2024 Applications

The UKRI AI Centre for Doctoral Training (CDT) in Biomedical Innovation is open for applications for September 2024 entry

The deadline for applications from overseas applicants for this coming academic year has closed. We have an extended deadline for UK-eligible applicants at midnight (GMT) on Friday 31st May 2024.

We will be interviewing candidates in May-June and will inform successful applicants of their offers throughout June-July 2024. See our Application Timeline for details.

The application portal is now open – please visit our “How to Apply” page and read our application guidance carefully before submitting your application.

Important Note for Overseas Applicants

We are aiming to recruit all students for the 2024 studentships in this deadline. Some applicants will need to apply for an ATAS certificate as well as a Student Visa, it is very important that you check whether you will need to apply for ATAS by reading the UK Government Guidance. If you will need to apply for an ATAS certificate then it is important that you make your application to the programme as soon as possible because it can take several months for certificates to be issued once an offer of a place has been issued. If an offer holder that needs them does not have a valid ATAS certificate and Student Visa in time to matriculate for the start of the programme we are not permitted to enrol them at the University and they will not be able to take up their place in the programme. The University has prepared excellent guidance for overseas students applying to study with us which you can find on the Student Immigration Service website.

Exceptionally for the first entry year of our new CDT, applications from overseas students requiring ATAS will be considered for early offers to maximise the chance of their obtaining the necessary permissions to commence their studies in September 2024.

Our Training Programme

We are seeking to fund approximately 10-12 studentships in each cohort, we would like to create student cohorts that come from diverse backgrounds and disciplines. We encourage applicants, if they would like to, to let us know of any challenges or barriers that they may have experienced that they feel has impacted their academic progression, ability to gain relevant experience, or indeed any other aspect they think is relevant to our consideration of their application.

The research programme is organised into four thematic areas: AI for Innovation in; Biomedical Imaging, Biomedical Engineering, Biomedical & Health Informatics, and Genomic Medicine each with an expert theme leader supported by groups of at least twenty project supervisors from across the University. For this application call, applicants will be asked to rank the themes that they are most interested in conducting their research in. Research Theme Leaders will work with successful applicants to align them with supervisors and research projects in time for joining the programme in September.

In our programme you will develop technical and domain specific inter-disciplinary research skills, and gain experience delivering innovation into the public and private sectors. You will learn to successfully design, develop, and implement AI approaches in partnership with external stakeholders.

Although we commonly recruit students from Computer science, Mathematics, Physics, and Engineering backgrounds we also have a lot of experience training those who may have relatively little prior exposure to computer science and mathematics. This includes clinicians, allied health professionals, biological, biomedical, and social scientists. We are primarily interested in an applicant’s potential to contribute to this field of research and have strategies in place to support students in gaining key skills and knowledge to successfully conduct research in applied biomedical artificial intelligence.

Our training is organised into overlapping academic areas: Artificial Intelligence, Biomedical, and Health each with an expert training lead and dedicated cross-programme training leads in RRI/Ethics, Entrepreneurship, and an ED&I Champion. These programme leads help to visualise the breadth and depth of the programme, tackling research challenges of profound societal and economic importance with an ethical and inclusive research ethos.

Programme Structure

Our programme is a 4 year PhD with integrated study in which you will take 180 credits of courses spread over years 1-3 whilst undertaking your PhD project research. You will undertake a Placement Dissertation Project (60 credits) for 3 months with either a public or private sector external partner flexibly in any one of years 1-3. You can read more about this on our Training page.

You will take three compulsory courses:

Year 1: Foundations in Biomedical AI Research (30 credits)
Year 2: Interdisciplinary AI Research (20 credits) and Case Studies in AI Ethics (10 credits)

You will also do a “Placement Dissertation Project”, a 3-month course in which you undertake a separate small research project in collaboration with an external partner to experience another environment and/or research challenge/technical area during your studies. This may take place remotely with the partner organisation but could also be conducted from the University if those arrangements better suit you and the partner organisation.

The exact profile of the taught component and timing of the placement dissertation project will be formulated in consultation between you, your supervisory team and the CDT. Many students will also choose to undertake separate internships during their studies.

The remaining 60 credits of courses will be selected by students to best suit their learning, research, and career development needs in consultation with their PhD supervisory team and CDT year group mentor.

Teaching Approach

You will gain an understanding of key challenges and opportunities for the application of AI in Clinical, Biomedical, and Public Health settings. You will gain the skills, knowledge, and experience to develop and implement AI solutions in interdisciplinary research environments and practice responsible research innovation.

  • Teaching and learning methods will include traditional lectures, tutorials, and workshops in the various courses as well as masterclasses, hackathons, and group mini-projects.
  • Training will be delivered by Edinburgh staff, invited lecturers, staff from industry and external partners, facilities/service staff.
  • Entrepreneurship training through “PhD Max”, “Venture Builder Incubator”, and other bespoke training through the Bayes Centre Entrepreneurship team and the programme’s Innovation training lead.
  • Outreach and Public Communication Training from specialist external providers including the Alan Turing Institute.
  • Public Patient Involvement and Engagement training and working with stakeholders to ensure research is well targeted and developed with the interests of all parties considered.
  • Responsible Research & Innovation training in collaboration with the Alan Turing Institute & experts from the University and the CDT’s external partners.

You will be supported by an experienced team of academic and professional service staff. Each year group will have a dedicated mentor who will work closely with our research and training leads, the CDT management group, external advisory board, and partners to support you in your studies.

Benefits of Joining Our Programme

  • Fully funded 4-year studentship, covering tuition fees, stipend (this is £19,237 in 2024/25) and an individual budget for travel and research support.
  • Supervision from at least two supervisors from different disciplines, covering expertise in artificial intelligence and biomedical/health science from in world-leading research groups across the University of Edinburgh.
  • An innovative interdisciplinary training programme with a focus on team working and application of novel methods to real-world challenges for the benefit of society and with the aim to improve health outcomes for patients.
  • Opportunities for research placements and internships with our partners.
  • Tailored training in public engagement, patient & public involvement & engagement (PPIE), entrepreneurship, leadership skills, and responsible research innovation (RRI).
  • CDT events including seminars, masterclasses, summer schools, conferences, guest lectures, hackathons, challenges, and partner days.
  • Located in the world-class and interdisciplinary research community of the Informatics Forum and Bayes Centre with access to state-of-the-art resources including unique data and computational resources.
  • Opportunities to connect and collaborate with other students at the University of Edinburgh’s CDTs, including the UKRI CDT in Biomedical Artificial Intelligence, UKRI AI Centre for Doctoral Training (CDT) in Responsible and Trustworthy in-the-world Natural Language Processing and the EPSRC Centre for Doctoral Training in Machine Learning Systems.
  • Opportunities to connect and collaborate with other aligned postgraduate research groupings including the MRC Precision Medicine Doctoral Training Programme and the East of Scotland Bioscience Doctoral Training Partnership.

Minimum Entry Requirements

Our minimum entry requirements are detailed on our application portal page, but in summary we require:

A UK 2:1 honours degree, or its international equivalent, in an area related to the topic of the CDT, for example, computer science, AI, cognitive science, mathematics, physics, engineering, biomedical science, biological science, and clinical & public health sciences.

We also welcome applicants who do not meet these requirements, but who can demonstrate suitability for the training programme based on extensive professional experience or from working in research posts.

There are also standard University English language requirements that are explained in detail on the application portal page.

How To Apply

For this application call we ask you to tell us about your background, your research ideas in relation to the Skills Domains, and to identify a number of potential supervisors you could work with. We have provided the following resources to help with the development of applications: