Bayesian Modeler in Flood Risk Assessment
We are seeking a highly skilled Bayesian modeler to join our project on flood risk assessment.
About the Project:
The project aims to 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 various sources, and a statistical emulator of an expensive hydrological flood prediction model, calibrated using observational data.
Key Responsibilities:
* Develop and implement computationally intensive Bayesian inferential methods for real-time forecasting of localised rainfall and flood prediction risk.
* Design and build efficient programs for statistical computing using R and a compiled language like C/C++ or Java/Scala.
Requirements:
* 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
* Excellent statistical computing skills, including familiarity with modern statistical tools and libraries
* Strong written and oral communication skills
* Effective time management skills