MAELSTROM Boot Camp 2022: Machine Learning for Weather and Climate

Europe/Berlin
Jülich Supercomputing Center

Jülich Supercomputing Center

Forschungzentrum Jülich Wilhelm-Johnen-Straße 52428 Jülich Germany
Description

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:

  1. An overview of the MAELSTROM project
  2. Introductory lectures on ML methods, meteorology, and High-Performance Computing systems
  3. Lectures on bespoken ML approaches of the six meteorological applications in MAELSTROM
  4. 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. KGMeteorologisk 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:

 

Participants
  • Alexander Hermanns
  • Anniina Korpinen
  • Aytac Pacal
  • Bangjun Cao
  • Ben Dixon
  • Cornelia Strube
  • Edwige Fifame Akpoly
  • Geert De Paepe
  • Hannah Melzer
  • Jacqueline Byukusenge
  • Jannik Thuemmel
  • Job Wiltink
  • José Miguel Vicencio Veloso
  • Karthick PANNER SELVAM
  • Lene Østvand
  • Ling Zou
  • Lynsia Saychele DONGMO TEDO
  • Mansour DIA
  • Margrethe Kvale Loe
  • Martin Vozár
  • Maxim Bragilovski
  • Mehmet Sedat Gözlet
  • Michaela Vorndran
  • Mohamadou Diallo
  • Moulikta Sanjeev
  • Nathalie Rombeek
  • Nazli Turini
  • Nils Brast
  • Reda ElGhawi
  • Rockefeller Rockefeller
  • Sebastian Lehner
  • Simon De Kock
  • Talytha Pereira
  • Thabang Lebese
  • Thomas Muschinski
  • Tony TONA LANDU
  • Yuliya Kazachkova
  • Ziming Wang
Bing Gong; Michael Langguth
    • 09:00 10:00
      Welcome and MAELSTROM introduction 4001b (INM )

      4001b

      INM

    • 10:00 10:30
      Coffee break 30m 4001b (INM)

      4001b

      INM

    • 10:30 12:00
      Lectures: Introduction to Machine Learning 4001b (INM)

      4001b

      INM

    • 12:00 13:30
      Lunch break 1h 30m Seccacino

      Seccacino

    • 13:30 14:45
      Lectures: Introduction to Weather and Climate Applications 4001b (INM)

      4001b

      INM

    • 14:45 15:45
      Lectures: Introduction to HPC systems 4001b (INM)

      4001b

      INM

    • 15:45 16:15
      Coffee break 30m 4001b (INM)

      4001b

      INM

    • 16:15 17:15
      Hands-on session: Hands on to access to HPC system, Git repo and trouble shooting 4001b (INM)

      4001b

      INM

    • 19:00 21:30
      Joint dinner in the city center of Jülich 2h 30m
    • 09:00 10:30
      Lectures: Introduction to the applications, datasets and problem statements Breakout room

      Breakout room

    • 10:30 11:00
      Coffee Break 30m
    • 11:00 12:00
      Hands-on session: Hands on session on dataset Breakout room

      Breakout room

    • 12:00 13:00
      Lunch break 1h
    • 13:00 13:30
      Lectures: Introduction to the first ML solution Breakout room

      Breakout room

    • 13:30 15:00
      Hands-on session: Hands on session on ML solution Breakout room

      Breakout room

    • 15:00 15:30
      Coffee Break 30m
    • 15:30 17:00
      Joint meeting of all applications: 5 min pitch from applications tutor or participants Breakout room

      Breakout room

    • 19:00 21:00
      Joint dinner 2h TBD

      TBD

    • 09:00 10:30
      Lectures: Introduction to advanced ML and Tier 2 datasets Breakout room

      Breakout room

    • 10:30 11:00
      Coffee Break 30m
    • 11:00 12:00
      Hands-on session: Hands on session on dataset/advanced ML solution Breakout room

      Breakout room

    • 12:00 13:00
      Lunch Break 1h
    • 13:00 15:00
      Hands-on session: Hands on session on advanced ML solution Breakout room

      Breakout room

    • 15:00 15:30
      Coffee Break 30m
    • 15:30 17:00
      Joint meeting of all applications: 5 mins pitch from application tutor or participants Breakout room

      Breakout room

    • 19:00 21:00
      Joint dinner 2h TBD

      TBD

    • 09:00 10:30
      Hands-on session: Hands on session on distributed ML and future work Breakout Room

      Breakout Room

    • 10:30 11:00
      Coffee break 30m
    • 11:00 12:00
      Hands-on session: Hands on session on distributed ML and future work discussion Breakout Room

      Breakout Room

    • 12:00 13:00
      Lunch break 1h
    • 13:00 15:00
      Joint meeting of all applications: Wrap-up and 5 min pitch per application, and feedback.
    • 15:00 18:00
      Visit coal mining site 3h