This fully-funded PhD offers a unique opportunity to drive that change.
We are seeking a talented and motivated student to join a multidisciplinary team working at the intersection of biomedical engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health.
You will develop and apply cutting-edge techniques in:
- Signal processing for extracting physiological biomarkers from ECG, PPG, and related sensor data
- Machine learning and AI for predictive modelling and risk stratification
- Computational physiology modelling to personalise and simulate maternal cardiovascular response
- Data fusion and integration of heterogeneous datasets from wearables and hospitals
A Collaborative, Interdisciplinary Environment:
The position is based in the Department of Biomedical Engineering at Swansea University, but you will also interact closely with our national network of clinicians from across the UK. This ensures the project stays grounded in clinical need, with direct routes to translation and impact.
You’ll have access to world-class computational facilities, real-world datasets, expert supervision across engineering and clinical science, and the vibrant interdisciplinary research community at Swansea.
Funding: This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £20,780 for 2025/26).
Additional research expenses of up to £1,000 per year will also be available.
