University of Lancaster

What you'll study

This four‑year integrated master's combines core mathematical theory with core and optional computer science modules. In early years you build solid foundations in calculus, linear algebra, proof and discrete mathematics alongside introductory programming and data structures. Later years progress to advanced analysis, algebra, probability and statistics, numerical methods and optimisation, together with algorithm design, complexity theory, databases, software engineering and machine learning.

• Typical first‑year: Calculus and analysis, linear algebra, discrete mathematics, introduction to programming and algorithms, mathematical reasoning.
• Typical second‑year: Real analysis, abstract algebra, probability and statistics, data structures and algorithms, object‑oriented programming, numerical methods.
• Typical third‑year: Advanced probability and stochastic processes, partial differential equations, optimisation, complexity theory, databases, compiler concepts or formal methods, plus optional specialised modules such as cryptography or computational geometry.
• Fourth (MSci) year: Research methods, advanced electives aligned with staff research, and a substantial independent research project or dissertation that integrates mathematics and computing.

Students can usually choose optional modules to emphasise applied or theoretical strands, and there are opportunities for undertaking an industrial placement or a summer research project with a supervisor. Teaching is a mix of lectures, small‑group tutorials, practical laboratory sessions and project work.

Entry requirements

Entry is normally at undergraduate level for the four‑year integrated MSci. Typical applicants will have strong qualifications in mathematics and related subjects. Acceptable qualifications include A‑levels, the International Baccalaureate or recognised international equivalents, with a high standard in mathematics (and often a second STEM subject).

Specific offers are set by the University and will vary by qualification; mature applicants and those with non‑traditional qualifications are considered on the strength of academic background and relevant experience. Applicants who already hold a university degree in a closely related subject should consult the admissions team about possible advanced entry or conversion routes.

Career prospects

Graduates combine quantitative reasoning with software and systems skills, making them attractive to a wide range of employers. Career paths commonly taken include:

• Software engineer and systems developer roles in technology companies.
• Data scientist, machine learning engineer or data analyst positions across industry sectors.
• Quantitative analyst or modelling roles in finance, insurance and fintech.
• Research roles in mathematics, theoretical computer science or applied computation; progression to PhD study.
• Cybersecurity, cryptography and IT consultancy roles that draw on both mathematical and computing expertise.

The University’s Careers Service and departmental employer links support placements, internships and graduate recruitment activities.

Why study at University of Lancaster

Lancaster offers a collaborative environment where the School of Mathematics & Statistics and the Department of Computing work closely to deliver cross‑disciplinary programmes. Students benefit from small‑group teaching, accessible academic staff, and opportunities to get involved in research projects. The curriculum emphasises both theory and practical skills with dedicated computing labs, mathematical computing software and project supervision that prepares students for workplace practice or further study.

The campus setting provides concentrated student services and a central careers team with strong employer engagement, while a range of student societies and departmental activities give practical experience and networking opportunities that complement the degree.