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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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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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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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microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational biology, human microbiota, microbiology or other relevant areas
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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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spin-offs and start-ups, creating a natural home for researchers and their families. English is very widely spoken in the city and surrounding area. We are looking for a postdoctoral computational
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, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes. The postdoctoral fellow will work
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"Multi-modal analysis of nucleic acids from liquid biopsies for cancer monitoring” Description The Translational Onco-genomics and Bio-Informatics lab (TOBI-lab; tobi.ugent.be) at the VIB-UGent is
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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