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, learner-aware sequencing of content. This includes work on semantic parsing, structured NLP, graph-based neural models, metacognitive prompting, ontology alignment across disciplines, and human-in-the-loop
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 1 month ago
new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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molecular level. To yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and
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The Bernhard Nocht Institute for Tropical Medicine (http://www.bnitm.de/en ) is the largest Research Institute for Tropical Medicine in Germany and is the National Reference Centre for Tropical
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 1 month ago
the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
the Fugger lab at the Oxford Centre of Neuroinflammation , focusing on the development of drugs that tame common brain diseases through the application of graph-based neural networks, deep learning, and