PhD position in the field of atmospheric clouds
University of Vienna, Austria
Closing date: 1 August 2022
Clouds are the visible result of dynamic and thermo-dynamic processes going on in the atmosphere. The description of cloud processes in Numerical Weather Prediction models has improved dramatically within the last decade. The correct timing and location of clouds is crucial e.g., for a correct precipitation forecast, for climate and climate change, ceiling and visibility, and sun shine duration in connection with renewable energy production. However, information about the 3D-structure of the clouds is lacking in the observations, e.g. for a 3D verification of cloud forecasts.
The PhD student will select and further develop machine and deep learning methods to quantify the cloud type from cloud images. The cloud type will be used as a substitute for the unmeasured vertical extension of the clouds. She*he will organize the training data set, select and test machine and deep learning methods, train and evaluate the selected methods.
This position will be part of the Vienna Network for Atmospheric Research (VINAR), a collaboration between the University of Vienna and ZAMG (https://vinar.univie.ac.at/). The student will have access to data and models used at ZAMG and the research will be conducted in close collaboration with ZAMG.
The successful candidate will be member of the Vienna International School of Earth and Space Sciences VISESS (https://visess.univie.ac.at/).
Besides research, the successful candidate is also expected to participate in teaching and the supervision of students as well as in science related administrative tasks.
Financial support is available for attending international meetings and visiting international research partners.