Current research degree projects

Explore our current postgraduate research degree and PhD opportunities.
Explore our current postgraduate research degree and PhD opportunities.
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.
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.
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.
This PhD project builds on a newly funded NIHR research aiming at predicting response to methylphenidate (the most common medication for ADHD), based on pre-treatment clinical, cognitive, and physiological characteristics. Ultimately, this will help tailor treatment options and thus improve patients’ outcomes.
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.
Modern lightweight space structures face harsh environments and often exhibit nonlinear dynamics due to contacts, friction, and geometric nonlinearities. This project combines numerical, analytical, and experimental methods to develop physics-informed machine learning tools for efficient nonlinear system identification, enabling accurate modelling and validation of the next-generation space technologies.
The Department of Aeronautical and Astronautical Engineering at the University of Southampton is offering PhD scholarships focused on using active thermography to inspect aerospace composites. The project aims to improve how defects are detected and analysed in aircraft materials, helping ensure safer and more efficient maintenance.