The aim of “CLOUD-TRAIN” is to establish a multi-site network of Early Stage Researchers (here predominantly PhD students) and Experienced Researchers at 10 partner institutions across Europe. The role of aerosol nucleation for atmospheric CCN levels, clouds and climate is investigated. The influence of various vapours and ions for aerosol nucleation, growth and cloud processes is studied to significantly improve our understanding of natural and anthropogenic climate forcing as well as feedback mechanisms.
The major focus of the network will be three sets of common experiments on ternary nucleation (ion-induced and neutral) and ion-aerosol-cloud interaction carried out at CERN to which all trainees contribute. These experiments are conducted at the newly established unique aerosol chamber “CLOUD” that is exposed to a CERN ionizing particle beam where the effects of cosmic rays on aerosol and clouds can be efficiently simulated. At the CLOUD chamber nucleation experiments are performed at an unprecedented level of precision and completeness using highly innovative instrumentation.
A comprehensive high quality training programme is set up for the fellows. Additional to the experiments at CERN, they are brought together for network training events such as annual summer schools and workshops for integral data analysis. Courses by world leading experts are taught spanning from general aerosol chemistry and physics to specialized sessions. The summer schools and workshops are specifically tailored to the needs of the trainees and are scheduled in addition to the national PhD programmes of their hosting institutions. Comprehensive transferable skills training is included (e.g. scientific writing, presenting talks, interaction with the media, entrepreneurship, IPR, management). Five network partners are from the private sector (2 full, 3 assoc.). Secondments are planned for each fellow to broaden the experience and to include exposure to another sector.
Field of science
- /natural sciences/computer and information sciences/data science/data analysis
Call for proposal
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