Current research degree projects

Explore our current postgraduate research degree and PhD opportunities.
Explore our current postgraduate research degree and PhD opportunities.
The primary goal of this project is to model the impact of ice build up using computational fluid dynamics.
The projects offered span from fast, empirical tools for aero-engine noise prediction, based on high-fidelity CFD or experiments, to full-aircraft and fleet-level noise modelling. These projects will be conducted within the Rolls-Royce University Technology Centre in Propulsion Systems Noise.
This project will focus on electrolyte design to address critical scientific and engineering challenges in next-generation flow batteries, aiming to understand the relationship among redox couples, electrode materials, transport phenomena, and electrochemical mechanisms. It will develop high-performant semi-organic flow batteries with increased capacity retention.
Respiratory diseases develop progressively. However, current monitoring methods are unsuitable for long-term continuous monitoring. Near-infrared spectroscopy (NIRS) uses light to interrogate the optical properties of tissue. This project aims to develop a wearable system for long-term respiration monitoring using NIRS powered by artificial intelligence (AI) to aid in analysis.
This project will explore the combination of Stacked Intelligent Metasurfaces (SIM) and Orthogonal Time Frequency Space (OTFS) in the next-generation Space-Air-Ground Integrated Network (SAGIN).
Imagine a world where there is Internet access and radar-assisted living and quantum security, wherever there is light. The objective of this project is to implement Integrated Sensing and Communication (ISAC) in visible light bands.
This PhD project will develop advanced ultrasonic array techniques for hydrogen leak detection, localisation and characterisation in complex, noisy environments. Combining mathematical modelling and physics-informed signal processing with AI-driven methods (including PINNs), the research aims to enhance robust, cost-effective leak detection with industrial applications on complex sites.
This project will develop an integrated membrane electrochemical system (MES) for efficient lithium separation and CO₂ capture. By combining advanced membrane materials development with electrochemical process design and optimisation, it aims to deliver a transformative solution for sustainable resource recovery and carbon management.
The objective of this project is to develop a gyroscope using a micron-sized levitated nanodiamond containing nitrogen-vacancy (NV) defects. We will leverage the properties of the NVs to accurately measure particle rotation, overcoming limitations found in other levitated optomechanics platforms with the goal of delivering a competitive levitated micro-inertial sensor.
This project aims to develop machine learning (ML) techniques for processing data collected from an array of hydrophones (underwater microphones). While our team and other international groups have harnessed ML's capabilities for single hydrophone data analysis, there has been limited exploration of the optimal approach for combining information across multiple hydrophones.