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required to create a holistic picture. Such additional information can improve the performance, help to reveal biases, or may enable to perform causal inference. We are interested in developing statistical
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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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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oral presentations at national and international conferences Your profile PhD in Ecology or a related field Solid background in (macro-) ecology and biodiversity research. Solid background in zoology