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Deadline: 08/04/2026
South West, All England
The Department of Mathematical Sciences at the University of Bath is inviting applications for the following fully funded PhD project/studentship, expected to commence late September 2026.
Supervisors:
Professor Matthew Nunes
Project
Large, multivariate time series arise in a multitude of fields from biology and medicine to social media, cyber security and finance. In many scientific areas, these data are observed on the nodes or edges of a network, or a network structure between time series can be inferred to aid model sparsity and inference. To maximise the potential of such data, there is a need for mathematically rigorous analysis tools which are specifically designed to capture complex data dynamics in different scenarios, giving rise to open methodological and computational problems when developing statistical analysis techniques.
A fully-funded PhD scholarship is available in the area of statistical methodology development for network-structured time series data. The successful student will contribute to developing statistical models of evolving, inter-connected stochastic processes by exploiting information at network nodes and edges. The intended modelling framework includes finding key relationships between time large sets of time series, for applications such as forecasting, detection of anomalous / extreme events, and classification of node/edge states. We will use these new tools to derive impactful insight in a range of scientific and industrial applications.
This exciting opportunity is aligned to the strategic EPSRC-funded research programme on Network Stochastic Processes and Time Series (NeST) which brings together researchers at the Universities of Bath, Edinburgh, Oxford, York, Imperial College London and the London School of Economics and Political Science, with industrial and government partners such as BT, EDF and the Office for National Statistics.
The successful candidate will be working with Professor Matthew Nunes at the University of Bath node, be part of the growing NeST team, and engage in collaboration between institutions.
Applicants should hold, or expect to receive, a First Class or good Upper Second Class UK Honours degree (or the equivalent) in a relevant subject. A master’s level qualification would also be advantageous.
Non-UK applicants must meet our English language entry requirement: https://www.bath.ac.uk/corporate-information/postgraduate-research-degrees-english-language-requirements-for-international-students/
Candidates may be considered for a University of Bath studentship tenable for 3.5 years. Funding covers tuition fees, a stipend (£21,805 p/a in 2026/7) and access to a training support budget.
Informal enquiries are encouraged and should be directed to Professor Matthew Nunes.
Formal applications should be submitted via the University of Bath’s online application form for a PhD in Statistics: https://tinyurl.com/34hd3ckh
IMPORTANT:
When completing the application form:
1. In the Funding your studies section, select ‘University of Bath URSA’ as the studentship for which you are applying.
2. In the Your PhD project section, quote the project title of this project and the name of the lead supervisor in the appropriate boxes.
Failure to complete these two steps will cause delays in processing your application and may cause you to miss the deadline.
More information about applying for a PhD at Bath may be found on our website.
PLEASE BE AWARE: Applications for this project may close earlier than the advertised deadline if a suitable candidate is found. We therefore recommend that you contact the lead supervisor prior to applying and submit your formal application as early as possible.
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Thu 16 Apr 2026