Loughborough University

What you'll study

The programme combines advanced applied mathematics, numerical computation and practical project work. You will study core topics in mathematical modelling and choose from specialised modules that reflect modern industrial needs. Teaching blends lectures, computer-based laboratory classes and a substantial independent project or dissertation, often carried out with an industrial partner.

• Core themes: formulation of mathematical models, nondimensionalisation and scaling, analysis of differential equations, and model validation and verification.
• Computational methods: numerical methods for ODEs and PDEs, finite difference/finite element ideas, spectral methods, and efficient algorithm implementation.
• Uncertainty and data: uncertainty quantification, Bayesian inference, statistical modelling, data assimilation and model calibration.
• Optimisation and control: deterministic and stochastic optimisation, inverse problems and optimal control methods used in industrial design and process control.
• Stochastic and dynamical systems: stochastic processes, random fields, multiscale dynamics and bifurcation analysis for complex systems.
• Practical project: a major individual dissertation or industrial project that tests modelling, simulation and communication skills on a real problem. Projects can be campus-based or run in collaboration with companies from sectors such as manufacturing, energy, transport, finance and life sciences.

Structure: the programme typically comprises taught modules followed by a research/dissertation component. It is offered full-time (typically one year) and may be available part-time or with flexible study arrangements.

Entry requirements

Applicants should normally hold a good honours degree (UK 2:1 or international equivalent) in mathematics, applied mathematics, engineering, physics, computer science or a closely related discipline. Candidates with a lower second-class degree (2:2) and demonstrable industrial experience or strong quantitative skills may also be considered.

Acceptable backgrounds include substantial experience in calculus, linear algebra, differential equations, and introductory probability/statistics. Programming experience (for example in Python, MATLAB, C/C++ or similar) is highly desirable.

International applicants must meet equivalent academic standards and satisfy the University's English language requirements; standard offers typically require proof of proficiency via recognised tests or previously taught instruction in English.

Career prospects

Graduates leave prepared for quantitative roles in industry, government and research. Typical career paths include:

• Modelling and simulation engineer in manufacturing, aerospace, automotive or energy sectors
• Data scientist, statistical modeller or machine learning engineer in finance, technology and consulting
• Computational scientist in research institutions and national laboratories
• Systems engineer, optimisation specialist or control engineer working on process design and operations
• Further academic study such as PhD research in applied mathematics, computational science or engineering

The practical project element and links with industry help graduates demonstrate applied experience sought by employers in R&D, product development, and technical consultancy.

Why study at Loughborough University

Loughborough has a strong reputation for engineering, mathematical sciences and close industry engagement. The Department provides concentrated expertise in applied and computational mathematics, with staff active in numerical analysis, uncertainty quantification, optimisation and mathematical modelling for industrial applications.

Students benefit from on-campus computing facilities and access to high-performance computing resources, hands-on laboratory and modelling support, and a compact campus with strong student services. The University’s established relationships with regional, national and international companies provide opportunities for industrial projects, placements and collaborative research.

Support for employability, including career counselling and connections with graduate employers, complements the technical training so that graduates are ready to step into quantitative roles across sectors or to continue to doctoral study.