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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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for therapeutic intervention. This PhD project will leverage large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology to develop models, including transformer-/graph-based models
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek