Early Detection of Eye Diseases using Visual Computing and AI technologies

This project aims to develop Visual Computing and Artificial Intelligence-Based technologies for the Diagnosis of retinal and/or Corneal eye diseases. The research will process variety of medical scans such as Optical coherence tomography (OCT), Fundus images, confocal microscope images, etc. Successful treatment needs early eye disease diagnosis and intervention but accurate and rapid identification of the bio markers of these diseases and proper management are challenging clinical problems.

Our research group has an established track record in developing medical diagnostic technologies, in collaboration with the National Health Service (NHS). This project will build on this collaboration and will deliver, in close collaboration with the NHS, a new computer vision system for process medical eye scans and diagnosing different eye diseases, using advanced medical imaging and machine learning techniques.

How to apply

Formal applications can be submitted via the University of Bradford web site; applicants will need to register an account and select ‘Full-time PhD in Computer Science’ as the course, and then specify the project title in the ‘Research Proposal’ section.

About the University of Bradford

Bradford is a research-active University supporting the highest-quality research. We excel in applying our research to benefit our stakeholders by working with employers and organisations world-wide across the private, public, voluntary and community sectors and actively encourage and support our postgraduate researchers to engage in research and business development activities.

Positive Action Statement

At the University of Bradford our vision is a world of inclusion and equality of opportunity, where people want to, and can, make a difference. We place equality and diversity, inclusion, and a commitment to social mobility at the centre of our mission and ethos. In working to make a difference we are committed to addressing systemic inequality and disadvantages experienced by Black, Asian and Minority Ethnic staff and students.

Under sections 158-159 of the Equality Act 2010, positive action can be taken where protected group members are under-represented. At Bradford, our data show that people from Black, Asian, and Minority Ethnic groups who are UK nationals are significantly under-represented at the postgraduate researcher level. 

These are lawful measures designed to address systemic and structural issues which result in the under-representation of Black, Asian, and Minority Ethnic students in PGR studies.