimisation and numerical optimisation, and probability and statistics for computation. Students also study modern programming and software practices relevant to mathematics, such as high-level scripting (Python, MATLAB) and performance-aware code, and gain experience with high-performance computing concepts.

The course is usually structured around a set of core modules, elective modules that allow specialisation (for example in machine learning, computational fluid dynamics, or financial mathematics), and a capstone experience. The capstone may take the form of a thesis, a substantial project involving original numerical experimentation or software development, or an industry-linked practicum where students apply computational methods to a real problem.

• Numerical Analysis and Error Estimation
• Computational Linear Algebra
• Numerical Methods for Ordinary and Partial Differential Equations
• Scientific Programming and Software Engineering for Mathematicians
• Optimisation and Computational Optimisation
• Statistical Computing and Data Analysis
• High-Performance and Parallel Computing (concepts and applications)
• Project/Thesis or Applied Capstone

Entry requirements

Applicants are normally expected to hold a recognised undergraduate degree in mathematics, applied mathematics, physics, engineering, computer science or a closely related discipline. Typical preparation includes coursework in calculus, linear algebra, differential equations and basic programming. Some experience with numerical methods or scientific computing is advantageous but not always mandatory.

To apply you will generally need to submit an academic transcript, a personal statement outlining your interests and background in computational mathematics, and a CV or résumé. Two academic or professional references are commonly requested. Where an applicant’s background is missing particular prerequisites, the admissions team may recommend or require preparatory modules to be completed.

Career prospects

Graduates with a master’s in computational mathematics have a wide range of career opportunities across industry, government and academia. Common roles include data scientist, quantitative analyst, computational scientist, numerical software developer, simulation engineer and applied researcher. Employers are found in sectors such as finance, technology, engineering, energy, healthcare and defence, as well as research laboratories and consultancies.

Many students also use the master’s as preparation for doctoral study in applied mathematics, computational science or related fields. The programme’s emphasis on programming, numerical methods and project experience helps graduates demonstrate practical skills sought by employers and research supervisors alike.

Why study at Lesley University

Lesley University offers a student-centred learning environment with relatively small class sizes and close faculty mentorship, which can be especially valuable in mathematically intensive and project-based study. The university’s location in the Boston–Cambridge area provides convenient access to a rich ecosystem of technology companies, research institutions and start-ups for networking, internships and collaboration.

Students benefit from interdisciplinary opportunities across departments, access to computing facilities and support for applied projects, and a curriculum designed to balance theoretical understanding with practical computing skills. The programme is suited to students who value personalised instruction and hands-on experience in computational problem-solving.