About the project
VIDA (Vascular and Immune contributions to DementiA) is a brand new multi-institutional partnership between four world-leading research sites: the University of Manchester, University of Edinburgh, Imperial, and St George’s University of London. With projects focussing on the Vascular and Immune contributions to DementiA, VIDA PhD students will become the next generation of much-needed dementia researchers, contributing to breakthroughs in dementia diagnosis, treatment, and care. VIDA students will embark upon a four-year fully-funded PhD project at one of the institutions above, with access to the state-of-the-art research facilities and interdisciplinary training available at all sites. Students at each site will come together as a cohort at several points during the programme, most importantly for an induction week at the beginning of the programme, followed by annual conferences, and residential workshop retreats. Students will also participate in engagement schemes with the Alzheimer’s Society and beyond, sharing the impact of their research in the community. The programme also benefits from built-in opportunities for placements with leading industrial partners, and bespoke training plans including schemes to develop teaching, mentoring, and grant writing skills.
Project title
Predicting cognitive and neurodegenerative outcomes from big data using automated retinal imaging analysis systems.
Supervisory team
Project description
Early detection of cognitive decline allows identification of those at high risk of developing dementia when medical treatments may be effective in preventing disease onset.
Our group have developed an AI-enabled system which can extract detailed retinal vasculometry characteristics from colour fundus photographs (CFPs) in a fully automated way, allowing application to large population-based studies. Using data from 11 million vessel segments from over 200,000 CFPs, we have shown that retinal vasculometry can predict cardiovascular disease as well as established risk scores and predict novel outcomes such as circulatory mortality. Retinal vasculometry (a neurovascular biomarker) as a predictor of cognitive/neurodegenerative status is yet to be examined at scale. While end-to-end AI approaches have recently been used to detect Alzheimer’s disease from CFPs among those with established disease (in case-control studies), the use of such approaches to predict disease (i.e., in early ‘prodromal’ stages) is yet to be established in large community settings.
This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative status, in exceptionally large population-based studies (e.g., UK Biobank and Scottish Collaborative Optometry-Ophthalmology Network e-research with over 100,000 study participants, with repeat assessment in a sub-set), and establish a retinal vasculometry data-set in clinical settings (e.g., the Imperial Comprehensive Cognitive assessment in Cerebrovascular disease IC3 study). Findings will provide an early warning system of dementia, to be exploited within existing healthcare pathways to trigger early intervention.
Skills acquisition
The studentship will provide training in data-analytics, statistics including predictive modelling, computer vision and epidemiology.
The programme also benefits from built in opportunities for placements with leading industrial partners, and bespoke training plans including schemes to develop teaching, mentoring, and grant writing skills.
Entry requirements
Applicants are expected to hold (or about to obtain) a minimum upper second class undergraduate honours degree (or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable.
Funding
This four-year studentship is open to UK and international students and provides funding to cover stipend (maintenance allowance at UKRI rate, set at £19,237 per year for 2024-2025, paid in monthly instalments) and home tuition fees.
Funding is also provided for research expenses, career development, and student travel/conference attendance.
Application process
The following documents should be submitted to stgeorgesphd@sgul.ac.uk no later than Sunday 14 July, 23.59 BST:
- Personal statement about your reasons for applying for this studentship (maximum one page)
- Curriculum Vitae (maximum two pages)
- Two references. Applicants should arrange for two relevant referees to submit letters of reference via email before the deadline.
Interested candidates must first make contact with the Primary Supervisor Professor Christopher Owen prior to submitting a formal application, to discuss their interest and suitability for the project. Informal enquiries can be sent via email to cowen@sgul.ac.uk
Interviews will likely take place in August 2024. Candidates will be asked to give an eight-minute presentation on a previous/on-going research project that showcases skills and knowledge, followed by questions on the presentation and the application.