Georgia Institute of Technology

What you'll study

The Master of Science in Applied Mathematics emphasises both rigorous mathematical foundations and practical computational methods. Core topics commonly covered include real and functional analysis, numerical analysis and scientific computing, partial differential equations and dynamical systems, optimisation, probability and stochastic processes, and mathematical modelling. Students typically choose from a range of electives to tailor their programme — examples include numerical linear algebra, computational methods for PDEs, machine learning for mathematical modelling, statistical inference, inverse problems, and multiphysics simulation.

The programme is offered with flexible completion options, including thesis (research) and non-thesis (coursework or project) tracks. The thesis route focuses on original research under faculty supervision and is appropriate for students preparing for doctoral study. The non-thesis route emphasises advanced coursework and a substantial project or practicum, often involving applied problems drawn from engineering, data science, finance, or industry collaborations.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in mathematics, applied mathematics, statistics, engineering, physics, computer science or a closely related quantitative discipline. Typical preparation includes coursework in calculus, linear algebra, multivariable analysis, differential equations and basic probability or statistics. Strong programming experience and familiarity with numerical computation are highly desirable.

Admission decisions are based on the overall academic record, letters of recommendation, a statement of purpose outlining research or career objectives, and transcripts. International applicants must meet English language proficiency requirements. Where required, applicants may also submit GRE scores, but expectations vary by year and by the School of Mathematics’ stated admissions guidance.

Career prospects

Graduates of the Applied Mathematics programme move into a wide range of roles that require quantitative modelling and computational skill. Common career paths include data scientist or analyst, quantitative researcher in finance, modelling and simulation engineer, software engineer with a numerical focus, operations research analyst, and roles in computational biology, energy systems, and aerospace modelling.

The degree also provides a strong foundation for students who choose to continue to PhD programmes in applied mathematics, computational science, engineering, statistics or related disciplines. Connection with industry partners and research centres at Georgia Tech can lead to internships and collaborative projects that help transition students into technical roles in both established companies and technology start-ups.

Why study at Georgia Institute of Technology

Georgia Tech is known for its strong emphasis on computation, engineering and interdisciplinary research. The School of Mathematics collaborates closely with departments across the College of Engineering, the College of Computing and affiliated research institutes, providing opportunities to work on practical problems with faculty in numerical analysis, scientific computing, optimisation and stochastic modelling.

Students benefit from access to high-performance computing resources, applied research centres and a large industry ecosystem in the Atlanta region. Faculty expertise spans theoretical and applied areas, enabling thesis and project topics that address real-world challenges. The programme’s combination of rigorous mathematics and applied computation makes it particularly well suited to students aiming for technically demanding careers or further research training.