Programme

The aim of the CDT is to train a new generation of responsible researchers and innovators with the expertise and knowledge to transform the pace and precision of medical diagnosis and care through the application of Artificial Intelligence.

TC: Turing Conference (AIUK); CC: CDT Conference (Internal and Joint); TR: Transfer Review; PR: Annual Progress Review

• The MSc programme lasts the first 18 months.
• It starts at the same time as, and takes place alongside, the PhD programme.
• Students on the MSc programme gain strong support as a cohort.
• Students complete 180 Masters-level credits:
  • 60 credits covering the fundamentals of AI in the context of various application domains, including health;
  • 30 credits on the wider perspective of digital systems in the health service, and ethical and legal issues associated with health data;
  • 60 credits from over 100 potentially relevant modules according to your individual background and chosen PhD research topic;
  • A 30 credit research project (gateway to the full PhD program)

• Students will undertake a small research project in an area of AI in medical diagnosis and care to help understand how AI can support improvements in medicine.
  • The MSc project consolidates research skills to prepare students for the PhD programme and give them practical experience in developing and discussing AI solutions that have the potential to transform diagnosis and care.
  • Students will:
    • design, build and test an AI application using sample data
    • carry out a critical review of the relevant literature
    • demonstrate a clear understanding of the steps required to undertake research
    • present a coherent, conference-standard research paper and presentation
  • Students will present their projects at the CDT Conference Simulation (see a full list of Cohort Activities here).

PhD research

• The PhD programme starts from month 6.
• During months 6-18 the students undertake research alongside their MSc training.
• At month 6, students select a topic area for their PhD research.
• The research is jointly supervised by an interdisciplinary team involving both AI and clinical researchers.
• The Student Page provides detail about our current students and their projects.
• Initially, we sought projects from interdisciplinary teams to address key challenges in one of the CDT's themes (Screening and Early Detection, Diagnosis, and Treatment and Care), though now this has expanded to a much wider range of problems in healthcare with potential AI solutions.
• The emphasis is on impact-driven research, innovation through application of AI, and experience/track record of the supervisory team. The topics offered are tailored to the interests of the students.

Research training

Alongside the MSc modules and PhD research, students follow an extensive programme of activities and events:

• Participation in an annual CDT Internal Conference, CDT AI² monthly forum and seminars in Leeds Institute for Data Analytics;
• Participation in masterclasses organised jointly with The Alan Turing Institute and the annual Turing AIUK conference;
• Participation in joint events organised with other CDTs at the University of Leeds and nationally;
• Training on ethics, responsible research and innovation, developing impact from research, and generic research skills;
• Weekly participation in the CDT journal club and other relevant journal clubs;
• Attending conferences and workshops at national and international level;
• Participating in two outreach and public/patient engagement activities per year.

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