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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not
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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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