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data, and operates state-of-the-art facilities for cultivating and analyzing colon bacteria to study their physiology, function and interactions. Finally, as members of VIB.AI, the newly established
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also opens new avenues for the design of climate-resilient crops. You will apply AI strategies to learn the regulatory syntax encoded by the Arabidopsis genome using single-cell transcript data as
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of synthetic promoters in planta. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to edit natural promoters. You will work very closely together
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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will focus on the development, optimization and application of multi-modal analysis strategies and pipelines for sequencing data generated on nucleic acids isolated from biofluids (genomics, epigenomics
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. The names and contact details of 2-3 referees. For more information, please contact Dr. Sibylle Vonesch (sibylle.vonesch@kuleuven.be ) (only clarifications or further details regarding the vacancy
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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Polleux, Nat. Rev. Neurosci. 2023). You will explore single-cell epigenomics and transcriptomics data, focused on the neurons of the cerebral cortex from human and an array of non-human species. Using
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experiences and future goals a detailed CV including publication list contact information of 2-3 references The first review of applications will start immediately. A shortlist of applicants will be selected
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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