Peter Dueben

Peter Dueben

Peter is the AI and Machine Learning Coordinator at ECMWF and holds a University Research Fellowship of the Royal Society that enables him to perform research towards the use of machine learning, high-performance computing, and reduced numerical precision in weather and climate predictions. Peter has also a strong interest in the quantification of uncertainty of predictions for chaotic systems. Peter is coordinator of the MAELSTROM EuroHPC-Join Undertaking project, work-package leader of the ESiWACE2 H2020 project, and Co-Pi of an US-INCITE grant to perform season-long, global, storm-resolving simulations. Before moving to ECMWF, Peter has written his PhD thesis at the Max Planck Institute for Meteorology and has worked as PostDoc with Tim Palmer at the University of Oxford.

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  • Organization
    European Centre for Medium-Range Weather Forecasts (ECMWF)
  • Profession
    AI and Machine Learning Coordinator
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