PhD Studentship: 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.

The student will investigate potential biomarkers to support the early and non-invasive diagnosis of neurological conditions alongside monitoring of brain health. 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.

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

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. 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.

Ophthalmologists Dr David Steel and Dr Maged Habib (NHS and Newcastle University) will support the clinical applicability of the project.

Both the University of Surrey and NPL offer a variety of professional training courses. 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.

Entry requirements

Open to UK students starting in January 2023.

A Bachelor’s degree in physics, mathematics, computer science, bioinformatics or a related field. 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.

How to apply

Send Dr Roman Bauer ([email protected] ) your CV and arrange an informal discussion. Apply  via the Computer Science PhD programme page . Please state clearly the studentship project that you would like to apply for and your intended supervisor.

Funding

Tuition fees at the standard UK rate and a stipend of £18,600 per annum for the student.

Deadline

23 October 2022