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Computational Cancer MSc

London, Bloomsbury

Be part of the revolution in cancer research and computational science with this interdisciplinary Master’s at UCL. Delivered jointly by UCL Medical Physics and Biomedical Engineering and the UCL Cancer Institute, this programme equips you with cutting-edge skills at the forefront of healthcare innovation.

UK students International students
Study mode
UK tuition fees (2026/27)
£18,400
Fees to be confirmed
Overseas tuition fees (2026/27)
£39,200
Fees to be confirmed
Duration
1 calendar year
2 calendar years
Programme starts
September 2026
Applications accepted
Applicants who require a visa: 20 Oct 2025 – 26 Jun 2026
Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 20 Oct 2025 – 28 Aug 2026
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

A minimum of an upper second-class Bachelor's degree in a relevant subject from a UK university or an overseas qualification of an equivalent standard.

The English language level for this course is: Level 2

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree


A revolution is underway in cancer research, transforming a field once driven by the collection of experimental evidence into one powered by data analysis, modelling, and computational insight.

This Master’s programme will equip you with the skills to apply cutting-edge computational techniques, including artificial intelligence, dynamical modelling, and data science, to some of the most pressing questions in cancer research. You will gain advanced expertise in computational methods and cancer biology, and contribute to pioneering research aimed at deepening our understanding of this complex disease.

A wide range of optional modules enables you to tailor your studies, developing specialisms in areas such as cancer therapy, AI applications, and computational pathology.

UCL is ranked 2nd in the UK for research power (REF 2021) and leads globally in research impact, ranking #1 and #4 for citations in oncology and in computational biology and mathematics, respectively. Students benefit from access to world-class laboratory, workshop, teaching, and clinical facilities across UCL and its affiliated hospitals.

Who this course is for

This programme is suitable for individuals with either a first degree in life sciences or medical sciences, or computational/mathematical sciences, with a demonstrable interest in developing interdisciplinary skills for cancer research.

Read about what it takes to study for a Master's at UCL

What this course will give you

This degree offers you the following benefits and opportunities 

  • Join a world-leading hub for interdisciplinary research and collaborations between computer scientists, biomedical scientists and medical practitioners across UCL and its affiliated teaching hospitals.
  • Access world-class computing facilities, including trusted research environments and high-performance computers.
  • Learn from and work alongside research staff in a supportive and inclusive research environment, with regular opportunities for networking and professional development.
  • Develop your skills alongside renowned academics across UCL Cancer Institute and Medical Physics and Biomedical Engineering. UCL ranks 9th globally (QS World University Rankings 2026).
  • Enjoy opportunities to work collaboratively with the NHS, through our partnership with the UCLH NHS Trust, assisting health professionals to find essential uses for new technologies.  
  • UCL’s Bloomsbury campus is in the heart of a London district famous for its cultural and educational institutions.
Read about what you'll get out of a graduate programme

The foundation of your career

As a postgraduate student at UCL, you will develop a robust set of cross-disciplinary skills and knowledge that can be applied across a wide range of industry and healthcare settings. These include expertise in computational modelling, data science, and artificial intelligence, alongside the domain-specific understanding essential for careers in the life and medical sciences.

Working alongside world-leading scientists, engineers, and healthcare professionals, you will also strengthen key professional skills such as project management, communication, and teamwork, ensuring you are well prepared to contribute effectively in any organisation.

Graduates from our departments have gone on to successful careers across diverse sectors, including financial technology, pharmaceuticals, biotechnology, medical technology, hospitals, clinical practice, and academia.

Find out more on our Meet our Alumni page.

Employability

By the end of this Master’s, you will be equipped to pursue a wide range of careers and further study opportunities; from doctoral research to roles within industry and the growing field of AI in healthcare.

Your skills and knowledge will be highly relevant across both public and private healthcare sectors. Graduates may progress into technical or strategic roles within hospitals, either in the UK or internationally, where computational approaches are increasingly shaping diagnosis, treatment, and patient care.

Alternatively, you may choose to apply your expertise in research and development within industry settings, contributing to the design and implementation of new technologies across multinational pharmaceutical companies, medical technology firms, or innovative biotech start-ups.

Networking

You'll find various opportunities to build your network throughout this programme:

  • The Computational Cancer Collaboratorium offers a series of opportunities to engage with your peers in the university and hear from leaders in the field. This includes regular seminars, hackathons, and symposia, as well as specific support for early career researchers in terms of mentorship and coffee meetings. 
  • Benefit from our national and international collaborations across the clinical, industrial and academic sectors. We have close links with many London hospitals, including University College London Hospital, Great Ormond St Hospital, Moorfields Eye Hospital, Royal National Orthopaedic Hospital, Royal Free Hospital, National Hospital for Neurology and Neurosurgery, Royal National ENT and Eastman Dental Hospital, and Whittington Hospital. We also work with organisations like the National Physical Laboratory, Institute of Nuclear Medicine, and Institute of Neurology. A wide range of MedTech companies have spun out of departmental research.
  • Get involved in our wider network of charities, research councils and international organisations, and support partner projects.
  • Benefit from supervision and mentorship from scientists who collaborate nationally and internationally across clinical, industrial and academic sectors.
  • Network with external partners and explore opportunities to showcase your research output at international conferences, private industry events and clinical centres to potential employers.
  • Build your networks further (and socialise) through clubs and societies at UCL, such as the UCL MedTech Society.

