| Level: | PhD |
| Tuition: | Full coverage |
| Deadline: | Feb 19, 2027 |
| Duration max: | 99 months |
| Level: | PhD |
| Tuition: | Full coverage |
| Deadline: | Feb 19, 2027 |
| Duration max: | 99 months |
This is a funded PhD position in applied medical imaging and deep learning to heart diseases, suited to candidates with an applied mathematics, computer science, electrical engineering, medical imaging, biomedical engineering, physics or equivalent MSc/BSc degree.
The overarching aim of this project is to develop new prediction tools of heart disease using big data by integrating machine learning and statistical learning approaches. Cardiovascular diseases (CVDs) are diseases of the heart and blood vessels. According to the World Health Organisation (WHO), 17.9 million people die each year from CVDs, an estimated 31% of all deaths worldwide. Large amounts of data in various forms, such as Electrocardiogram (ECG), imaging, clinical tests and patient characteristics, are routinely generated in clinical research and practice. The successful candidate will develop novel deep-learning image analysis solutions to support the prediction of CVDs based on an unprecedented large image dataset in Liverpool.
Stipend (approx): £15,000 per annum tax-free, full UK home tuition fees and research bench fees paid. Exact amount TBC
Open to students worldwide