Applications are invited for several (5) Postdoctoral Research Associate positions in Network Data Science, Statistics and Probability to work on an EPSRC-funded programme on Network Stochastic Processes and Time Series (NeST).NeST brings together the Universities of Bath, Bristol, Imperial College London, the London School of Economics and Political Science, Oxford and York, with industrial and government partners BT, EDF, the GCHQ, the Office for National Statistics, Microsoft, Royal Mail, Securonix and FNA. Stochastic network data are of rapidly increasing ubiquity in many fields such as medicine, transportation, cybersecurity, the environment, finance, biology and economics, and NeST aims to achieve a step change in the modelling and prediction of evolving, inter-connected stochastic network processes.
As part of the NeST team, you will contribute to realising a substantial coordinated push to create, develop and apply innovative new models, computational techniques and underpinning theory, in response to real applied problems spurred by dynamic networks in many contexts.
For the role advertised at the University of York, initially you will be attached to two research projects and be line managed in the Department of Mathematics by Prof. Marina Knight. As part of the NeST team, you will have access to, and potential opportunities to work with a larger team consisting of academics (Ed Cohen, Nick Heard, Guy Nason, Matt Nunes, Gesine Reinert, Patrick Rubin-Delanchy, Almut Veraart and Qiwei Yao) collectively covering a wide range of research in NeST areas, and a growing cohort of postdoctoral and PhD student colleagues spread over the constituent universities.
Projects that are available for this round of positions are P2 Modelling and Forecasting Dynamic Networks via their Edges (Lead/Line Manager: Knight, Yao/Marina Knight. Location: York. Team partners Heard, Nason, Nunes); P4 Dynamic Graph Embeddings: Procedures and Inference (Lead/Line Manager: Heard, Rubin-Delanchy/Nick Heard. Location: Imperial, London. Team partners: Knight, Nunes, Yao); P5 Network Count Processes (Lead/Line Manager: Ed Cohen. Location: Imperial, London. Team partners: Heard, Knight, Nason, Nunes Veraart); P6 Novel Long-Memory Spectral Domain Modelling for Network Data (Lead/Line Manager: Knight, Nunes/Matt Nunes. Location: Bath. Team partners: Cohen, Nason, Veraart); P7 Network Time Series in Continuous Time: Modelling and Estimation (Lead/Line Manager: Almut Veraart. Location: Imperial, London. Team partners: Cohen, Knight, Nason, Nunes, Reinert). P8 Novel Network Time Series Models with Application to Advanced Modelling and Prediction of Government Flow Data Sets (Lead/Line Manager: Nason, Nunes/Matt Nunes. Location: Bath).
See Job Description for further details of these projects. The role responsibilities and requirements are listed in the Job Description.
While there is a clear expectation of collaboration for the Postdoctoral Research Associates across projects and universities, please do indicate clearly in your application cover letter the institutions for which you would like to be considered, including your preferred choice. The available institutions for this round are Bath, Imperial College London and York.
If you are interested in more than one project at more than one location, then please apply to every project/institution that you are interested in using the links found at
Since each position will contribute to the global success of the NeST programme, we will share the applications across the hiring institutions.
This role is primarily for Project P2 Modelling and Forecasting Dynamic Networks via their Edges (Lead/Line Manager: Knight, Yao/Marina Knight. Team partners Heard, Nason, Nunes). You will also be involved in Project P6 Novel Long-Memory Spectral Domain Modelling for Network Data (Lead/Line Manager: Knight, Nunes/Matt Nunes. Location: Bath. Team partners: Cohen, Nason, Veraart).
For informal enquiries for the role at York: please contact Prof. Marina Knight by email email@example.com
The position is full-time, initially for 24 months. The successful candidate is expected to take up the position as soon as possible, but ideally before October 2023 for the right candidate.
The salary is on the University of York Grade 6 for the Research Associate position. All applicants with a relevant background and research skills are eligible to apply.
Please apply by completing the online application associated to this advert.
Closing date: 7th May 2023
Provisional interview timeline: candidates will be invited to a face-to-face interview at their chosen institution(s) in the interval 29th May to 9th June 2023. Offers will be made only after interviews across all institutions have taken place.
The University strives to be diverse and inclusive – a place where we can ALL be ourselves.
We particularly encourage applications from people who identify as Black, Asian or from a Minority Ethnic background, who are underrepresented at the University.
We offer family friendly, flexible working arrangements, with forums and inclusive facilities to support our staff. #EqualityatYork
York is one of the most successful universities in the UK.
With world-class activity across the spectrum from the physical sciences, life sciences, and social sciences to the humanities, we have been recognised as one of the top 100 universities in the world, gaining outstanding results in official assessments of our research and teaching.