PhD Scholarship in Network Data Science, Dept. of Mathematics, University of York, UK

A full PhD Scholarship is available in the area of statistical learning for network-structured data. There has been a recent explosion in the availability of network data, arising across a multitude of fields from biology and medicine to social media, cyber security and climate science. Your research will contribute to efficient modelling and forecasting of evolving, inter-connected stochastic processes by exploiting simultaneously collected information across network nodes and edges, and integrating their dynamic statistical properties. You will use the techniques you develop to maximise insight in scientific and industrial applications.

This exciting opportunity is aligned to the strategic EPSRC-funded research programme on _Network Stochastic Processes and Time Series (NeST, see which brings together researchers at the Universities of York, Oxford, Bath, Bristol, 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.

You will be working with Prof. Marina Knight at the University of York node, be part of the growing NeST team and engage in collaboration between institutions.

Applications are invited from students who aim to commence their PhD studies during 2024. Full funding is available for UK students and those qualifying for home-fee status. Partial funding is available for students not qualifying for home-fee status. Applicants should hold, or be close to completing, an Honours undergraduate degree or a Masters degree in Statistics, or a closely related field. You should be self-motivated, with a keen interest in developing methodological and computational statistical techniques in answer to practical problems, backed up by demonstrably strong mathematical/statistical and programming skills.

To apply, please send your CV with academic transcripts and a cover letter to Prof. Marina Knight (

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