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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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), specifically within the Faculty of Science and Engineering (FSE), in the Groningen Institute for Evolutionary Life Sciences (GELIFES), and in collaboration with the interfaculty research centre BirdEyes Centre
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
loss patterns across diverse plant lineages Explore graph-based algorithms for multiple genome alignment and ancestral karyotype reconstruction Position 2: Evolutionary Analysis and Network
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education at the department occurs in an international environment and is focused on animal biology. Outstanding and high impact research is conducted in a variety of fields, including evolutionary biology
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Bioengineering, including but not limited to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound
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integrating data from primary patient samples and experimental models, you will predict evolutionary trajectories and identify novel targets for precision medicine, aiming to enhance treatment responses and
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integrating data from primary patient samples and experimental models, you will predict evolutionary trajectories and identify novel targets for precision medicine, aiming to enhance treatment responses and
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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reinforcement learning and evolutionary algorithms to balance emissions reduction, safety, commuter convenience, economic factors and policy evaluation to generate optimised sustainable mobility plans. Decision