The RMS model development team boasts the best scientists building mathematical models thatpredict the distributions ofpossible damage due tothe effects of tropical storms, extra-tropical storms, thunderstorms, storm-surges and fluvial floods, using a combination of observed data, reanalysis data, numerical and statistical models and data assimilation.
RMS is the pioneer in the development and application of complex statistical and numerical modeling methods for the quantification of natural hazard risk.
RMS’ risk models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world. Our clients include several hundred insurance and reinsurance companies as well as brokers, banks, hedge funds, regional and local governments, and multilateral agencies.
Part of the Model Development group, the Flood team focuses on developing high-resolution, large-scalehydrologic / 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.
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
Furtheradvancement 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
Experience with GPU-accelerated computing for the solution of numerical problems
KnowledgeofMachine Learning techniques applied to large environmental datasets
Familiarity with large scale model development projects on HPC environments in Linux
Understandingof data-assimilation and / or forecasting environments, GIS tools, SQLand a strong publication record
Strong knowledge of statistics and probability theory