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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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, computer simulations and various statistical approaches to increase understanding of the ecological and evolutionary processes that underlie speciation and ecological diversification in the context
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We are seeking a highly motivated Postdoctoral Researcher with expertise in computational biology, deep mutational scanning data, and generative artificial intelligence (AI). The successful
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structure and our propensity to lie – and test under which social and environmental conditions these two features spontaneously emerge as beneficial and stable strategies that boost the evolutionary fitness
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populations. This project will explore the genetic and evolutionary mechanisms shaping adaptation through a combination of genomic, computational, laboratory, and field-based approaches. Research focus
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in biology, forest sciences, environmental sciences, or data sciences. A strong background or motivation to learn ecological genetics and evolutionary biology as well as competence in bioinformatics
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Evolutionary Biology Condensed Matter and Statistical Physics / Dynamical and non-equilibrium phase transitions , Mesoscopic Physics , Non-equilibrium many-body theory Ecology / Population Biology
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: 270175818 Position: Postdoctoral Research Associate Description: The Department of Ecology and Evolutionary Biology (EEB) at Princeton University invites applications from postdoctoral research associates
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relevant fields of biology (e.g., systems, evolutionary, developmental, computational), physics, mathematics or related fields. In the appointment process, special attention will be given to research skills
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that match the tenure of this role About Us: The Population Biology and genomics Group The Population Biology and Genomics Group is focussed on the ecological and evolutionary dynamics of populations. We