Ra In Bayesian Modelling Of Flood Risk

8 hours ago

Sydney, New South Wales, Australia The International Society For Bayesian Analysis Full time

D74668R – Research Assistant/Associate (Statistical Modeller)
School of Mathematics & Statistics
Newcastle University, U.K.
maths
Closing date: 12 July 2017
We are seeking to appoint a Research Associate in Statistics to the 4-year Natural Environment Research Council funded "Highlights" project, Flood-PREPARED: Predicting rainfall events by physical analytics of real-time data.
The project is made up of a research team from Newcastle University who will develop an international leading capability for real-time surface water flood risk and impacts analysis for cities.
The appointed researcher will devise a space-time model for rainfall that can integrate data from a variety of sources, and a statistical emulator of an expensive hydrological flood prediction model, calibrated using observational data.
They will develop and implement computationally intensive Bayesian inferential methods that allow real time forecasting of localised rainfall and flood prediction risk.
Applicants must have a PhD in Statistics or a closely related discipline (awarded or in submission); expertise in Bayesian inference and computationally intensive inferential methodology; track record of research in computational Bayesian statistics and developing efficient programs for statistical computing.
They must have excellent statistical computing skills, including familiarity with modern statistical tools and libraries; strong programming skills in R and an efficient compiled language like C/C++ or Java/Scala; excellent written and oral communication skills and skills in effective time management.
The post is full time and fixed-term for 36 months.
Informal enquiries can be made to Professor Darren Wilkinson () or Dr Sarah Heaps ().
Further details, including the application procedure, can be found here:
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