Are you passionate about advancing weather modeling using cutting-edge technology? Join the Royal Netherlands Meteorological Institute (KNMI) in the EU funded Horizon project Weather Generator. The goal of this project, led by the European Centre for Medium Range Weather Forecasts (ECMWF), is to develop a European open-source foundation model for weather and climate in a collaborative effort of 16 institutes, where we push the future of high resolution weather modeling through deep learning. In addition to this foundation model, a number of tail networks will be developed. Think this could be your next big challenge? Find out more below!

How you contribute in this role
As part of the Data Science cluster in the Research & Development Weather and Climate Models department, we drive the development, maintenance, and application of several cutting-edge machine learning models. Our focus is on advancing machine learning methods for postprocessing of numerical weather prediction model output, as well as pioneering data-driven weather models using machine learning; a task where you will play a key role. You will contribute to the development of a specific tail network of the Weather Generator, namely a network to improve high resolution probabilistic extreme weather forecasts in Western Europe.

Additionally, you will compare the performance of the forecasts from this tail network with those from another machine learning weather model, a so-called stretched grid model, and with those from our operational high resolution numerical weather prediction model Harmonie Arome.

What gives you satisfaction
You thrive on solving complex challenges and pushing the boundaries of weather modeling through innovative machine learning techniques. You are excited about working with large, detailed datasets and collaborating with international experts to drive forward projects that have a direct impact on weather forecasts.

• You have completed a PhD in data science or a related field, with a strong focus on machine learning.
• You have hands-on experience developing deep learning models using PyTorch.
• Meteorological knowledge is a bonus.
• Experience with a data-driven weather model (such as AIFS from ECMWF) and/or Anemoi (Anemoi: a new framework for weather forecasting based on machine learning | ECMWF) is a bonus.
• You are prepared to travel a few times a year to different European countries.
• For this position you will need to have a valid European work permit.

• Your official workplace is De Bilt. At the Royal Netherlands Meteorological Institute (KNMI), we actively encourage hybrid working. In consultation with your manager and colleagues, you can work from home or at the office, depending on the nature of your role.
• If we receive sufficient suitable applications, the vacancy may close earlier than the stated deadline.
• An (online) pre-selection test or assessment may be part of the recruitment process. Completing a case assignment and undergoing (online) screening, such as through databases, may also be included. Reference checks may be conducted as well.

Want to learn more?
We also understand you might want to learn more about this position. Therefore, feel free to contact Maurice Schmeits, coordinator of the Data Science cluster, at +31 6 15648902 or Ben Wichers Schreur, team leader Research & Development Weather and Climate Models department, at +31 6 81336849. They will be happy to assist you!