MAELSTROM Boot Camp 2022: Machine Learning for Weather and Climate will be held from 27 September 2022 at 9:00 CEST to 30 September 2022 at 17:00 CEST on-site at Forschungszentrum Jülich. Registration is available and open (Deadline 15th Aug 2022):
The goal of this four-day Boot Camp is to provide training for the participants to use machine learning (ML) in weather and climate applications on High-Performance Computing systems (HPC). The participants will explore the applications developed in the MAELSTROM project with an introduction to the scientific background of meteorology, ML, and HPC.
The Boot Camp will cover the following topics:
- An overview of the MAELSTROM project
- Introductory lectures on ML methods, meteorology, and High-Performance Computing systems
- Lectures on bespoken ML approaches of the six meteorological applications in MAELSTROM
- Comprehensive hands-on tutorials in the scope of the MAELSTROM applications
The tutors are from MAELSTROM partners: European Centre for Medium-Range Weather Forecasts, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 4Cast GmbH & Co. KG, Meteorologisk Institutt, E4, Universite de Luxembourg and FZJ.
This event will be held in English. The target participants are Master and PhD students. The participants should have a basic background either in meteorology or machine learning or both. Some limited knowledge of Python and standard ML frameworks (e.g. TensorFlow or PyTorch) is preferred. Ideally, you are also familiar with Jupyter Notebooks and git, though this is not required.
There will be no registration fee, but travel and accommodations must be paid by your home institution.
Please check the FZJ web page for information on how to get to Jülich and book your own accommodation.
We arrange a tour to visit RWE coal mine on the last day of the Boot Camp. Please indicate if you would like to participate when you register (Please check details: https://www.rwe.com/nachbarschaft/rwe-erleben)
if you have any question, feel free to contact us: b.gong@fz-juelich.de; m.langguth@fz-juelich.de
Additional information:
- How to reach FZJ:https://www.fz-juelich.de/en/about-us/contact-visitor-information/how-to-reach-us
- List of hotels (not exhaustive):
