Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
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271 research degree projects
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Electronics and Computer Science | Engineering
Designing low-power digital integrated circuits for machine learning based signal processing
There is a growing demand for high-throughput and low-power signal processing in implantable devices. Traditional DSP engines struggle with this need, while compact AI models can offer better accuracy with smaller code sizes. Efficient implementation on silicon can allow small components to run effective machine learning algorithms with minimal power use. -
Engineering
Turbulent boundary layers in realistic conditions
This project aims to carry out state-of-the-art experiments to generate new data that will transform our understanding and predictive approaches for turbulent boundary layers in realistic conditions. Understanding and modelling these flows are increasingly important for innovative technologies in transportation, energy, and environmental sectors. -
Photonics and optoelectronics
Optoelectronic backplane for computing and quantum applications
The aim of this project is to build the next generation of optical backbone for artificial intelligence (AI) hardware, computing and quantum technologies. You’ll design, fabricate and test silicon photonic circuits for ultra-fast data-links, gaining hands-on experience in cleanroom processes, simulation and characterisation within a world-leading silicon photonics group and in collaboration with industry partners. -
Engineering
Using vibration to explore human balance function
A well functioning balance (vestibular) system is essential for everyday life. When illnesses affect vestibular function it can be very disabling. This project aims to use world leading vibration test facilities to apply controlled motions to humans with the aim to test and improving understanding of the human balance system. -
Electronics and Computer Science
Adversarial defence for Large Language Models (LLMs)
Large Language Models (LLMs) are powerful but can be tricked - Adversarial Defence protects them. You will improve LLM robustness to prompt-based attack or jailbreaking, exploring novel algorithms for adversarial defence inspired by recent success of adversarial pre-prompt training, reinforcement learning from human feedback (RLHF) and adding safety layers to LLM architectures. -
Electronics and Computer Science
Metasurface technology for next-generation automotive sensing and 3D facial recognition
This project will develop metasurface-engineered optical systems for next-generation automotive and biometric sensing. It combines advanced nanofabrication, machine learning-driven optical design, and international collaboration with NTU Singapore and MIT to push metasurface technologies toward real-world commercialisation. -
Engineering
Investigating urban blast effects and injury risk through numerical and experimental techniques
This project investigates how urban environments influence injury risk during explosions. Using advanced computational fluid dynamics (CFD) modelling, analytical methods, and small-scale blast experiments, it will reconstruct the 2020 Beirut explosion and extend findings to generic urban settings to develop validated models and guidance that enhance human protection and urban resilience. -
Engineering
Recovering precipitation strengthening in additive friction stir deposition builds: heat-treatment design for microstructure control and property improvement
This project aims to unlock stronger 3D-printed metals. It pioneers new heat-treatment strategies to recover and even surpass the strength of additively manufactured light alloys. Using advanced microscopy, modelling and mechanical testing, you’ll design process–microstructure-properties maps that transform low-strength printed parts into high-performance components for aerospace, transport and hydrogen technologies. -
Engineering
The sentient hearing aid: engineering a symbiotic link between mind and machine
Millions struggle with "hidden hearing loss." Pilot data from our lab shows a disconnect between the brain's effort and listening success. This project will engineer a "sentient" hearing aid that reads the user's unique physiological signature of effort to intelligently adapt its sound processing in real-time. -
Electronics and Computer Science
Risk management for robust Machine Learning Operations (MLOps)
MLOps refers to the processes for developing and maintaining machine learning systems. Robust MLOps ensure reliability under uncertainty, adversarial conditions, and distributional shifts. Given the massive growth of ML-based projects across scientific fields, effectively managing risks to MLOps robustness has become non-negotiable.