Further develop the flood model components (e.g., large scale modeling of stochastic rainfall processes, rainfall-runoff processes, defense failure mechanisms) and to seek for scientific and technological improvements;Quality-check the results (e.g., calibration results);Evaluate final model output (e.g., flood footprints, flood losses and their spatial patterns using statistical and GIS tools);Further develop the usability of the flood models in RMS(one);Further advancement of hydrological and hydraulic modules by researching and implementing novel scientific techniques (e.g. advancing the stochastic modules and peril modules that are at the center of the flood model);Checking of model results (both hazard and loss data) by comparison to existing flood maps and loss benchmarks;Perform research into consistency between observed and modeled spatial patterns, seasonality of floods, flood magnitudes).
Candidates with a PhD in Hydrology preferred, but a similar degree in Meteorology, Applied Mathematics, or Civil Engineering will also be considered;
Must have a strong analytical mind-set combined with strong programming skills (Fortran, R, bash, csh, python, awk and sed);
Prior experience of working on large data sets in a Linux/Unix environment;
Ability to work as part of a team.
Experience with model development, usage of GPUs for large compute jobs, data-assimilation and/or forecasting environments, GIS tools (e.g., GRASS), SQL, and a strong publication record are considered an advantage.