Flood modeler / hydrologist full-time position at Risk Management Solutions - (Updated)

[stefano...@gmail.com]

Risk Management Solutions (RMS) has opened a full time position for a hydrologist / flood modeler, based in London, UK. 

Details are below, you can apply here. 

For any further information feel free to contact Stefano Zanardo (stefano...@rms.com).

The Position

Part of the RMS Model Development group focuses on developing high-resolution, large-scale hydrologic/hydraulic models which are used to assess flood risk. The modeling work carried out by the flood team encompasses all steps from hazard modeling to loss modeling. The department has an engaged, collaborative working environment with a clear scientific and technological culture.

Key Accountabilities & Deliverables:

• Contribute to the scientific and technological development of the flood hazard model components, as well as to their application: space-time stochastic rainfall model, water, and energy balance for the description of rainfall-runoff processes, hydraulic modelling of water flow in open channels, high-performance models for floodplain inundation and defense failure mechanisms
• 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)
• Quality-check the results by means of automatic calibration routines and contributing original ideas for calibration/validation of model components including benchmarking of flood inundation maps
• Evaluate final model output (e.g., flood footprints, flood losses and their spatial patterns using statistical methods and GIS tools)
• Perform applied research related to the occurrence and severity of floods across different domains (e.g. meteorological drivers of extreme floods, large scale patterns of flooding, trends and impact of regional flood risk, etc..)

 Experience Required:

• PhD in Hydrology, Hydraulics, Coastal and Ocean Engineering, Applied Mathematics, or a related discipline. Strong candidates with a relevant MSc and appropriate research or work experience will also be considered
• Strong programming ability in scientific and analytical scripting/programming languages (e.g. Fortran, R, Python, bash, CUDA, C/C++)
• Ability to work as part of a team

Advantageous Skills

• Experience with GPU-accelerated computing for the solution of numerical problems
• Knowledge of Machine Learning techniques applied to large environmental datasets
• Familiarity with large scale model development projects on HPC environments in Linux
• Understanding of data-assimilation and/or forecasting environments, GIS tools, SQL and a strong publication record
• Strong knowledge of statistics and probability theory