Computer Science and Mathematics

Computer science and mathematics together form one of the most intellectually powerful combinations in the undergraduate curriculum, pairing the formal study of computation and software with the rigorous analytical thinking of mathematics. Many of the most important ideas in computer science, including the theory of algorithms, cryptography, machine learning, and computer graphics, are deeply mathematical in character, and studying both disciplines together gives you the ability to engage with these ideas at the level of genuine understanding rather than merely technical application. Conversely, computing provides mathematicians with powerful tools for modelling, simulation, and visualisation.

At Loughborough University this three-year full-time programme is explicitly designed around the premise that many real-world problems are best approached with a combination of mathematical and computational techniques. You will study core computer science topics including algorithms, data structures, software engineering, and programming alongside the mathematical foundations of analysis, algebra, probability, and statistics, and you will engage with the intersection of the two fields in areas such as computational mathematics, mathematical optimisation, and the mathematical underpinnings of machine learning and data science.

Graduates from computer science and mathematics programmes are exceptionally well placed for careers in a wide range of technical and analytical roles. Technology companies, financial services, defence, cybersecurity, data science, consultancy, and academic research are all major employers. The combination of rigorous mathematical thinking and software development skill is particularly valued in roles that involve building models, designing algorithms, or developing data-intensive systems.

Many graduates also pursue postgraduate study in computer science, mathematics, or a specialist applied area such as machine learning or operations research. The degree provides a particularly strong foundation for doctoral research at the intersection of the two disciplines.