This MRes is the entry point to the 4 year PhD Programme in Health Data in Practice, funded by the Wellcome Trust. Acceptance onto the MRes in Health Data in Practice constitutes entry onto the 4 year PhD programme in Health Data in Practice; progression to PhD requires successful (i.e. pass or above) completion of the MRes. This course is not currently available as a standalone MRes in Health Data in Practice.

Our Wellcome-funded doctoral training programme applies human-centred data research to health and care data, and will introduce you to a wider context for your research, enabling you to draw on concepts, disciplines and methods underpinning algorithmic designs, sensing and data capture, human-data interactions, qualitative and quantitative evaluation and decision-making, in real-world settings. You will develop as a future scientific leader able to apply interdisciplinary perspectives to your research and realise the potential of innovations in health data research for the benefit of patients, the public, health care systems, and society.

The Wellcome Trust Health Data in Practice programme combines scientific excellence with a commitment to improving the working environment and transition support for trainees.

Additional costs

Studentships are fully funded including a stipend, tuition fees, research and training costs for the 4 year period of study. Additionally students will be able to apply to the Transition Fund in their final year of study to assist students in successfully navigating to the next stage of their career. Further details on the support provided can be found here.


Students will undertake six taught modules (120 credits in total) and a 60 credit independent project module. In total 180 credits are required to achieve the MRes.

  • Three compulsory modules totalling 75 credits
  • Three elective modules totalling 45 credits
  • A 15,000 word dissertation (60 credits)

The course structure and modules are for 2020-21 entry. Availability of elective modules depends on staffing and timetabling and may be varied.


  • Health Data in Practice
  • Introduction to Social Science Research 1: epistemology, research design, and qualitative methods
  • Introduction to Social Science Research 2: quantitative methods and data


  • Effective and efficient evaluation
  • Design for Human Interaction
  • Natural Language Processing
  • Applied Statistics
  • Interactive System Design
  • Neural Networks and NLP
  • Risk and Decision-making for Data Science and AI

How to apply

Deadline 1 April 2020. Visit the website:


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