Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
174 research degree projects
-
Engineering
Ultrasonic drilling for minimally invasive assessment of inhomogeneous damage in degraded concrete
This project aims to develop a robot-integrated ultrasonic drilling system for minimally invasive, high-resolution assessment of inhomogeneous damage in degraded concrete. By combining ultrasonic sensing and force measurement during drilling, the system enables real-time subsurface characterization in extreme environments such as underwater or post-fire, supporting safer infrastructure inspection and maintenance. -
Electronics and Computer Science | Engineering
AI-assisted design of intelligent antimicrobials for gastrointestinal disease treatment
This project aims to develop AI-driven, metal-based smart antimicrobials targeting gastrointestinal infections and antimicrobial resistance. You will use cutting-edge AI drug design and microfluidic organ-on-a-chip technology for rapid, animal-free drug screening. -
Engineering
Intelligent electrical impedance matching for ultrasonic surgical devices under varying load conditions
This project aims to investigate the effect of varying excitation and loading on the change of electrical impedance of the ultrasonic surgical devices during tissue cutting. It also seeks to implement intelligent and self-adaptive control algorithm. The goal is to achieve a state of autonomously matched impedance between the load and the ultrasonic resonance tracking system. This will help maximise the ultrasonic energy transmission efficiency. -
Engineering
Aero-engine and aircraft noise research: multiple opportunities from multi-fidelity modelling to community impact
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. -
Engineering
Rapid alloy discovery and characterisation of additively manufactured Type 316 stainless steel and its advanced variants
This project aims to accelerate bulk alloy discovery for additive manufacturing by leveraging smart design and 3D printing of material libraries to dramatically increase the throughput of characterisation and testing. Integrated with AI-assisted workflows, the project will streamline data curation and enable rapid exploration of structural material systems. -
Electronics and Computer Science | Engineering
Stacked Intelligent Metasurface (SIM) for Orthogonal Time Frequency Space (OTFS)
This project will explore the combination of Stacked Intelligent Metasurfaces (SIM) and Orthogonal Time Frequency Space (OTFS) in the context of Space-Air-Ground Integrated Network (SAGIN) applications. -
Electronics and Computer Science | Engineering
Visible Light Integrated Sensing and Communication (VL-ISAC)
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. -
Electronics and Computer Science | Engineering
Prioritized management strategies for power assets using machine learning
This research project within the ‘Doctoral Centre for Advanced Electrical Power Engineering’ aims to develop a criticality ranking system for power grid assets using data-driven approaches. By applying machine learning and statistical models, it prioritizes high-risk assets, enabling proactive decisions, optimised resource allocation, enhanced maintenance efficiency, and improved grid reliability. -
Electronics and Computer Science | Engineering
Soft materials for ambient energy scavenging applications
This project aims to develop advanced flexible materials used as dielectric elastomer transducers (DET) in energy harvesting applications. As part of the Doctoral Centre for Advanced Electrical Power Engineering, your research will seek to maximise DET efficiency in converting energy naturally available in the surrounding environment into sustainably sourced, electricity. -
Engineering | Electronics and Computer Science | Mathematical sciences | Physics and astronomy
Modelling gust-wing interactions in curvilinear flows
This PhD project will explore gust–wing interactions in vertical axis wind turbines (VAWTs). Integrating computational fluid dynamics, data-driven modelling, and experiments on a custom-built VAWT rig, you will examine how gusts influence blade aerodynamics in curvilinear flows and develop predictive tools to mitigate their adverse effects.