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Information about Research Studentship in AI for Healthcare currently recruiting

Research Studentship in AI for Healthcare

3.5-year DPhil studentship 

Supervisor: Prof David Clifton

There is an urgent, unmet need for reliable, intelligent systems that can monitor patients in hospitals and in the home. Delays in recognition of the needs of a patient can worsen outcomes and increase healthcare costs. Intelligent systems are required to address the needs of patients in optimising care pathways. The Computational Health Informatics Lab at Oxford University is at the forefront of research and developing such systems.

This NIHR-funded PhD project will focus on the use of wearable technology, ranging from consumer items (e.g. Fitbits and Apple watches) to FDA-cleared devices, to monitor patients both at home and in hospital settings. Within this broad topic the student will have the scope to focus on aspects of this in which they have most interest. This could be, for example, investigating early warning of tropical diseases in LMICs, or developing ward-level monitoring of patients in UK hospitals. The studentship would be suitable for applicants with general interests in machine learning, signal processing, computational statistics, and biomedical engineering. It is an opportunity to work in a thriving engineering lab with close working relationships with UK clinicians and international partners. For more details about our work see the lab website:


This studentship is open to Home students (full award – home fees plus stipend).

Award Value

University course fees are covered at the home student rate. The stipend will be at least £18,622 for the first year, and at least this amount for a further two and half years.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:
  • A first-class honours degree (or equivalent) in Engineering or computer science, ideally with a specialism in signal processing, biomedical engineering, or statistics.
  • Excellent written and spoken communication skills in English.
  • Strong mathematical and analytical skills.
  • Knowledge of the practical aspects of deploying ML-based tools.

The following skills are also highly desirable:

  • Programming skills (e.g. Matlab, Python).
  • An interest in healthcare and knowledge of medical statistics.
  • Willingness to travel to international collaborators’ sites (expenses will be covered).

Application Procedure

Informal enquiries are encouraged and should be addressed to

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.

Details are available on the course page of the University website.

Please quote 24ENGBI_DC in all correspondence and in your graduate application.

Application deadline: 12:00 midday 1 March 2024.

Course start date: October 2024