22 phd-in-mathematical-modelling-of-biochemical-reactions Postdoctoral positions at VIB in Belgium
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-resistant forms. By identifying the biochemical factors that govern carbon storage in the ocean, we hope to better assess the impact of human activities on this reservoir and provide transferable results
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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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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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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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subteam, working closely with an experienced lab technician, two dedicated PhD students, and two postdoctoral researchers on a project focused on in vitro screening methods, including the use of organoids
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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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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Integration of phenotypic data with omics analysis Explore machine learning and network analysis methods Profile Essential A PhD in Bioinformatics, Computational Biology, Evolutionary Biology
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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