Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
348 research degree projects
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Electronics and Computer Science | Photonics and optoelectronics | Engineering | Physics and astronomy
Nanolaser–to–silicon coupling for high-bandwidth optical switching
Join a PhD at the University of Southampton to build optoelectronic neural-networks and hardware for neuromorphic computing. You’ll design, fabricate and test III–V-on-silicon photonic circuits for AI inference and ultra-fast data-links. Learn cleanroom, simulation and characterisation skills in a supportive, world-leading silicon photonics group with industry and international collaborators. -
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. -
Engineering
Crack-to-leak: cryogenic damage mechanisms and fracture toughness of composites for future on-aircraft liquid hydrogen fuel storage
This project aims to understand how carbon fibre composite materials are affected by extremely cold temperatures (around 20 Kelvin, or -253°C), using both experiments and computer simulations. This research is crucial for designing fuel tanks that can safely store liquid hydrogen on aircraft. -
Electronics and Computer Science
Using machine learning to model complex biological interactions
This project aims to build an AI-driven system that analyses live-cell microscopy videos showing how immune cells attack cancer cells. The videos are generated in a biology lab where each experiment can be precisely controlled. You will create machine-learning and computer-vision algorithms that can detect, track, and model these cell-to-cell interactions, revealing patterns that explain when and why immune cells succeed or fail. -
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. -
Engineering
Mathematically scaling the physical impacts of soil bioturbation on bulk scale water flow, gas transport, and mechanical properties in soil
Unlocking how soil’s hidden ecosystem engineers, such as earthworms and roots, reshape its structure could revolutionize sustainable agriculture. This project develops mathematical models linking tiny biopores to large-scale soil behaviour, improving predictions of water flow, gas transport, and mechanical resilience, with vital implications for combating soil compaction and safeguarding global food security.