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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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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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biologist to decipher the genomic regulatory code controlling gene expression in plants. Within the ERC-funded multiCODE project, we aim to unravel how plants control gene expression across different tissues
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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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to unravel how plants control gene expression across different tissues and stress conditions by combining single-cell genomics, artificial intelligence, and synthetic biology. Apart from shedding light on
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. The impact of microglia during the progression of neuropathology is dictated by their subtype composition – as different subsets will lead to different functional outcomes. Microglia transcriptional
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effectively with team members from different backgrounds and in different research areas Proficient use of the English language for both oral and written communication is a must Desirable International
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the somatosensory cortex display striking differences in their synaptic properties, even when intermingled on the same cortical dendrite. This project will explore the molecular mechanisms that mediate
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of (epi-)genomic sequencing data generated on biofluids from cancer patients. You will develop novel strategies to integrate the different omics data layers. You will validate results by comparing the data