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conclude on December 31st 2029. The goal of this research effort is to apply machine learning (ML) techniques, in particular (equivariant) graph neural networks to accelerate the creation of all physical
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for structural analysis of metabolites and lipids, creating metabolomics knowledge graphs, and inferring fluxes from MS data. The group collaborates with mass spectrometry vendors and technology partners
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