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. The project enables a targeted combination of expertise from machine learning, data science, and education with insights from educational practice. Drawing on large-scale data from authentic educational
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both empirical and simulated genetic data. These metrics will be applied to a unique large-scale dataset on plant genetic diversity in grasslands and forests. The position is part of the collaborative
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PhD in Plant Science, Plant Ecology or equivalent, have experience with designing and analyzing large-scale greenhouse experiments and publishing the results in peer-reviewed journals. Understanding
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the German Research Foundation (DFG). The priority area contributes to a better understanding of language technology (in particular, large language models, LLMs) and its applicability in the sciences, with a
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interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium and the Cluster of Excellence "Machine Learning