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Flood Modeller

RMS is currently recruiting for a position in the Flood Modelling Team in London, UK or Newark, CA. The Flood team focuses on developing high-resolution, large-scale flood models which are used to assess flood risk. The modelling work carried out by the flood team encompasses all steps from hazard modelling to loss modelling. The department has an engaged working environment with a very clear scientific and technological focus, and with strongly self-motivated people.

Key Accountabilities & Deliverables:

- Further development of large scale rainfall-runoff models, stochastic rainfall processes, and defence failure models, and to seek for scientific and technological improvements in them;
- Spatial and temporal result analysis using GIS in a scripting environment;
- Calibration of hydrologic and hydraulic models;
- Advancement of hydraulic inundation methods;
- Benchmarking of model loss results against claims data and loss targets;
- Perform rigorous QA and research into consistency between observed and modelled spatial patterns, seasonality of floods, flood magnitudes, and similar for loss patterns.

Experience Required:

- Candidates with a PhD in Hydrology or Hydraulics preferred, but a similar degree in Meteorology, Applied Mathematics, or Civil Engineering will also be considered;
- Must have a strong analytical mind-set;
- Strong programming skills (Fortran, R, bash/csh, Python, Perl, awk/sed);
- Experience working with GIS-tools and spatial databases;
- Prior experience of working on large data sets in a Linux/Unix environment;
- Strong personal motivation, combined with an ability to work as part of a team, and to communicate results;
- Experience with Data Science considered an advantage;
- Experience with model development, usage of GPUs for large compute jobs, SQL, and a strong publication record are considered an advantage;
- Experience working with Spark, and Scala is considered an advantage.

Please quote "Application Flood Modeller" when applying.

More info can be found on RMS' career webpages.

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Good job. Keep it up.

James otoo, Student

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