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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data scientist AI driven weather model - **Company:** Koninklijk Nederlands Meteorologisch Instituut - **Location:** DE BILT, Netherlands (Remote available) - **Salary:** €3,496.0 - €5,535.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Machine Learning, Pytorch, Deep Learning, Data Analytics, Multiaccess Edge Computing - **Published:** August 22, 2026 - **Apply:** https://www.mmimir.nu/track/fbf9cf55-9c9f-4db3-b028-7c2326c40031 ## About the Role * 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. ## Description 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., * Individual Choice Budget (IKB): use this budget (the amount is 16.5% of your salary) for options such as repaying student loans, purchasing a (electric) bike with accessories, company fitness, making your home more sustainable, or other tax-friendly purposes * flexible leave arrangements, including care leave, parental leave, adoption leave, and foster care leave * our program provides support for visas and related matters, and language training (it does not include accommodation) ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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