Intern -Coastal Flood Modelling (Hybrid)

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Team Overview

Moody's RMS is the world's leading provider of mathematical models and information related to the financial impact of natural catastrophes. Our Model Development department has fifty PhD scientists and engineers based in London, building mathematical models that predict damage caused by tropical storms, extra-tropical storms, thunderstorms, coastal floods, freshwater floods and tsunamis.

We use a combination of observed data, reanalysis data, numerical, statistical and engineering models and data assimilation. We are the pioneers in the development and application of complex statistical and numerical modelling methods for the quantification of natural hazard risk, and our risk models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world.

The Coastal Flood team is responsible for modelling coastal flood hazard globally. This includes flooding caused by Hurricanes, Typhoons and Extratropical Windstorms. We model all aspects of a coastal flood including wind driven surge, waves, tides, defense behavior and inundation on land.

Members of the coastal flood team have diverse backgrounds including expertise in coastal dynamics, oceanography, and statistics. There is a strong focus on collaboration and innovation within the team with regular meetings to share methodologies and research.

Overview of role/responsibilities for the intern

• Project aims: Build a ML model to produce water-level timeseries during a real-time European Windstorm event.
• European windstorms bring a risk of coastal flooding which, if severe, could cause extensive damage to properties, infrastructure, and businesses. Moody's RMS has a catalogue of thousands of simulated storms causing coastal flooding along European coastlines. The aim of this project is to use this extensive dataset to develop and train a ML model to produce water-levels along a specified coastline given limited observational data as inputs. The measure of success will be how well the model can reproduce the water-levels compared to a fully hydrodynamic simulation.

• The candidate will develop and run a ML model (using PyTorch, for example) using an extensive training data set of water levels at the coast during European windstorms.
• Ideally the candidate will bring their own knowledge of ML to shape the initial planning phase and development of a model.
• The candidate will be required to present and discuss their work during regular meetings with their supervisor and the wider Coastal Flood Team. There will be an opportunity to present a seminar on their work at the end of the project to the whole Model Development team.

Qualifications:

Must have strong programming ability in scientific and analytical programming languages (e.g. R, Python, Fortran)

Must have experience with Machine Learning

Qualifications in an Earth Science/Physics - preferably Coastal Dynamics or Oceanography but other disciplines will be considered.

Experience working with high-performance clusters in a UNIX or Linux environment is advantageous

Some experience with GitHub is advantageous

Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.