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team and actively participate in the DIPONI project (“Digital Transformation in Polymer Processing: Interoperability and Machine Learning Solutions for Process Optimization and Sustainability
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination
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