About the role:
Applications are invited for 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, Edinburgh, 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 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.
What you would be doing:
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/or underpinning theory, in response to real applied problems spurred by dynamic networks in many contexts.
Initially, you will be attached to one or two research projects led by one or two Imperial College investigators (Ed Cohen, Nick Heard, Guy Nason or Almut Veraart; and line managed by one of them). As part of the NeST team, you will have access to, and potential opportunities to work with a larger team consisting of additional academics (Marina Knight, Matt Nunes, Gesine Reinert, Patrick Rubin-Delanchy 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.
What we are looking for:
- The role requires a candidate with a PhD in Statistics, Applied Probability or a closely related discipline (or soon to be acquired)
*Candidates who have not yet been officially awarded their PhD might be appointed as Research Assistant
- Practical experience within a research environment and / or publication in relevant and refereed journals
- Advanced knowledge in advanced statistical methodologies
- Advanced programming knowledge, preferably in R, Python or MATLAB
- Ability to organise own work with minimal supervision
- Willingness to work as part of a team and to be open-minded and cooperative.
What we can offer you:
- The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity
- Grow your career: Gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression
- Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
Further Information
This is a full time and fixed term role for 24 months based at the South Kensington Campus.
