Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
343 research degree projects
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Photonics and optoelectronics
A Quantum Leap for Quantum Technology
Take a Quantum Leap into the Future of PhotonicsAre you passionate about quantum technologies and cutting-edge photonics? Join the Hollow Core Fibre Group at the University of Southampton, in collaboration with Microsoft Azure Fiber, to help shape the future of quantum computing and communication. -
Engineering | Mathematical sciences | Geography and environmental science
High-fidelity simulations of wind and dispersion over a city-scale urban area
We live in a rapidly changing world. It is crucial that we understand such a complex system and build reliable predictive tools in time. The computational fluid dynamics (CFD) model includes buildings and abrupt terrains in a city-scale environment. It aims to understand across-scale physical processes with a focus on metre to kilometre scales and develop a fast CFD tool. -
Photonics and optoelectronics
Shaping the Future of Global Communications with Hollow Core Fibres
Are you a graduate in physics, engineering, materials science, chemistry, or a related discipline? Do you want to be part of a technological revolution that could redefine how the world communicates? Join our cutting-edge PhD project at the Optoelectronics Research Centre (ORC) - in collaboration with Microsoft Azure Fiber -
Engineering
Multi-level topology optimization of architected metamaterial structures
Mechanical metamaterials are engineered structures with extraordinary properties driven by geometry, not composition. This PhD project will pioneer a multi-scale framework combining topology morphing and surrogate modeling to streamline design and enable defect engineering, unlocking real-world metamaterial applications in ultralight, reconfigurable, and high-performance materials. -
Electronics and Computer Science
AI-generated content detection and localization
In a world increasingly dominated by AI-generated content, this PhD project will research advanced AI methodologies for detection and localization of manipulated imagery. You’ll push the frontiers of computer vision and data forensics, creating tools that strengthen digital authenticity, security, and global trust in visual information. -
Engineering
Investigation of thermoacoustic instabilities of hydrogen flames
Hydrogen offers a clean route to decarbonise aviation, but its flames can be prone to thermoacoustic instabilities, which are undesirable in aviation engines. This project investigates these instabilities in hydrogen jets-in-crossflow, an important configuration for efficient mixing and stable low-carbon combustion. -
Engineering
Broadband noise control using synergetic poroelastic acoustic metamaterials
Become a pioneering researcher in new noise control technologies based on acoustic metamaterials to tackle noise pollution, a growing problem which negatively affects the health and productivity of millions of people. -
Engineering
Development of memristor artificial synapses for neurorehabilitation
This project aims to develop next-generation mind-controlled prosthetics and exoskeletons using memristor-based neuromorphic interfaces that emulate human synapses. You'll design, nanofabricate, and characterize these artificial synapses, establishing the foundational building blocks for advanced neurorehabilitation technologies -
Engineering
Physics informed neural networks as an environmentally friendly alternative to CFD
Physics-Informed Neural Networks (PINNs) provide an innovative, efficient alternative to traditional methods employed in fluid dynamics simulations, delivering Computational Fluid Dynamics (CFD)-level of accuracy at significantly lower computational costs, thus reducing energy use and benefiting the environment. -
Electronics and Computer Science | Engineering
Brain-inspired security primitive for secure hardware in space
Memristors mimic how the brain learns—offering low-cost, secure, and energy-efficient computing. This PhD tackles challenges limiting their adoption, from ageing to variability, to create unforgeable, self-identifying chips.