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is looking for a full-time (100%) postdoctoral scholarship holder in the field of statistical shape modelling. Position The project aims to advance personalized musculoskeletal care by transforming
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for recombinant antigen expression.A key responsibility will be contributing to the development and characterization of transgenic and knockout mouse and hamster models, which are essential for studying viral
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-generation humanized models for studying peripheral neuroimmunity in Parkinson’s disease The Laboratories for Gut-Immune-Brain Axis Research (GIBA, Prof. Seppe De Schepper) and the Microglia and Inflammation
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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-Vandepitte Laboratory disposes of extensive experimental testing facilities and infrastructure. ABOUT THE DOC-CEM PROJECT The general objective of this project is to build-up knowledge and develop models and
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trajectories of individuals and households with a migration background in Belgium, focusing on hazard and microsimulation models of demographic events in multiple life domains. You contribute to the development
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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-based policy models for climate adaptation and land-use management by integrating socio-economic and environmental dimensions. Integrate research outcomes into European climate and rural development
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approaches to understanding life. These range from capturing life’s essential features to questioning if ‘life’ itself is a valid, objective category. While there is no consensus, most scientists agree
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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 data