Research Associate in Monitoring Complex Systems with Rare High Consequence Events: Methodology for Rare Event Prediction and Monitoring Workstream

Imperial College London - Statistics Section, Department of Mathematics

South Kensington Campus and The Alan Turing Institute

Fixed Term: 3 years with the possibility of extension

Starting Date: Negotiable, ideally by 1 January 2018.

The Statistics Section is seeking a Research Associate to work in the area of Data-Centric Engineering. The position is funded through the Lloyd’s Register FoundationAlan Turing Institute Programme on Data-Centric Engineering. The Research Associate will work directly with Professor Axel Gandy and Dr Almut Veraart, and will join a vibrant Statistics Section at Imperial College London as well as the Data Centric Engineering team at the Alan Turing Institute. The position will be physically based at the Alan Turing Institute, headquartered at the British Library, London.

The Statistics Section of the Department is consistently rated one of the top in the country for research. We have 18 permanent faculty and research expertise in diverse areas including: Signal Processing, Statistical Theory, Applied Probability, Bayesian Methods and Computation, Machine Learning, Big Data and Astrostatistics. Currently we have over 40 PhD students and RAs in the Section who contribute to a young and dynamic environment. We believe we offer a world class training environment for post-doctoral researchers.

The project is for the methodology stream of the Grand Challenge on Monitoring Complex Systems with Rare High Consequence Events and aims to develop statistical methodologies and mathematical methods to characterize, estimate and extrapolate extremal dependence in multivariate, spatial, spatio-temporal and network settings.

You will have a PhD degree, or an equivalent level of professional qualifications and/or experience, in Statistics. You must have working experience in one or more of: statistical modelling, data science, stochastic processes or extreme value theory. A background and proven knowledge of data processing and analysis and computational statistics e.g. handling time series data, spatio-temporal data, numerical optimization, Monte Carlo and bootstrap methods are essential. You will also have a record of achievement, including publications, in a relevant research field that is commensurate with your experience. 

In addition, you will have the demonstrated ability for independent research, and be able to work effectively as part of a team. You will have the ability to develop and apply new concepts, and have a creative approach to problem solving. You must be able to demonstrate excellent verbal and written communication skills, be able to interact effectively with a wide range of people, and be able to learn and teach new skills. You will also be able to write clearly and succinctly for publications.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £32,380 - £34,040 per annum.

For additional information please contact Professor Axel Gandy ( or Dr Almut Veraart (

Our preferred method of application is online via our website: (Please select “Job Search”, then enter the job title or vacancy reference number NS2017149LH into “Keywords”). Please complete and upload an application form as directed, also providing a CV and a list of publications, and the names of three referees.

Should you have any queries regarding the application process, please contact Mr. Thomas Brain, Research Liaison Officer, Email:

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