Computer Science (retinal) PhD Projects, Programmes & Scholarships

We have 6 Computer Science (retinal) PhD Projects, Programmes & Scholarships

SEVERITY GRADING AND BIOMARKERS FOR RETINAL VASCULITIS

University of Liverpool Department of Eye and Vision Science

Retinal vasculitis is an important component of inflammatory eye disease or uveitis, as well as a serious adverse effect of new intravitreal treatments. Read more

Supervisor: Dr N Beare

Year round applications PhD Research Project Self-Funded PhD Students Only

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Identifying variants impacting splicing of 5’ and 3’ UTRs and underpinning inherited retinal disease

The University of Manchester Faculty of Biology, Medicine and Health

Genomic variation that impacts splicing is well established as a cause of genomic disorders, but is almost exclusively limited to protein-coding exons and introns intersecting protein-coding exons. Read more

Supervisors: Dr J Ellingford, Prof R O'Keefe

15 June 2024 PhD Research Project Funded PhD Project (UK Students Only)

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Development of a novel AI model for cardiovascular disease risk prediction by analysing retinal vascular structure and functional changes in blood flow

University of Liverpool Department of Eye and Vision Science

The Department of Eye and Vision Sciences at the University of Liverpool is inviting PhD candidates who are highly motivated in developing novel risk prediction model of cardiovascular disease (CVD) by analysing retinal images, contributing to a better understanding of relationship between the cardiovascular disease and the functional changes in blood flow. Read more

Supervisor: Dr HZ Zhao

1 May 2024 PhD Research Project Funded PhD Project (Students Worldwide)

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Machine learning for early and personalised risk assessment for pathological myopia

The University of Manchester Department of Mechanical, Aerospace and Civil Engineering

This project aims to assess if vascular analysis in retinal images can be used for personalised and early myopic degeneration/pathological myopia risk prediction. Read more

Supervisors: Dr A Harish, Dr H Radbakrishnan, Dr A Revell

31 May 2024 PhD Research Project Funded PhD Project (UK Students Only)

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Trusted AI for Diabetes personalised self-management systems

Kingston University Faculty of Engineering, Computing and the Environment

Diabetes mellitus is a common cause of morbidity and mortality across the globe. Type 2 diabetes continues to rise in prevalence annually; from 1980 to 2004, Type 2 quadrupled in both prevalence and incidence [1]. This will be exacerbated further by the increase in obesity. Read more

Supervisor: Dr N Philip

Year round applications PhD Research Project Self-Funded PhD Students Only

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Exploration of deep learning based generative adversarial networks (GANs) to mitigate bias in the evaluation of medical images among diverse population and disease sub-groups

Kingston University Faculty of Engineering, Computing and the Environment

Medical image analysis using Deep Learning models involves training on progressively larger datasets. Homogeneity of data within the training set, particularly in its representation of diverse population sub-groups and various disease stages, substantially influences model effectiveness. Read more

Supervisors: Prof S Barman, Dr F Rahman

Year round applications PhD Research Project Self-Funded PhD Students Only

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We have 6 Computer Science (retinal) PhD Projects, Programmes & Scholarships

Computer Science (retinal) PhD Projects, Programmes & Scholarships

We have 6 Computer Science (retinal) PhD Projects, Programmes & Scholarships

SEVERITY GRADING AND BIOMARKERS FOR RETINAL VASCULITIS

Identifying variants impacting splicing of 5’ and 3’ UTRs and underpinning inherited retinal disease

Development of a novel AI model for cardiovascular disease risk prediction by analysing retinal vascular structure and functional changes in blood flow

Machine learning for early and personalised risk assessment for pathological myopia

Trusted AI for Diabetes personalised self-management systems

Exploration of deep learning based generative adversarial networks (GANs) to mitigate bias in the evaluation of medical images among diverse population and disease sub-groups

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