Swansea University

What you'll study

This degree emphasises mathematical methods, numerical analysis and modelling applied to problems in science, engineering and industry. In the early years you build a foundation in calculus, linear algebra, differential equations, probability and statistics, and introduce computational tools such as MATLAB, Python and numerical linear algebra. Core topics typically include:

• Calculus and vector analysis
• Linear algebra and matrix computations
• Ordinary and partial differential equations
• Numerical analysis and scientific computing
• Probability theory and statistical modelling
• Mathematical modelling of physical and biological systems
• Computational methods: finite differences, finite elements and optimisation

In later stages you take more specialised modules and project-based work. Options commonly offered include fluid dynamics, mathematical biology, dynamical systems, stochastic processes, data analysis and machine learning, inverse problems and optimisation, and high-performance computing for large-scale simulations. A substantial final-year individual project gives you the opportunity to apply analytical and computational skills to a research-style problem, often aligned with departmental research themes or an external placement partner.

Entry requirements

Typical entry requires strong grades in mathematics at A-level (or equivalent). Applicants are expected to demonstrate competence in pure and applied mathematics; further mathematics is advantageous but not always essential. Universities normally consider a combination of academic qualifications, predicted grades/previous performance, and any contextual factors. International applicants should provide recognised equivalent qualifications and evidence of English language proficiency where required. Admissions tutors may also consider personal statements, references and any relevant experience such as programming or quantitative work.

Career prospects

Graduates from applied mathematics programmes move into a wide range of careers that value strong analytical and computational skills. Common destinations include:

• Quantitative analystroles in finance and insurance
• Data science, analytics and machine learning positions in technology and consulting
• Engineering and simulation roles in aerospace, energy and manufacturing
• Research and development in modelling teams across industry and government
• Further study at MSc or PhD level in applied mathematics, statistics, computational science or related disciplines

The course also prepares graduates for roles in software development, risk analysis, environmental modelling and public-sector technical positions. Practical project work and industrial links at Swansea support employability by helping students build a portfolio of computational and modelling experience.

Why study at Swansea University

Swansea's Department of Mathematics provides a strong combination of theoretical and computational expertise with active research groups in areas such as fluid dynamics, computational mathematics, mathematical biology, statistics and data science. Students benefit from access to modern computing facilities and software, opportunities to collaborate on research projects, and links with regional and national industry partners for placements and projects.

The university's campus environment and support services are geared towards helping undergraduates develop both subject knowledge and transferable skills. Teaching typically blends lectures, small-group problem classes, practical computing sessions and supervised project work, giving applied mathematics students the tools to tackle complex, real-world problems.