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to decipher the regulatory code controlling gene expression in plants through the engineering and large-scale validation of synthetic promoters. Within the ERC-funded multiCODE project, we aim
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training data. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to design synthetic promoters. You will train and evaluate predictive models in
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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are seeking a motivated and enthusiastic colleague with strong computational skills in the analyses of complex data sets to join our teams. About the project We have generated advanced brain on chip models
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: In vitro and/or in vivo phage display; Cloning, engineering, expression, purification and characterization of VHHs. We invite applications from dynamic individuals with a strong drive for innovation
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of cellular metabolism or physiology. Experience in genetic engineering of phytoplankton or mass spectrometry-based metabolomics is a plus. The postdoc will get training in high-throughput metabolomics and
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intervention trials (e.g., diet, FMT), and ex vivo gut models enabling advanced multi-omics analyses of these samples. In addition the lab also maintains a large culture collection, partially linked to genomic
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critical roles of ion channels—particularly the TRP superfamily—in physiological and pathological processes. Our interdisciplinary approach spans from foundational electrophysiology to translational models
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interest in neurobiology and/or evolutionary biology, with a strong background in bioinformatics. PhD in Bioinformatics, Engineering, Computer Science, Physics, Bio-engineering, or Life Sciences
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temperature signalling in plants, such as the model plant Arabidopsis thaliana and the crop plants wheat and soybean. To unravel this, we focus on dynamic changes in protein phosphorylation status, since