Using AI to predict and prevent future stroke using routine investigations


To apply please use the online application form. Simply search for PhD Medical Studies (and select the entry point of October 2023), then clearly state that you are applying for a PhD and name the project at the top of your personal statement.
Online application
Before applying, please ensure you have read the Doctoral College’s general information on applying for a research degree.

For more information on the admissions process please contact
Supervisory team
Director of Studies Dr Stephen Mullin 
2nd Supervisor Professor Stephen Hall
3rd Supervisor Professor Emmanuel Ifeachor
4th Supervisor Dr Mark Thurston
Applications are invited for a three-year PhD studentship. The studentship will start on 1 October 2023.
Project description

The advanced bioinformatics in imaging group is pleased to announce an exciting research opportunity to use routinely collected clinical data to help prevent future stroke. There are more than 100,000 strokes in the UK each year causing 38,000 deaths, making it a leading cause of death and disability. The first year of stroke aftercare costs between £12,000- £24,000 per patient. Many evidence-based interventions are available to reduce stroke risk and 95% of those who had a stroke had at least one untreated risk factor for it, with up to an estimated 13.7% of these strokes deemed to be preventable. There is significant potential to reduce morbidity/mortality and associated costs. 
The proposed project will draw on a dataset of routine investigations undertaken in patients who subsequently developed a stroke and matched controls. It comprises MRI and CT brain, ambulatory ECG and echocardiogram data. The aim of the project will be, using this unique dataset comprising some 10,000 stroke cases and 30,000 controls, to build and optimise a machine learning model to predict future stroke risk based on investigations undertaken prior to the stroke occurring.
It will entail learning a range of bioinformatic techniques such as deep learning, image segmentation and natural language processing. It will interface with de-identified clinical data extracted from the systems of University Hospitals Plymouth NHS Trust, particularly Digital Imaging and Communications in Medicine (DICOM) standard. Candidates will learn about the strict governance requirements for the handling of such data and be involved in processes to demonstrate compliance with it. A particular focus of the PhD will be the use of explainable AI to evaluate and demonstrate the validity of findings.
The successful candidate will sit within a multidisciplinary group, part of the Brain Research & Imaging Centre (BRIC) of the University of Plymouth. They will have access to scheduled teaching aligned to the MSc Human Neuroscience and a taught module programme, which allows development of generic research skills including academic writing, statistics, research design and governance. 

Applicants should have a first or upper second class honours degree in an appropriate subject and preferably a relevant masters qualification. A background in health data science is desirable but not essential. The successful candidate must however be able to demonstrate a track record of computer programming and the use of advanced bioinformatics techniques.
The studentship is supported for 3 years and includes full Home tuition fees plus a stipend of £17,668 per annum (2022/23 rate).  The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications.  Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates (approximately £12,670 per annum).
If you wish to discuss this project further informally, please contact Dr Stephen Mullin
Please see here for a list of supporting documents to upload with your application. 
This vacancy will involve working with children and/or vulnerable adults and any appointment will be subject a Disclosure and Barring Service check.

For more information on the admissions process generally, please contact
The closing date for applications is 12 noon on 27 March 2023.

Shortlisted candidates will be invited for interview shortly after the deadline.  We regret that we may not be able to respond to all applications.  Applicants who have not received a response within six weeks of the closing date should consider their application has been unsuccessful on this occasion.