Flood Risk Modelling Expert
We are seeking a skilled researcher to join our project at the School of Mathematics & Statistics. The successful candidate will be part of a 4-year initiative funded by a leading research council.
The goal of this project is to develop an advanced system for real-time surface water flood risk analysis for cities. As a key team member, you will devise a space-time model for rainfall that integrates data from various sources, and develop a statistical emulator of an expensive hydrological flood prediction model.
You will apply computationally intensive Bayesian inferential methods for real-time forecasting of localized rainfall and flood prediction risk. A strong background in Bayesian inference, computational statistics, and programming skills in R and C/C++ or Java/Scala is essential.
This is a full-time position for 36 months. You will have the opportunity to collaborate with experienced researchers and contribute to the development of cutting-edge flood risk modelling techniques.