Florida State University

What you'll study

The programme emphasises rigorous analysis and practical computation. Core topics typically include partial differential equations, numerical analysis and scientific computing, dynamical systems and stability, applied linear and functional analysis, and mathematical modelling methods. Elective courses allow you to specialise in areas such as computational optimisation, stochastic processes and applied probability, data analysis and numerical linear algebra, or applications in fluid dynamics, materials, biology and finance.

Students choose between thesis and non‑thesis options. The thesis route centres on a supervised research project and original written thesis; the non‑thesis route focuses on advanced coursework and may include a practicum or comprehensive examination. The degree is delivered through seminars, lecture courses, computational laboratory work and one‑to‑one research mentorship, with emphasis on developing programming skills, parallel computation, and the use of modern mathematical software.

Entry requirements

• A bachelor’s degree in mathematics or a closely related quantitative discipline (for example physics, engineering, computer science or statistics) from an accredited institution.
• Transcripts demonstrating strong preparation in calculus, linear algebra, differential equations and at least one proof‑based course; prior coursework in numerical analysis, real analysis or programming is advantageous.
• A statement of purpose describing academic background, research interests and career goals, and typically two to three academic or professional letters of recommendation.
• International applicants must demonstrate English proficiency through an accepted test unless exempt by institutional rules. Specific test score expectations and additional materials may be available on the department’s graduate admissions page.
• Some applicants with exceptional quantitative experience but a non‑standard background may be admitted with conditional requirements to address any foundational gaps.

Career prospects

Graduates move into a wide range of technical and research roles. Common paths include quantitative analyst or modeller in finance, data scientist and machine learning engineer, computational scientist in national labs and research institutes, software developer focusing on scientific computing, and applied mathematician or consultant in engineering and technology companies. Many students use the master’s as preparation for doctoral study in applied mathematics, computational science, engineering or related disciplines.

The programme’s combination of theoretical training and computational practice is particularly valued where advanced numerical methods and mathematical modelling are required for decision making, simulation and optimisation across industry, government and academia.

Why study at Florida State University

Florida State University offers a supportive research environment with faculty working across classical and contemporary areas of applied mathematics. Students benefit from interdisciplinary collaborations with engineering, physics, biology and statistics, access to high‑performance computing resources and opportunities to contribute to active research projects. FSU’s partnerships with regional research centres and national facilities provide avenues for internships and applied research experience.

The department keeps class sizes at the graduate level conducive to close mentorship, and seminars and colloquia connect students with visiting researchers and local industry. The campus setting in Tallahassee offers a balance of academic life and connections to state agencies and regional employers, supporting both career development and further academic pursuits.