Current research degree projects

Explore our current postgraduate research degree and PhD opportunities.
Explore our current postgraduate research degree and PhD opportunities.
This project explores acoustic scaling between air and water by investigating differences in propeller acoustic radiation in both media. Using full-scale water measurements and partial-scale air measurements, it aims to develop a predictive model for underwater acoustics based on air tests, enhancing our understanding of cross-medium acoustic scaling for propeller noise analysis.
This project aims to develop predictive models for propeller noise generated by in-flow turbulence. It will investigate how background turbulence and upstream obstacles, such as hulls or support structures, impact propeller noise, enhancing our ability to predict and mitigate noise in non-uniform flow environments for improved marine vessel design and operation.
This project focuses on understanding and modelling the vibroacoustic mechanisms of early British pianos. The goal is to create virtual replicas of these historical instruments, with an emphasis on the design of hammers, strings, and soundboards, to preserve and appreciate their original sounds.
The aim of this project is to explore new frontiers in the design of photonics integrated circuits (PICs) by using artificial intelligence (AI). The project has potential to revolutionise chip design and manufacturing processes by reduction of circuit footprint, optimisation of various elements and devices and their integration, and enabling more efficient packaging. It can play a crucial role in shaping the future of PICs and their implementation in various applications.
Minimally invasive brain-machine interfacing (MiBMI) establishes a direct communication pathway between the brain and external devices with minimal disruption to the brain or surrounding tissues. These approaches aim to reduce surgical risks, recovery times, and complications while maintaining or improving the accuracy and functionality of the interface.
In this project you will develop advanced machine learning tools to convert real X-ray measurement data into artefact free 3D images. The work draws on a range of ideas from artificial intelligence, optimization, X-ray physics, applied mathematics and computer science.