19 – 21 August 2026 · Bonn, Germany
Hackathon: Machine Learning for Earth System Modelling (MLESM)
About the Hackathon
We are pleased to announce a new Hackathon on Machine Learning for the Earth System for PhD students and early-career researchers. This event is associated with our third Workshop on Machine Learning for Earth System Modelling right before the hackathon.
The application procedure is closed. Accepted participants were notified and should follow the instructions provided via email to complete their registration.
What is a Hackathon & Why Machine Learning for Climate Science?
A hackathon is an event where people come together to solve real-world problems through coding, collaboration, and innovation. It’s a fast-paced, hands-on experience where teams brainstorm, develop, and present projects within a short timeframe.
Machine Learning (ML) is revolutionising many fields, including weather and climate science. From improving numerical weather predictions to developing climate emulators and foundation models, ML helps us better understand and predict the Earth system. This hackathon provides a unique opportunity to apply cutting-edge ML techniques to critical challenges in weather and climate research.
Join us!
Join us for an exciting Machine Learning Hackathon for the Earth System! This event brings together PhD students and early-career researchers from Earth System Science and Computer Science to collaborate, learn, and tackle challenges at the intersection of AI and climate research.
Date: August 19–21
Location: Computer Science Department, University of Bonn – Friedrich-Hirzebruch-Allee 8, 53115 Bonn, Germany
Fee: 50 € (includes access to the venue, extended coffee breaks, and lunch for the 2.5 days)
Stay updated—subscribe to our mailing list at mlesm-workshop@listen.uni-bonn.de to receive announcements!
Why Join?
Inspiring Talks – Kickstart with expert-led technical sessions.
Hands-on Coding – Work on real-world challenges in weather and climate modeling.
Mentorship & Networking – Learn from and connect with researchers and developers.
Team Collaboration – Whether you’re a beginner or an expert, find teammates and build together.
Exciting Prizes – Compete for awards in different tracks!
What to Expect?
Building on the momentum of workshops and research initiatives in deep learning for the Earth system, this hackathon will provide a collaborative event that brings together developers, researchers, and enthusiasts from Earth System science and Computer Science. Participants will tackle critical challenges and learn about large-scale deep learning in weather and climate.
The Hackathon challenges are currently in preparation. Potential project topics include:
ML-based numerical weather predictions (NWP)
Climate emulators
Foundation models for Earth System Science
Example project: Use the open-source Weather Generator code!
Participants will have the opportunity to attend expert-led lectures covering a range of topics in Earth System Science (ESS), Machine Learning, and general computational practices.
There will be lectures on both the ESS domain and the ML domain.
For ML, sessions will cover an introduction to Graph Neural Networks, fine-tuning and utilizing pre-trained models, and coding attention mechanisms for weather AI models. Participants will also learn about training and evaluating weather AI models on multiple GPUs.
Is this for me? ✅
✔ I am a PhD student, early-career researcher, or ML enthusiast.
✔ I have an interest in AI and climate science.
✔ I want to gain hands-on experience in ML for Earth sciences.
✔ I enjoy collaborating with peers and experts in the field.
✔ I am eager to learn and contribute to impactful projects.
This hackathon is for you! 🎉 Whether you’re a developer, researcher, or just someone passionate about learning more about Earth System AI this hackathon welcomes participants of all backgrounds and skill levels.
Teams will be formed during the hackathon.
Organising Committee
- Martin Schultz (Jülich Supercomputing Center)
- Florentine Weber (CESOC Coordination)
- Marieke Wesselkamp (MPI for Biochemistry)
- Sorcha Owens (UK MetOffice)
- Daniel Minge (TRA Modelling, University of Bonn)
Questions?
📩 Contact us at: mlesm-workshop@cesoc.net
Headline here
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Why Join?
Inspiring Talks – Kickstart with expert-led technical sessions.
Hands-on Coding – Work on real-world challenges in weather and climate modeling.
Mentorship & Networking – Learn from and connect with researchers and developers.
Team Collaboration – Whether you’re a beginner or an expert, find teammates and build together.
Exciting Prizes – Compete for awards in different tracks!
Is this for me?
✔ I am a PhD student, early-career researcher, or ML enthusiast.
✔ I have an interest in AI and climate science.
✔ I want to gain hands-on experience in ML for Earth sciences.
✔ I enjoy collaborating with peers and experts in the field.
✔ I am eager to learn and contribute to impactful projects.
This hackathon is for you! 🎉 Whether you’re an experienced developer, researcher, or just someone passionate about learning more about AI this hackathon welcomes participants of all backgrounds and skill levels.
Teams can be formed during the hackathon. Don’t worry if you don’t know anyone—we’ll help you find a team.
Supported by
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 will be 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.