Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
288 research degree projects
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Engineering | Electronics and computer science
Machine learning for multi-channel underwater acoustic data
This project will develop machine learning (ML) techniques for processing acoustic data from sensor arrays, allowing the enhancement of signals and localization of sound sources. While ML has been used for single sensors, this project will create new methodologies for processing data from multiple sensors, improving underwater acoustic analysis. -
Electronics and computer science | Engineering
Sustainable polymer solutions for high-performance power electronics in wind energy systems
This project develops advanced and sustainable polymer materials for power electronic inverters in wind energy systems. By combining nanocomposites, cross-linked networks, and bio-based polymers, it aims to enhance thermal, electrical, and mechanical performance, supporting the creation of more reliable, efficient, and environmentally friendly renewable energy infrastructure. -
Engineering
Prioritized management strategies for power assets using machine learning
This project 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. It offers a unique opportunity to drive progress in flexible energy-harvesting technologies and to address contemporary challenges associated with expanding technologies and innovative applications. -
Electronics and computer science | Engineering
Integrating innovative sensors and artificial intelligence to reduce emissions in maritime shipping and aviation
The goal of this project is to create a predictive sensing methodology, leveraging AI-driven analytics to provide detailed temporal and spatial flow characteristics. -
Medicine
Investigating immune responses to controlled human infection with Bordetella pertussis using multi-omics
Pertussis is an infectious disease caused by the bacterium, Bordetella pertussis. Disease can occur across the life course but is most significant in children under the age of 1 year where serious, life-threatening complications may occur. Unfortunately, pertussis has resurged globally despite high vaccine coverage. In order to better control this disease, new vaccines are required that induce long-lasting protection and generate herd immunity. -
Engineering | Medicine | Biological sciences
Ultra-high speed imaging based organotypic and hydrogel model for ultrasound stimulated bone and soft tissue
This project aims to validate the hypothesis that ultrasonic surgical tools can both limit cell damage at the site of cutting and stimulate tissue healing in regions remote from the surgical tip. This is achieved using ultra-high speed imaging based organotypic and hydrogel models for ultrasound-induced effects on bone and soft tissue. -
Electronics and computer science | Engineering
Reliable and sustainable overhead line equipment for rail electrification
This project will study how overhead line equipment in existing rail networks ages and deteriorates over time when exposed to stronger electric fields and more extreme weather conditions. -
Electronics and computer science
AI for sustainability
This 4-year integrated programme (iPhD) focuses around 5 research themes where AI can improve environmental sustainability:sustainable operations and circular economyAI for transportation and logisticsAI for sustainable energy and buildingsAI for the natural environmentsustainable AI -
Engineering
Modelling gust-wing interactions in curvilinear flows
This project will explore gust-wing interactions in curvilinear flows, focusing on vertical axis wind turbines (VAWTs). It offers a unique opportunity to develop expertise in computational fluid dynamics (CFD), data-driven modelling, and experimental aerodynamics while addressing a critical challenge in renewable energy, such as gust-wing interactions in curvilinear flows.