Physics-informed modelling and sensing algorithms for environment reconstruction in 6G ISAC networks

Future 6G wireless networks will not only transmit data but will also be able to sense and understand their surrounding environment using the same radio signals. This PhD project will develop new mathematical and physics-informed models and algorithms for Integrated Sensing and Communication (ISAC) systems. 

The research will focus on designing improved channel models and sensing algorithms that better reflect how radio waves interact with real environments. The goal is to move beyond simplified models and purely data-driven approaches by combining physical understanding with modern signal processing and machine learning techniques. 

The outcome will be more accurate, reliable, and efficient methods for tasks such as environment reconstruction, localisation, and adaptive network optimisation. The project sits at the intersection of wireless communications, signal processing, electromagnetics, and machine learning. It includes collaboration with industry partners, providing opportunities to test new ideas using realistic network scenarios and real-world data.

In addition to meeting the minimum entry requirements for our PhD programme, we particularly welcome applicants with strong backgrounds in wireless communications, electromagnetics, signal processing, or applied mathematics. A solid foundation in linear algebra and estimation theory will be advantageous. We are seeking motivated candidates interested in rigorous, interdisciplinary research at the intersection of wireless systems and electromagnetic modelling, with enthusiasm for developing both theoretical frameworks and practical algorithms.

Open to any UK or international candidates. Up to 30% of our UKRI funded studentships can be awarded to candidates paying international rate fees. Find out more about eligibility.