Probability, Statistics and Data Science PhD Project
PhD projects in the Centre for Probability, Statistics and Data Science
The Centre for Probability, Statistics and Data Science covers three broadly overlapping main areas of research: probability, statistics and data science. Probability theory is a core topic within mathematics and a foundational aspect in much of the work of the centre. A broad range of areas within probability and applied probability are investigated from stochastic processes, understanding the properties of random mathematical structures including many applications to areas such as statistical physics, finance, etc. The centre also has a strong group of statisticians developing both statistical theory, e.g. Bayesian inference, methodologies, e.g. modelling of spatio-temporal data, and applications, e.g. biostatistics. Finally, the centre has in expertise of other aspects of data science including the foundations of machine learning, solving inverse systems as related to data, topological techniques, and others.
The Centre (PSD) also welcomes applications year-round from students with alternative sources of funding, such as self-funding, Doctoral Loans, Commonwealth scholarships, or other funding options. Contact the relevant academic to discuss projects alternatively if you are considering a PhD using funding not listed below, we encourage you to contact the relevant academic to discuss potential projects.
The following projects are currently open to applicants and will be considered on a rolling basis for interview and offer:
| Project Title | Supervisor | Funding | Start Date | Application Deadline |
|---|---|---|---|---|
| The Topology of Hyperuniform Processes |
Omer Bobrowski / Primoz Skraba |
CSC | Sep 2026 | 28 Jan 2026 |
| Empowering Causal Inference with Functional Data Analysis | Nicolás Hernández | New Talent/CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Advanced Inference methods for High-Dimensional and Functional Data | Nicolás Hernández | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Signature-Based Forecasting of Functional Time Series | Nicolás Hernández | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Advanced Modelling and Forecasting of Functional Time Series | Nicolás Hernández | CSC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Scalable and Adaptive Statistical Modelling for Environmental DNA Surveys of Biodiversity in China | Eleni Matechou / Silvia Liverani | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Integrating AI and Statistical Ecology: Bridging Automated Photo-Recognition and Inference of Population Demographics | Eleni Matechou / Kostas Papafitsoros | EPSRC/Underrepresented | Sep 2026 | 28 Jan 2026 |
| Toric spaces from finite posets | Amaranta Membrillo Solis | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Applications and modelling of high-dimensional time series | Alexander Shestopaloff | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Causal Machine Learning Methods for Complex Imaging Data | Eftychia Solea / Nicolás Hernández | CSC/EPSRC/Underrepresented/Self-Funded | Sep 2026 | 28 Jan 2026 |
| Low-rank function approximations for high-dimensional financial risk management | Linus Wunderlich | EPSRC/UnderRep | Sep 2026 | 28 Jan 2026 |
Check our Fees and Funding page for details about these studentships.