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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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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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the fundamental aspects of transcriptional control, this project also opens new avenues for the design of climate-resilient crops. Supported by single-cell profiling and predictive artificial intelligence models
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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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-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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project that combines cutting-edge approaches including state-of-the-art imaging techniques, pluripotent stem cell models, in vivo mouse models of neurological disorders, drug (brain) delivery and nanobody
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. Their findings aim to unlock plant specialized metabolism for numerous human applications given these serve as a novel resource for engineering tools that will facilitate 1) the creation of (plant-based) synthetic
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in January 2025. The overarching goal is to identify the key factors controlling microbe-mediated carbon storage in the ocean, with a focus on using model microbial systems in the lab. We specialize in
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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
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Immunology or Neuroimmunology Experience in working with mouse models (FELASA B or C required) Strong organizational and communication skills, with an ability to work independently and collaboratively. Ability