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Graph Machine Learning and Graph Data Management At Section for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk
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independently and as part of a team Preferred Qualifications Experience in graph-based AI models, multi-omics data integration, or network inference Background in epigenomics, gene regulation, or aging biology
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ability to work both independently and as part of a team Preferred Qualifications Experience in graph-based AI models, multi-omics data integration, or network inference Background in epigenomics, gene
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SQL databases and file repositories. We are now taking the next strategic step: developing ontologies and a dynamic knowledge graph to semantically link our internal data systems - and connect them
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph transformation, algorithm engineering. Applications of these areas to systems
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science, computational chemistry / biochemistry, applied mathematics, or a related area. The ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph
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mathematics, or a related area. The ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph transformation, algorithm engineering. Applications