Assessing the use of retinal images for the early diagnosis of ageing-associated neurological diseases

Are you interested in AI as well as the brain? Then this interdisciplinary 4-year PhD studentship might be for you: we are looking for a bright and highly motivated student to utilise modern Artificial Intelligence (AI) algorithms to analyse images of the retina. The retina is a neural tissue at the rear of the eye. Recent results of ours and other researchers indicate that retinal images can reveal information about brain health that is relevant to the diagnosis of neurological conditions such as Alzheimer’s disease or Parkinson’s disease.

Here, the student will investigate potential biomarkers to support the early and non-invasive diagnosis of neurological conditions alongside monitoring of brain health. To this end, the student will work together with experts in the field to learn how to use modern AI tools to extract valuable information from the available dataset, and produce novel hypotheses that will generate better methodologies to support the diagnosis of neurological conditions in the early stages. In particular, the goals of this project are:

• Analyse retinal fundus and optical coherence tomography imaging data with associated patient metadata
• Develop Machine Learning (ML)/AI models to detect ageing-associated neurological disease
• Carry out thorough sensitivity analysis resulting in a reproducible AI/ML pipeline
• Interact with collaborating clinicians to identify applications of the research.

Training

As an EPSRC iCASE PhD researcher you will undertake training that will lead towards a PhD and allow you to gain various skills and expertise to strongly support your future career, whether in industry or academia. Students will be supported in publishing their research and encouraged to present it at international conferences.

The student will be supervised by Dr Roman Bauer and Dr Alireza Tamaddoni-Nezhad at the Department of Computer Science at the University of Surrey.

Researcher Dr Tameem Adel, based at the National Physical Laboratory (NPL), will co-supervise the student and help ensure that the methods developed meet metrology requirements through a thorough sensitivity analysis of data parameters and ML/AI hyperparameters, resulting in a reproducible ML/AI pipeline. Moreover, ophthalmologists Dr David Steel and Dr Maged Habib (Newcastle University and NHS) will support the clinical applicability of the project.

Both the University of Surrey and NPL offer a variety of professional training courses that will be made available to the successful applicant. Overall, the supervisory team includes domain experts who will support the student in gaining highly interdisciplinary skills. These are in fields including artificial intelligence, statistics, biomedicine, ophthalmology and others. Moreover, the student will benefit from weekly seminars and daily interactions with computational and experimental researchers.

Equality, Diversity and Inclusion

The University of Surrey is committed to providing an environment which recognises and values people's differences, capitalises on the strengths that those differences bring to the institution and supports all staff and students in maximising their potential to succeed. This commitment is made with specific reference to a person's age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religious belief and non-belief, sex and sexual orientation. Along those lines, the University of Surrey was awarded an Athena SWAN Bronze award, is part of the Race Equality Charter, has partnered with AccessAble and supports the “Time to Change” campaign. Likewise, the National Physical Laboratory is strongly committed to diversity, beyond the Equality Act and Public Sector Equality Duty.

Reflecting our Institutes’ position, we are committed to diversity, inclusion and wider engagement (e.g., with schools, communities and international partners). In our labs we are committed to creating an open, diverse and interdisciplinary environment that is welcoming to everyone, including under-represented minorities, women and underprivileged students. For instance, the BioDynaMo collaboration that is led by Dr Bauer commits to the Contributor Covenant Code of Conduct.

This project is suitable for UK students (only UK fees covered) with a Bachelor's degree in physics, mathematics, computer science, bioinformatics or a related field. Academic excellence should be demonstrated, i.e. 2:1 or above.

A Master’s degree and/or experience in image analysis or AI/ML methods are desirable but not essential. The key requirements are an interest in the topic and a good work ethic.

Students who like developing tools for computational biology/drug discovery platforms and interacting with industry may also be interested.

If English is not your first language, you will be required to have an IELTS Academic of 6.5 or above (or equivalent), with no sub-test score below 6. 

View the other English language qualifications that we accept. If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.

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