Teaching and learning

The programme is delivered through a combination of lectures, demonstrations, practical exercises, assignments, and a research project. Lecturers are drawn from UCL and from London teaching hospitals including UCLH, St. Bartholomew's, and the Royal Free Hospital.

  • In Term 1, you will be introduced to key concepts and techniques. You will study modules in cancer biology, data handling, cleansing and analysis, and an introduction to different modelling techniques. 
  • In Term 2 you will pick optional modules allowing you to sample a greater range of specialisms in greater depth, including computational pathology, AI, and therapeutic techniques.
  • In Term 3 and over the summer you will engage full time in a research project, guided and supervised by two members of research staff.

Typically your research project will involve applying data science or modelling approaches to clinical or experimental datasets generated by the research groups. You’ll work closely with university research staff from a specific UCL research group, and present your work through reports and presentations.

You’ll be assessed through exams, coursework, presentations, group work, lab sessions and a research project.

Each module typically consists of around 36-40 hours of lectures and problem-solving classes over a 10-week term.

On top of your timetabled hours, you’ll spend time outside of class reviewing the material and completing coursework. In total, you’ll need to spend approximately 35-40 hours a week on your studies as a full-time student. This equates to around 20 contact hours a week and approximately 15-20 hours of self-directed study.

If you’re studying part-time or on flexi-time, this study commitment is divided on a pro-rata basis. This can all be discussed with your tutor during the course induction programme, who will design a timetable to suit your personal circumstances.

Modules

The taught part of the programme comprises of a mix of compulsory and optional modules. 

The first two academic terms consist of the taught modules, with your research project comprising a large part of the programme running from March to September. This is carried out under the supervision of an academic member of staff. 

Year 1

  • Term 1: 2 compulsory modules
    MPHY0059 - Curating Cancer Data (15 credits)
    MPHY0060 - Computational Modelling and Analysis of Cancer Dynamics (15 credits)
  • Term 2: 30 credits of optional modules (either taken as 1 or 2 modules)
     

Year 2

  • Term 1: 1 compulsory module
    CINS0001 - Basic Biology and Cancer Genetics (30 credits)
  • Compulsory module MPHY0061 Computational Cancer Research Project in Terms 1 to 3
  • Term 2: 30 credits of optional modules (either taken as 1 or 2 modules)

Compulsory modules


Curating Cancer Data

Computational Modelling and Analysis of Cancer Dynamics

Computational Cancer Research Project


Optional modules






Applied Digital Pathology

Fundamentals of Subtyping in Pathology


Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Accessibility

The department will endeavour to make reasonable adjustments for students with disabilities, including those with long-term health conditions, neurodivergence, learning differences and mental health conditions. This list is not exhaustive. If you're unsure of your eligibility for reasonable adjustments at UCL, please contact Student Support and Wellbeing Services.

Reasonable adjustments are implemented on a case-by-case basis. With the student's consent, reasonable adjustments are considered by UCL Student Support and Wellbeing Services, and where required, in collaboration with the respective department.

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

For more information about the department and accessibility arrangements for your course, please contact the department.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2026/27) £18,400 Fees to be confirmed
Tuition fees (2026/27) £39,200 Fees to be confirmed

Additional costs

For full-time and part-time offer holders with a fee status classification of UK, a fee deposit will be charged at 2.5% of the first year fee.

For full-time and part-time offer holders with a fee status classification of Overseas, a fee deposit will be charged at 10% of the first year fee.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

There are no programme-specific additional costs.

For in-person teaching, UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £119.90. This price was published by TfL in 2025. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

Funding your studies

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

See all the ways you can fund your studies

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.


There is an application processing fee for this course of £90 for online applications. Further information can be found at Application fees.


When we assess your application we would like to learn:

  • Why do you want to study Computational cancer at graduate level?
  • Why do you want to study Computational cancer at UCL?
  • Whether you have relevant industrial or workplace experience.
  • How your academic and professional background meets the demands of this challenging programme.
  • Where you would like to go professionally after your degree.
     

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

Please note that you may submit applications for a maximum of two graduate courses (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2026-2027

Apply for this course

Got questions? Get in touch

Medical Physics and Biomedical Engineering
Medical Physics and Biomedical Engineering

medphys.teaching@ucl.ac.uk

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