Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
266 research degree projects
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Electronics and Computer Science
Verifiably sustainable AVs: formal methods for safety, trust, and resilience
The aim of this project is to explore how mathematical modelling and verification techniques (formal methods) can be used to prove that autonomous vehicle systems are safe, trustworthy, and resilient. -
Electronics and Computer Science
Creating explainable AI for health with confidence
This project will develop advanced machine learning methods to transform heterogeneous, routinely collected medical data into explainable, uncertainty-aware insights for healthcare decision-making. Combining multimodal data, longitudinal modelling, and personalised uncertainty quantification, the project tackles critical challenges in digital health, improving disease prediction, monitoring, and communication of confidence in clinical decisions. -
Electronics and Computer Science | Mathematical sciences
Responsibility reasoning in multiagent systems
The aim of this project is to develop formal models of accountability and liability using logic, game theory, and agent-based simulation. You will explore responsibility under uncertainty, delegation, and trust, with applications in autonomous systems, digital governance, and ethical AI. -
Electronics and Computer Science | Engineering
Smart materials for wearable electronics with next-gen manufacturing
This project offers a rare opportunity to work with the UK’s only roll-to-roll sputtering system, a brand new and bespoke platform designed specifically for next-generation material discovery. You’ll explore innovative thin-film materials for flexible electronics, developing scalable recipes that bridge cutting-edge research with real-world commercial compatibility through high-throughput, fabric-friendly processes. -
Engineering
Development of high-performance miniaturised ultrasonic devices for precision minimally invasive surgery
This project, in the field of ultrasonic surgery, focuses on the development of cutting-edge miniature ultrasonic devices targeted for bone surgery. It seeks to advance the current state-of-art design by introducing new configurations and incorporating novel structures in miniaturised devices to enhance precision and improve clinical outcome. -
Biological sciences
Microbiologically Influenced Corrosion Associated with Marine Fouling
Microbiologically-influenced corrosion and biofouling in hostile marine and offshore energy sectors costs billions annually. This project advances in-situ spatial biofilm analyses to map microbe–surface interactions and develops data-driven genome-scale metabolic models. Combining genomic, electrochemical, and imaging techniques, it will predict and control biofilm-mediated structural corrosion through novel natural mitigation strategies. -
Electronics and Computer Science
Predicting chaotic behaviours for financial risk analysis
The analysis of financial risk relies on chaotic systems, which are difficult to predict due to their sensitivity and complexity. In this project, you will build on existing machine learning research to create effective prediction approaches, and work alongside experts in chaos modelling, machine learning, and finance to achieve this. -
Electronics and Computer Science
Application mapping on parallel compute systems
Massively parallel compute architectures, like Graphics Processing Units (GPU) and Field-Programmable Gate Arrays (FPGA), are becoming an integral part of the high-performance computing ecosystem. This project is about effective mapping of large parallel problems onto these architectures, improving the optimised performance of numerical simulations and artificial intelligence. You will access leading supercomputer resources to achieve this. -
Engineering
Development, optimisation, and validation of µCT-based 3D X-ray histology for advanced clinical and biomedical applications
This project aims to develop cutting-edge 3D X-ray imaging methods to improve histopathology and tissue diagnostics. It will advance non-destructive µCT -based imaging of histological specimens to guide sampling, reduce diagnostic error, and support spatial -omics. Based at the interface of engineering and medicine, this project combines imaging science, pathology, and translational biomedical research. -
Engineering
Hybrid turbulence modelling: bridging physics and data
This project pioneers deep learning for turbulence modeling, focusing on wall-bounded flows. By combining convolutional neural networks (CNNs), generative adversarial networks (GANs), and physics-informed methods, it aims to develop hybrid predictive models that overcome current limitations. The research supports scalable, accurate simulations of multi-scale phenomena, advancing computational design across energy, transport, and biomedical applications.