Jesper Dramsch

Scientist
Forecast Department, Innovation Platform Team

Summary:

Jesper Dramsch implements state-of-the-art machine learning solutions for numerical weather prediction, approaching different topics in the 10 years ML roadmap at ECMWF.

Professional interests:
  • Machine learning in science
  • Validation of machine learning models in real-world contexts
  • Systems thinking
  • Semi-supervised and unsupervised learning
Career background:

Work Experience

  • 2021 - present: Scientist for Machine Learning, ECMWF
  • 2020 - 2021: Machine Learning Engineer, GMV NSL
  • 2019 - 2020: Postdoc, Technical University of Denmark
  • 2019 - 2020: Machine Learning and Python educator, Agile*
  • 2018 - 2019: Visiting Scholar, Heriot-Watt University Edinburgh
  • 2016 - 2019: PhD, Technical University of Denmark
  • 2016 - 2016: Research Assistant, Technical University of Denmark
  • 2016 - 2016: Research Assistant, GfZ Potsdam
  • 2014 - 2015: Geotechnical Student Assistant, O+P Geotechnik
  • 2013 - 2014: Lab Assistant, DESY
  • 2012 - 2012: Geophysics Intern, Schlumberger
  • 2011 - 2011: Geophysics Intern, Fugro FSI
  • 2010 - 2012: Student Research Assistant, University of Hamburg
  • 2007 - 2007: Intern Depth Imaging, GfZ Potsdam

Open Source Contributions

Maintainer

DOCUMENTATION