Cluster of Excellence “Machine Learning”
Maria-von-Linden-Str. 6
72076 Tübingen
+49 7071 2970895


I’m a theoretical physicist mainly interested in climate data analysis using probabilistic models.

Research Interests

  • Climate data analysis (i.e. spatial-temporal data from satellites and meteorology)
  • El Nino Southern Oscillation diversity
  • Generative models (Hidden Markov models, Variational Autoencoders)
  • Representational learning
  • Physics-informed Machine Learning (parameter inference, EnKF)
  • Uncertainty quantification
  • Climate networks


I obtained my Bachelor in Physics at the University of Konstanz which was followed by a Masters in Physics at the University of Regensburg. During my studies I spent five months at the Weizmann Institute of Science in Israel and half a year at Bosch Research in Renningen. Since September 2020, I’m a PhD student in the Machine Learning for Climate Science group at the University of Tübingen and I’m part of the International Max-Planck Research School for Intelligent Systems. Privately, I love sports, nature and wildlife.

My CV can be found here.

Publications and conferences


  • Felix M. Strnad, Jakob Schlör, Christian Fröhlich, and Bedartha Goswami, Teleconnection patterns of different El Nino types revealed by climate network curvature, arXiv Preprint (2022), 2203.07035



  • Daniel Hernangómez-Pérez, Jakob Schlör, David A. Egger, Laerte L. Patera, Jascha Repp, and Ferdinand Evers, Reorganization energy and polaronic effects of pentacene on NaCl films, Phys. Rev. B 102, 115419 (2020)