Data scientist AI driven weather model

Are you passionate about advancing weather modeling using cutting-edge technology? Join the Royal Netherlands Meteorological Institute (KNMI) in the Destination Earth (DE) AI project (DE_376), where we push the future of high-resolution weather forecasts through deep learning. We are looking for a data scientist to help develop a model that matches the accuracy of our Harmonie-Arome model, especially for extreme weather. Collaborate with top meteorological institutes across Europe and shape the next generation of weather modeling.

How you contribute
As part of the Data Science cluster in the R&D Weather and Climate Models department, we are driving the development, maintenance, and application of several cutting-edge machine learning models. Our focus is on advancing ML methods for post-processing of numerical weather prediction (NWP) model output, as well as further developing data-driven weather models using machine learning – a task where you will play a key role. You’ll contribute to the further development of a stretched-grid weather model, leveraging a 40-year ERA5 re-analysis archive and multi-year high-resolution (km-scale) re-analysis data from several NWP models, such as our Harmonie-Arome model. This model is a graph neural network with a graph transformer.

Additionally, you will compare the performance of the forecasts from the stretched-grid weather model with those from Harmonie-Arome.

This exciting work is part of the DE_376 project. You’ll be collaborating with leading European meteorological institutes to develop high-resolution data-driven weather models for Europe with a focus on improving probabilistic forecasts of extreme weather by incorporating diffusion techniques a.o.

Your activities

• You develop and improve state-of-the-art machine learning models for data-driven weather forecasting.
• You contribute to the development of a stretched-grid weather model based on graph neural networks and graph transformers.
• You train and optimize models using large-scale weather datasets, including ERA5 and high-resolution NWP reanalysis data.
• You evaluate and benchmark machine learning weather forecasts against the Harmonie-Arome numerical weather prediction model.
• You collaborate with leading European meteorological institutes on the DE_376 project to advance probabilistic forecasting of extreme weather.
• You explore and apply innovative AI techniques, such as diffusion models, to improve next-generation weather prediction.

Your team
You will join the Data Science Cluster within the R&D Weather and Climate Models Department at KNMI. The cluster brings together data scientists and researchers who develop innovative machine learning solutions for weather and climate applications.

In the Destination Earth (DE_376) project, you will directly collaborate with 2 other colleagues at KNMI, while also working with other leading European meteorological institutes. The team combines scientific excellence with an open and collaborative culture, where knowledge sharing and innovation are central.

Would you like to know more?
We understand that you might want to learn more about this position. Feel free to contact Maurice Schmeits, coordinator of the Data Science cluster, at +31 (0)6 15 64 89 02 or Ben Wichers Schreur, team leader, at +31 (0)6 81 33 68 49. They will be happy to assist you!

KNMI's unique task is the gathering of information about the atmosphere and the subsurface and the translation of that information to risks for society.

Would you like to learn more about how we strive to make our high-quality knowledge and information in the area of weather, climate, and seismology operationally available? You'll read more about it on our website.

• You hold an MSc 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.
• Experience in weather forecasting (models) is a bonus.
• Experience with a data-driven weather model (like AIFS of ECMWF) and/or Anemoi is a bonus.

We are looking for someone who demonstrates the following competencies

• Analytical skills: you are good in interpreting and analyzing scientific results.
• Collaboration: you enjoy working in multidisciplinary and international teams.
• Results orientation: you focus on delivering high-quality outcomes and achieving project goals.
• Innovation: you are eager to explore and apply new machine learning techniques.
• Communication skills: you communicate complex ideas clearly, both verbally and in writing.

• Apply immediately, we look forward to it!
• We have opportunities for two full-time positions (2 FTE) within this project.
• These are temporary positions. Depending on the position offered, the employment contract will be for 15 or 18 months.
• A valid EU work permit is required.
• Once we have found the right candidates, we close the vacancy.
• Starting date: January 1 2027 – we’re eager to have you join us.
• Obtaining references can be part of the application process. An (online) pre-selection test, an assessment, making a case and (online) screening via databases, among others, can be part of the application process.
• Acquisition in response to this vacancy is not appreciated.