In the project BINARY, funded by the Carl-Zeiss foundation, a PhD position (TVöD 13, 75%, 40 months) is available. The project deals with the topic of cloud organisation with a focus on the organisation and aggregation of convection. The plan is to combine modelling and big data machine learning techniques from observations, e.g. satellite data, to better constrain the conditions for organisation of convection. A goal of the project is to make use of the information obtained from the machine learning analysis to derive a parameterisation for convective organisation to be applied in large-scale climate models.
As a successful candidate, you will be able to communicate well in German or English and enjoy working in a collaborative environment. You will have a strong background and a keen interest in atmospheric convection and modelling, with good analytical skills, and you will be familiar with at least one programming language (optimal would be FORTRAN). Experiences in numerical modelling are desirable and knowledge about machine learning techniques is beneficial. We expect you to hold a Master degree in Meteorology, Physics, Applied Mathematics, computational physics or a related science. The candidate is expected to work in a highly interdisciplinary environment in this project in close collaboration of atmospheric sciences and computer sciences.
JGU Mainz is the largest University of Rhineland-Palatinate covering a wide spectrum of disciplines. The IPA has a long-standing tradition in Weather Research, Numerical Modelling, and Cloud Physics, which are all key areas for the project. In addition, there are strong ties between IPA and the German Weather Service. The group has long experience on atmospheric modelling with a focus on both convective processes and chemistry-climate interactions. The first aspect is covering the topic of this position.
JGU is an equal opportunity employer. Women are especially encouraged to apply. Applicants with disabilities will be preferentially considered if equally qualified.
Please send your application to Prof. Dr. Holger Tost (tosth @ uni-mainz.de).