Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
Explore our current postgraduate research degree and PhD opportunities.
In the wake of growing data privacy concerns and the enactment of the GDPR, Federated Learning (FL) has emerged as a leading privacy-preserving technology in Machine Learning. Despite its advancements, FL systems are not immune to privacy breaches due to the inherent memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital.
This PhD project might be for you if you are concerned about the growing microplastic contamination in our water bodies.
In this project, you will push the boundaries of our understanding of extreme neutron star physics, developing your own research ideas and building expertise in AI and large-scale data science. You will apply machine-learning and data science techniques to discover anomalies in vast data sets of radio pulsar observations, and use these to understand how neutron stars evolve over their lifetimes.
Supermassive black holes live in the centre of galaxies and grow by the accretion of gas from their surroundings. This process of black hole growth occurs throughout the evolution of the Universe and powers some of the most spectacular and energetic events we can observe: Active Galactic Nuclei.
Are you excited to develop innovative solutions to revolutionize the development of high-speed aircraft? Do you want to work in an environment that encourages you to guide your own career through exposure to a diverse set of novel, open-ended problems working in a multidisciplinary team?We're looking for motivated, creative thinkers who can help develop solutions to the toughest challenges in aircraft development today.
This project aims to develop a real-time in-situ plasma measurement payload for CubeSats. This payload will enable CubeSats to measure the characteristics of their space environment in real time, providing crucial information about interactions that could cause failure and possible ways to mitigate them.
This project focuses on advancing the trustworthiness and usability of multi-robot systems, particularly in the context of swarm robotics.
This project will be observationally driven and you will have proprietary access to two new spectroscopic survey datasets from the 4MOST spectrograph on the ESO VISTA telescope, and the MOONS spectrograph on the Very Large Telescope, which are due to begin observations in 2025.
This project aims to answer the questions of how supermassive black holes (SMBHs) grew through cosmic time and how they interacted with the growth of their galaxies.
Modern all-sky astronomical surveys have started detecting unusual, extremely luminous, and long-lived flares in the centres of distant galaxies. These flares are too bright to be caused by the death of a single star and are more likely the result of a violent accretion of material onto a supermassive black hole. This project aims to uncover what that material is and how it gets there, which is key to understanding how black holes grow.