Artificial Intelligence Enabled Healthcare MRes + MPhil/PhD

London, Bloomsbury

Artificial Intelligence (AI) has the potential to transform health and healthcare systems globally, yet few individuals have the required skills and training. To address this challenge, our Centre For Doctoral Training (CDT) in AI-Enabled Healthcare Systems will create a unique interdisciplinary environment to train the brightest and best healthcare artificial intelligence scientists and innovators of the future.

UK students International students
Study mode
UK tuition fees (2022/23)
Overseas tuition fees (2022/23)
1 calendar year
2 calendar years
Programme starts
Research degrees may start at any time of the year, but typically start in September.
Applications accepted
Applications are accepted on a rolling basis.

The Centre for Doctoral Training recruits in at least two rounds. Please see the CDT website for further details.

Entry requirements

A minimum of an upper second class honours undergraduate degree, or a Master's degree in a relevant discipline (or equivalent international qualifications or experience). Our preferred subject areas are Physical Sciences (Computer Science, Engineering, Mathematics and Physics) or Clinical / Biomedical Science. Applicants with a clinical background or degree in Biomedical Science must be able to demonstrate strong computational skills. You must be able to demonstrate an interest in creating, developing or evaluating AI-enabled Healthcare systems.

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Standard

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. International Preparation Courses

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

If you are intending to apply for a time-limited visa to complete your UCL studies (e.g., Student visa, Skilled worker visa, PBS dependant visa etc.) you may be required to obtain ATAS clearance. This will be confirmed to you if you obtain an offer of a place.

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

Every student who is accepted onto the AI-enabled Healthcare Systems Centre for Doctoral Training (CDT) must take the MRes Artificial Intelligence Enabled Healthcare in their first year.

This will be followed by a 3 year PhD. Throughout this period the CDT will continue to closely monitor the need for continuing training and support, tailored to each student, and provide ongoing training in research skills.

The MRes is not currently available as a stand-alone programme.

The MRes programme covers the core competencies of artificial intelligence and has a central emphasis on how healthcare organisations work. As part of the MRes, you will complete a substantial Masters-level project of your choice, working with a supervisory team that will normally include a clinician and an academic.

The remaining years will be more like a traditional PhD, which leads to the presentation of a PhD thesis at the end of the fourth year. During your PhD you will remain involved in CDT activities and will continue to work closely with relevant health professionals and clinical teams through our NHS partners and leading academics at UCL.

More information can be found on the CDT Website.

Who this course is for

What this course will give you

  • Benefit from UCL's excellence both in computational science and biomedical research innovating in AI;
  • Be supervised by world-leading clinicians and AI researchers in areas related to your research;
  • Work within a real-world setting, embedded within hospitals, allowing you to gain a practical understanding of the value and limitations of the datasets and the translational skills required to put systems into practice;
  • Have the opportunity to not only apply AI to healthcare but to apply healthcare to AI, generating novel large-scale open datasets driving methodological innovation in AI;
  • Become a future leader in solving the most pressing healthcare challenges with the most innovative AI solutions;
  • Study at UCL, which was ranked the top university in the UK for research strength in the most recent Research Excellence Framework (2014) and ranked 10th best university in the 2021 QS World University Rankings.

The foundation of your career

The CDT is a new programme. As such, we do not yet have any graduates from the four-year programme. Previous students from our experienced CDT supervisors have tackled projects in AI and healthcare and gone on to successful careers in academia and industry.


The distinctive characteristics of our programme allow us to produce graduates who are prepared to:

  • engineer adaptive and responsive solutions that use AI to deal with complexity;
  • innovate across all levels of care, from community services to specialist hospitals;
  • be comfortable working with patients and professionals, and responding to their input;
  • appreciate the importance of addressing health needs rather than creating new demand.


Teaching and learning

Research areas and structure

  • AI-enabled diagnostics or prognostics
  • AI-enabled operations
  • AI-enabled therapeutics
  • Public Health Data Science
  • Machine Learning in Health Care
  • Public Health informatics
  • Learning health systems
  • Electronic health records and clinical knowledge management
  • Big Data
  • e-health and m-health
  • Clinical Decision Support Systems

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 is subject to change.


Details of the accessibility of UCL buildings can be obtained from AccessAble Further information can also be obtained from the UCL Student Support & Wellbeing team.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2022/23) £5,690 £2,845
Tuition fees (2022/23) £26,500 £13,230

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website:

Additional costs

All studentships include a research training support grant, which covers additional research costs throughout students' time on the programme.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

Please visit the CDT website for funding information:

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

Next steps

Note for applicants: When applying on UCL Select, please select MRes Artificial Intelligence enabled healthcare to apply for programme.

Please note that you may submit applications for a maximum of two graduate programmes in any application cycle.

UCL is regulated by the Office for Students.