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across the lifespan, with a particular emphasis on ecological active learning—how learners interact dynamically with their environments to acquire knowledge and make decisions. This is an open-topic
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning
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group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins. Thereby, relevant mechanisms are identified, which allow optimizing
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on the new Heilbronn campus (not in Garching / Munich!) Your tasks Graphs are a fundamental data structure and are commonly used to model relationships between data points such as links between web pages
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complex tasks despite its simple make-up, consisting of only one giant cell that harbors millions of cell nuclei. Nuclei interact and may even kill each other when organisms fuse. But nuclei also act
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practical and laboratory tests as well as sophisticated simulations. We not only publish research results gained at numerous conferences and in journals, but also make our software available in open source
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rankings in research and teaching. Our group “Sustainable Energy Materials” concentrates on the preparation of heterogeneous catalysts and the understanding of structure-performance indicators in