Workshop on

Machine Learning for Earth System Modelling 

25-27 August 2025

Bonn, Germany

We are pleased to announce the third Workshop on Machine Learning for Earth System Modelling

following a series of two workshops on Large-Scale Deep Learning for the Earth System. This year the workshop will be followed by Hackathon on Machine Learning for the Earth System.

The workshop will take place on August 25 – 27, 2025 in the Universitätsclub Bonn, Germany. 

On-site registration and abstract submission are closed. It is still possible to register for online attendance until Thursday, August 21st, 2025 23:59 UTC

Check the timeline below for an overview! You can also check the Abstracts & Registration page for more information! 

Stay tuned and subscribe at mlesm-workshop@listen.uni-bonn.de if you want to receive further announcements by email.

The workshop will again bring together the leading groups that develop large-scale neural networks for weather and climate.

Topics include:

    • Machine learning-based numerical weather prediction
    • Climate emulators and machine learning-based climate models
    • Machine learning-based Earth system component models, such as ocean and land models
    • Incorporation of Earth system observations in the above models
    • Evaluation and explainability of the above model
    • Datasets for model training, evaluation and benchmark

Read here about our workshop last year.

We are pleased to announce the third Workshop on Machine Learning for the Earth System Modelling (formally Large-Scale Deep Learning for the Earth System) together with a new hackathon event for PhD students and early-career researchers.

Scientific Review Committee:

Local Organising Committee

 

We gratefully acknowledge the support by
CESOC, ECMWF, the TRA Modelling at the University of Bonn, the Forschungszentrum Jülich and the University of Cologne.

 

Acknowledgement: The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

 

For questions please contact us via email:
mlesm-workshop@cesoc.net