University of Leicester

What you'll study

This degree integrates traditional physics topics with modules in computational methods and data science. In early stages you build firm foundations in mechanics, electromagnetism, waves, thermal physics and quantum ideas alongside calculus and linear algebra. Practical laboratory work develops experimental technique, error analysis and scientific reporting.

Computational and data-focused topics run through the programme: programming (typically Python), numerical methods, probability and statistics, databases and data visualisation. Intermediate modules introduce computational physics, statistical modelling and data structures. In the final year you choose advanced physics options such as condensed matter, particle or astrophysics together with higher-level data science modules covering machine learning, Bayesian inference, large-scale data analysis and optimisation. The degree culminates in a substantial research or project dissertation that typically combines a physics problem with data-driven methodology.

• Core physics modules: classical mechanics, electromagnetism, quantum mechanics, thermodynamics and waves
• Mathematics and computational modules: calculus, linear algebra, differential equations, numerical methods
• Data science modules: programming for scientists, probability and statistics, machine learning, data visualisation and databases
• Laboratory and research skills: practical experiments, uncertainty analysis, scientific communication
• Final-year project: independent research or industry-linked project combining physics and data analysis

Entry requirements

Typical entry is via A-levels, with an offer commonly requiring strong grades including Mathematics and/or Physics. Alternative qualifications are welcomed: the International Baccalaureate, BTEC qualifications (usually alongside A-level Mathematics), Access to HE and other recognised international equivalents are considered. Applicants should have a demonstrable aptitude for mathematics and computing and for courses taught in English, an appropriate English language qualification is required if English is not your first language.

Applicants with relevant industrial experience, coding background or prior study in statistics or computing are also encouraged to apply; the admissions team can advise on specific qualification combinations and required subject content.

Career prospects

Graduates leave prepared for roles that demand quantitative analysis, computational skills and physical reasoning. Typical career pathways include data scientist, machine learning engineer, quantitative analyst in finance, software developer, research scientist in academia or industry, and roles in engineering and technology firms. The combination of physics and data science is also good preparation for further study such as MSc or PhD research in physics, applied mathematics, or data science, and for technical roles in sectors such as space, energy, healthcare and scientific instrumentation. Graduates may also move into STEM teaching or technical consultancy.

Why study at University of Leicester

The University of Leicester offers a long-established physics tradition with active research groups in astrophysics, particle physics and condensed matter, providing opportunities to link teaching with current research. Leicester has recognised strengths in space and planetary science and hosts research centres and facilities that students can engage with. The School provides modern laboratories, computing clusters and dedicated support for learning programming and data analysis tools commonly used in industry (for example Python and relevant libraries).

Students benefit from industry links, careers support and opportunities for summer internships or project collaborations with local and national employers. Small-group teaching in core practicals, a strong academic support network and options for research-led final projects make the programme well suited to those who want a balance of theoretical physics and hands-on data skills.