Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
283 research degree projects
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Engineering
Prediction of propeller noise in the presence of in-flow turbulence
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. -
Engineering
Developing magnetohydrodynamic (MHD) accelerator for a dual-stage pulsed plasma thruster
This project aims to develop a high-performance, low-cost propulsion system for CubeSats, enhancing manoeuvrability and mission longevity. Building on the All-Printed Propulsion System (ALPS) concept, this research will explore plasma acceleration using electric and magnetic fields, enabling a dual-stage propulsion system for improved thrust and efficiency in micro- and nanosatellite applications. -
Engineering
Investigating the ablation of hypersonic re-entry object and its global climate effect
This project investigates the environmental impact of spacecraft re-entry, focusing on material ablation and its effects on ozone chemistry and Earth’s radiative balance. Using high-fidelity computational models, molecular dynamics, and atmospheric simulations, this research will enhance sustainability in space activities by assessing the long-term consequences of satellite disposal practices. -
Electronics and computer science
Enhancing research software recognition and provenance in scholarly publishing
This project will explore themes in artificial intelligence (AI), machine learning, and provenance data to analyse research software development, verify contributions, and enhance peer review transparency. Supervised by experts and supported by leading institutes, this project offers the chance to shape how research software is evaluated, credited, and integrated into academia. -
Engineering
Data-driven density modelling (D3M) for orbit prediction using machine learning and data assimilation
The aim of this project is to develop a responsive high-fidelity atmospheric density model that can be updated with additional observation data from satellite tracking for use in precise orbit prediction. -
Engineering
Development of innovative miniature ultrasonic surgical devices for robot-assisted surgery
This project aims to develop innovative miniature ultrasonic devices specifically designed for bone surgery. It aims to advance the current design by introducing innovative configurations, incorporating novel structures in miniaturized devices, and integrating them with surgical robotics to enhance precision and improve clinical outcomes. -
Electronics and computer science
Decolonising AI: Building Culturally Aware Multimodal AI
This project develops next-generation Vision-Language Models (VLMs) sensitive to cultural diversity, addressing critical biases in current AI systems. Current VLMs often perpetuate harmful stereotypes due to their training data. This research investigates how cultural biases manifest in VLMs and develops innovative mitigation techniques, leading to more inclusive and equitable AI. -
Physics and astronomy
Phase transitions in quantum materials
Twisted layers of 2D materials allow for new degrees of freedom in quantum matter, leading to novel phenomena such as unconventional ferroelectricity, superconductivity and topological states. This project explores physics of these phase transitions in suspended membranes, measured by advanced nanomechanical and optical probes, to reveal complex phase diagrams within these unique systems. -
Physics and astronomy | Photonics and optoelectronics
Water-based THz optoelectronics
This PhD project aims to explore the role of quantum electronic coherence in photo-excited water samples and develop new kinds of liquid-based devices for wireless terahertz (THz) communication. -
Engineering
Novel fluidic topology optimisation methods for gas turbine design
This project seeks to develop novel fluidic topology optimisation approaches for gas turbine component design by leveraging cutting edge machine and deep learning methods alongside computational fluid dynamics, ultimately aiming to revolutionise the solution of aerodynamic design problems.