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in healthy states, genetically perturbed states, and during liver regeneration. On the other hand, you will develop algorithms to disentangle direct intercellular signals from those that are induced
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hypothesize that the coordinated proliferation of liver cells is orchestrated by evolutionary conserved molecular circuits that ensures liver function and avoids organ failure during the rapid neonatal tissue
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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strong interest in developmental, cellular or molecular neurobiology, in link with human brain evolution and diseases. PhD in neuroscience, genetics, evolutionary biology or related field. Experience in
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developmental biology, cell biology and evolutionary biology. We like to implement novel omics technologies such as single cell approaches and chemical biology to help us answering our biological questions
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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and Delivery: Design and develop training programs on Data Science and AI topics, including machine learning algorithms, data visualization, and statistical analysis. Provide foundational sessions about