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Artificial Intelligence and Medical Imaging MSc

London, Bloomsbury

Are you intrigued by the potential of medical imaging and AI, and how these new technologies can be used to enhance clinical care? This one-year Master’s will give you specialist expertise in the latest imaging technologies and AI methods, so you can play your part in improving disease detection and diagnosis, and help patients benefit from the treatments they need most.

UK students International students
Study mode
Full-time
UK tuition fees (2026/27)
£18,400
Overseas tuition fees (2026/27)
£39,200
Duration
1 calendar year
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 Computer Science, Engineering, Physics or related fields from a UK university or an overseas qualification of an equivalent standard. Undergraduate level knowledge in programming languages (such as Python or C++) is essential, demonstrated, e.g., by relevant courses or by an individual project they worked on during their UG. Undergraduate level knowledge of mathematics is also required, in algebra, analysis and probability. Applicants must show an interest in developing thinking and problem-solving skills.

The English language level for this course is: Level 2
Overall score of 7.0 and a minimum of 6.5 in each component.

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


This MSc covers the core technology and applications of the latest medical imaging tools currently available in healthcare, as well as new developments – and the valuable data and analysis that can be extracted from them.

You will explore core methods and techniques in both AI and medical imaging, and undertake your own piece of research to put your skills into practice working on clinically relevant problems. Explore topical challenges like medical image segmentation, quantifying pathological regions in medical images, improving imaging based diagnosis and treatment response prediction, working alongside UCL’s researchers who are helping to shape and influence new developments in this exciting field. 

There’s a lot of flexibility too, with the chance to add in optional modules. The programme spans the departments of UCL Medical Physics and Biomedical Engineering and UCL Computer Science, so you can focus on computing, study AI and computational modelling in surgery, or learn more about med-tech entrepreneurship if you’re interested in exploring a start-up career path.

Who this course is for

This course is for you if you have a background in computer science, engineering or a related field, and are looking to deepen your knowledge and specialise in applying it to healthcare.

It’s particularly relevant if you enjoy problem-solving and innovating, and are interested in redefining what’s possible in healthcare with the goal of improving patient lives through AI and medical imaging.

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:

  • Develop your skills alongside renowned academics across UCL's Department of Medical Physics and Biomedical Engineering. UCL is ranked 8th in the world for Medicine and 21st in the world for Data Science and Artificial Intelligence (2025 QS World University Rankings by Subject).
  • Be part of a world-leading hub for interdisciplinary research and collaborations between computer scientists, physicists, mechanical engineers, biomedical scientists and medical practitioners across UCL and its affiliated teaching hospitals.
  • Learn directly from research staff in a close-knit community, with regular opportunities for networking and professional development.
  • Get first-hand insight into the latest research taking place globally in this field, in areas like foundation models for medical imaging, image registration and segmentation.
  • Build analytical, research and communication skills you can take with you into your career.
  • Work on a 9-month-long dissertation structured around the application of AI and medical imaging in healthcare.
  • 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

Globally, the use of AI in healthcare is rising rapidly. Diagnostic workflows in clinics and other healthcare settings rely on an ever-increasing amount of imaging data (such as x-rays, MRIs and ultrasounds) and their analysis puts time pressure on consultations. 

AI technologies can help ease the burden, and provide faster and more accurate diagnoses.

High-tech start-ups and established healthcare providers need to recruit engineers with these skills to drive research and innovation in this rapidly emerging field.

Graduates from our Department have obtained employment with a wide range of employers and sectors, such as financial technology, medtech industries, hospitals, clinical settings and academia.

Find out more on our Meet our Alumni page.

Employability

By the end of this Master’s, you’ll be well placed to pursue diverse careers and opportunities – from academic research to roles in industry and positions that contribute to emerging technologies such as the use of AI in healthcare. Your expertise will be relevant in both industry and public healthcare. You could go on to develop or evolve new technologies as part of a med-tech start-up or global company. 

This MSc is also an excellent starting point for doctoral studies and a career in research, as you’ll be learning from world-leading UCL researchers at the forefront of healthcare innovations.

Networking

You will have regular opportunities to connect, collaborate and build professional contacts as part of your Master’s.  

  • 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.
  • Work within research groups, and across UCL departments, to develop your knowledge and skills.  
  • Network with external partners and showcase outputs to potential employers at private industry events and clinical centres.
  • Build your networks further, and socialise, through clubs and societies at UCL, such as the UCL MedTech Society and UCL AI Society.  
  • Tap into our partnerships with charities, research councils and international organisations. 

Teaching and learning

Your time will be split between lectures, seminars and tutorials, and independent study.

You’ll be assessed through exams, coursework, 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 lectures, you’ll spend time outside of class reviewing the material and completing coursework; this equates to around 20 contact hours a week and approximately 15-20 hours of self-directed study for a full-time student.

Finally, you’ll need to spend a significant amount of your study time on your research project (on average, up to 8 hours a week for full-time students). Exactly how much time you spend on your research project will change from term to term – you’ll spend less time on it in Terms 1 and 2 and then work exclusively on it in Term 3 (the summer term after the exam period).

Modules

The taught part of the programme is comprised of 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. 

Compulsory Module Requirements

To meet the compulsory module requirements, students must choose at least one of the following modules:

  • MRI and Biomedical Optics
  • Medical Imaging with Ionising Radiation

(Students may choose to take both of these modules if they wish.)

In addition, students must choose one of the following:

  • Applied AI in Medical Imaging
  • Applied Deep Learning

(Please note that students cannot take both of these modules)

Compulsory modules











Optional modules








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.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Artificial Intelligence and Medical Imaging.

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
Tuition fees (2026/27) £18,400
Tuition fees (2026/27) £39,200

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.

It is expected that students will provide their own laptop. For example, machine learning modules require a modern laptop that can run basic Python and MATLAB computing environments with an internet connection, camera and microphone (e.g., 8GB RAM, 500 GB of hard-drive space). For artificial intelligence projects GPU support will be an advantage. (Information from June 2025)


Students will be required to pay for their travel costs to teaching or project locations if they are off campus (e.g. at 90 High Holborn or Charles Bell House). Project locations and teaching are based in London. As of June 2025, the anytime 18+ Student Oyster (Zone 1 - 5) pay-as-you-go cap is £15.30.

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

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 you want to study Artificial Intelligence and Medical Imaging at graduate level
  • why you want to study Artificial Intelligence and Medical Imaging at UCL
  • what particularly attracts you to this programme
  • how your academic and professional background meets the demands of this programme
  • where you would like to go professionally with 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.

Successful applicants should show an interest in developing thinking and problem-solving skills.

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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