Measuring brain and body biological age to predict health outcomes and disease risk during ageing
Prof D Sharp
Dr B Glocker
No more applications being accepted
Funded PhD Project (European/UK Students Only)
(4 year MRes + PhD studentship)
This project is one of 11 studentships on offer in the Imperial College EPSRC Centre for Doctoral Training in Neurotechnology for Life and Health
Supervisors: David Sharp (Brain Sciences), Ben Glocker (Computing), Paul Matthews (Brain Sciences), James Cole (Brain Sciences)
As the global population ages, a better understanding of the ageing process is essential to help combat the rising burden of age-related disease. Using UKBiobank brain and heart imaging data, in combination with physiological, behavioural and genetic measures, this project will characterise ageing from a biological perspective. Cutting-edge ‘machine learning’ techniques will be developed into a healthcare tool for identifying people at increased risk of age-related ill-health, before symptoms are visible. This ‘big data’ software will have applications in health screening and clinical trial design, and allow us to better understand positive and negative influences on the human ageing process.
The CDT programme is not a standard PhD programme. Throughout the 4 years, there is considerable emphasis upon multidisciplinary and transferable skills, through centre activities beyond the individual research project. The programme cannot be taken without the first (MRes Neurotechnology) year, as it is an integral part of the overall programme.
Applicants should have (or expect to obtain) a first or upper second class degree (or non-UK equivalent) in an engineering or physical science subject. Students with a biological and medical sciences background may be considered, but candidates must have sufficient quantitative skills to thrive in the programme. You should be looking for a challenging, multi-disciplinary PhD at the interface of neuroscience and engineering.
The project would suit a candidate interested in biomedical applications of computational learning methods. Familiarity with computer science/programming and/or machine learning/statistical learning techniques would be an advantage.
To apply online, visit www.imperial.ac.uk/neurotechnology/cdt/apply/
If you have questions or would like further information about the project, we encourage you to contact the supervisors directly before making your formal application.
Studentships pay UK/EU tuition fees, stipend and a generous consumables and travel fund for the duration of the programme (one year of MRes and 3 years of PhD).
Places are open to UK and EU applicants only.
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