Florida International University

What you'll study

This programme combines core mathematical theory with computational techniques used to model and solve complex problems. Core subjects typically include multivariable calculus, linear algebra, real analysis, differential equations and probability and statistics. Computational and applied modules emphasise numerical analysis, scientific computing, numerical linear algebra, numerical methods for differential equations, optimisation, and computational modelling.

Students learn practical tools and languages commonly used in industry and research, for example Python, MATLAB, and C/C++ as well as software packages for statistics and visualization. Coursework frequently includes laboratory or project components where you implement algorithms, carry out simulations, and validate models against data.

• Fundamental mathematics: Calculus sequence, Linear Algebra, Real Analysis
• Computational core: Numerical Analysis, Scientific Computing, Numerical Linear Algebra
• Applied topics: Differential Equations, Optimisation, Probability and Statistics, Mathematical Modelling
• Computer science fundamentals: Data Structures, Algorithms, Programming for Scientists
• Capstone/project: A senior project or practicum involving algorithm implementation, simulation, or collaboration with faculty on research

Electives allow specialisation toward areas such as data science, computational finance, mathematical biology, or high-performance computing. Undergraduates are encouraged to take modules from related departments (computer science, engineering, statistics) and to participate in research, internships or co‑op placements.

Entry requirements

Applicants should have a strong background in high‑school mathematics, including algebra, precalculus and preferably calculus. Admission typically considers your secondary-school transcript, preparation in mathematics, and any standardised test information if submitted. FIU assesses readiness for university calculus and may require placement testing for incoming students.

Additional supporting materials can include a personal statement describing mathematical interests, and letters of recommendation particularly from mathematics teachers. Transfer applicants should provide college transcripts showing completion of introductory calculus and college‑level mathematics where relevant. International applicants must meet FIU's English proficiency expectations.

Career prospects

Graduates with a computational mathematics degree are sought after for roles that require quantitative analysis, mathematical modelling and programming skills. Typical career paths include:

• Data scientist or data analyst – analysing data, building predictive models and deploying algorithms
• Software engineer or developer – focusing on scientific, numerical or high‑performance applications
• Quantitative analyst/financial modeller – constructing and validating models used in finance and risk management
• Operations researcher/optimisation specialist – designing efficient systems and decision‑support tools
• Scientific programmer or computational scientist – supporting research in engineering, physics, biology or climate modelling

Many graduates also continue to postgraduate study (master’s or PhD) in applied mathematics, computational science, statistics, computer science or engineering. Undergraduate research, internships and ties to local industry improve employability and provide practical experience.

Why study at Florida International University

FIU offers a diverse, research-active environment with access to computing resources and opportunities to collaborate across science, engineering and business faculties. The university’s location in Miami supports connections to regional technology, finance and healthcare sectors, which can be useful for internships and applied projects.

Undergraduates benefit from opportunities for supervised research with faculty, dedicated computing labs, and career services that assist with internship and job placement. The programme’s flexibility permits interdisciplinary study, enabling students to tailor their degree toward data science, engineering applications or graduate study.