PhD in Mathematics

Harness the power of Artificial Intelligence to address a major global health crisis./nMany serious respiratory conditions, including COPD and asthma, originate in the small airways – often called the “silent zone” because early abnormalities are missed by current diagnostic methods. This project sits at the cutting edge of biomedical engineering, AI, and respiratory medicine, developing a non-invasive, low-cost diagnostic tool by analysing subtle acoustic signals generated within diseased lungs./nYou will join a highly supportive supervisory team with world-leading expertise in computational lung modelling. Working with our proprietary respiratory system model, you will generate large-scale, high-quality virtual airflow and acoustic datasets. You will then develop and train state-of-the-art deep learning algorithms (e.g., CNNs, RNNs) to identify characteristic signatures of early airway disease./nThis project is designed for real-world impact. Through established clinical and industry collaborations, you will have the opportunity to embed your validated AI models directly into digital stethoscope platforms and support their translation into healthcare practice./nWe welcome motivated students with a strong background in engineering or science, such as physics, mathematics, computer science, or related disciplines. Skills in mathematics, computational modelling, programming, signal analysis or machine learning are particularly valuable.