AI-based usage of retinal images with brain imaging for the early diagnosis of ageing-associated neurological diseases
PhD studentship in biomedical informatics at the University of Surrey, in collaboration with the National Physical Laboratory.
Start date1 October 2022
Funding sourceUniversity of Surrey (matched studentship for EPSRC ICASE PhD studentship)
Tuition fees at the standard UK rate and a stipend of £18,600 per annum for the student.
Funding for this project is available to UK students.
Are you interested in AI as well as the brain? Then this PhD studentship might be of interest: we are looking for a bright and highly motivated student to utilise modern Artificial Intelligence (AI) algorithms to analyse large amounts of biomedically relevant data to create novel computational models. You will be studying datasets including images of the retina and the brain to explore neural biomarkers in health and disease.
Here, the student will investigate potential biomarkers to support the early diagnosis of disease and 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 diagnose neurological conditions in the early stages. In particular, the goals of this project are:
- Analyse and compare retinal images with brain imaging data
- Develop multimodal models to detect ageing-associated neurological disease
- Carry out thorough sensitivity analysis resulting in a reproducible AI/Machine Learning (ML) pipeline
- Contribute to the ongoing computational biomedicine collaboration BioDynaMo.
As a 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.
Researchers Dr Ignacio Partarrieu and Dr Jenny Venton 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 (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 that will be made available to the successful applicant.
The student will learn modern Machine Learning techniques and also benefit from the ongoing BioDynaMo project on high-performance computational research, in collaboration with IT-experts at CERN. Notably, the student will benefit from weekly seminars and daily interactions with computational and biomedical researchers as well as clinical experts. The studentship is for a duration of 4 years.
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.
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.
EU/International students are considered only if they can demonstrate exceptional achievements (e.g., publications, excellent academic performance, prizes, etc.).
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.
How to apply
PhD Computer Science