PhD positions in the interdisciplinary project Big Data in Atmospheric Physics (BINARY)

Johannes Gutenberg University of Mainz, Germany
Closing date not specified

In many natural sciences, and also in atmospheric physics, very large data sets are available due to improvements in measurement techniques and numerical simulations. At the same time, essential processes in the atmospheric system are still not well understood. Due to the recent great progress in machine learning and statistical data analysis there is a justified hope that by applying these modern and powerful methods to large data sets (e.g. meteorological reanalyses, satellite images) the underlying processes can be better analyzed and understood. Complementary to the methods of statistical data analysis, however, theoretical concepts and (mathematical) models have to be developed, and numerical simulations with models have to be carried out, so that new insights can be gained by combining the different points of view.

In the BINARY project the following topics in atmospheric physics will be investigated:

  • Structure formation in clouds
  • Aggregation of cloud systems
  • Predictability of difficult weather situations
  • Representation of small-scale processes in coarse weather or climate models

The work will be carried out in an interdisciplinary way, in a cooperation of the Institutes of Atmospheric Physics and Computer Science at JGU Mainz. The project is supervised by 5 scientists each from computer sciences and atmospheric physics. The aspects of machine learning will be taken over by computer sciences staff. The positions advertised here focus on model development and mathematical and/or numerical modeling of the underlying processes and systems.


By continuing to use the site, you agree to our privacy policy and the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.