Available
Project number:
2025_36
Start date:
October 2025
Project themes:
Main supervisor:
Professor of Cardiovascular Data Analytics and Artificial Intelligence
Co-supervisor:
Pier-Giorgio Masci
Additional Information:
Understanding the heart-brain connection to tackle dementia and cardiovascular diseases using deep learning generative, advanced statistical and genetic modelling
Background-cardiovascular diseases and dementia share the same risk factors and pathobiological underpinnings. This is of particular concern given the increasing ageing population, the coexistence of CVDs and dementia in the same patients, and the lack of effective therapeutics for neurodegenerative diseases.
Novelty and Importance: A better insight into the heart-brain axis holds the potentials to unveil common mechanisms underlying cardiovascular diseases and dementia and, thereby, laying the foundation for novel therapeutic strategies to tackle cardiovascular diseases and dementia alike
Aims & Objectives:
Aims: the overarching aim of this project is to develop the first deep learning generative model of heart-brain interactions by leveraging large cohort study (UK-Biobank) combined with computational and machine learning technologies for prediction of neurodegenerative changes in the brain with causal inference
Objective-1 – to estimate the biological age of the brain (BrainAge) using brain MRI phenotypes and supervised machine-learning algorithm (XGBoost) to identify the cardiovascular MRI traits associated with an accelerated BrainAge
Objective-2- build deep learning generative model (Digital Heart-Brain) to characterize statistical relationships between biophysical properties underlying heart function and brain phenotypes, including an accelerated BrainAge.
Objective-3 – implement genome-wide-association (GWAS) and Mendelian Randomisation study (MR) to infer causality between cardiovascular system and neurodegenerative changes in the brain including an accelerated BrainAge.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at