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Application deadline: 30 April 2019
We invite you to apply for a PhD position in the field of atmospheric cloud research. Clouds, specifically shallow clouds over the global oceans, are the largest source of uncertainty for climate projections. During your PhD research, you will explore concepts from the field of dynamical systems theory to improve our understanding and modelling of shallow cumulus clouds. In combination with machine learning, you will apply these concepts to analyze large data sets of cloud fields. You will work with existing data from simulations and observations as well as perform your own numerical simulations. Within a broad scope, we will guide you in designing specific research projects that take your own ideas and interests into account.
We are looking for a strong, curiosity-driven candidate who enjoys conceptual thinking as well as computational data analysis.
To be considered for this position, you must hold a scientific degree (Master's or equivalent). As a suitable candidate, you may come from a range of backgrounds including, but not limited to, Atmospheric Science and Geoscience, Physics, Computational Science and Applied Mathematics. You should have practical programming experience, ideally including data analysis and visualization (e.g. in python). Any prior knowledge you may have about atmospheric modelling or observation, dynamical system theory or statistical physics will be beneficial but is not required. We expect you to work independently as well as in small teams. You should communicate fluently in English (oral and written) and will present your results to the scientific community in the form of peer-reviewed publications and presentations at scientific meetings.