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into operational decision‑support tools for farmers, in close collaboration with an industry partner. The project focuses on automated rumen‑fill assessment using 3D imaging, computer vision, and predictive
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We are seeking a highly motivated candidate who has recently completed, or is close to completing, a PhD and has training in statistics, data processing, bioinformatics, or a related discipline, to
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freshly resected patient tumor material for evaluation of immunotherapeutic strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging
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within the University of Münster developing imaging methods allowing to visualize molecular processes inside organisms, tissues and cells. With the help of imaging, we perform cutting-edge research in
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strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features
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qualifications A high level of computer proficiency, particularly in advanced imaging and image analysis, FACS, in vitro and/or in vivo assays Very high motivation, ambition and enthusiasm are fundamental
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
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other relevant qualifications A high level of computer proficiency, particularly in advanced imaging and image analysis, FACS, in vitro and/or in vivo assays Very high motivation, ambition and enthusiasm
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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological
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, with scientific areas ranging from fundamental chemistry, health and medical technology, materials science, renewable energy, to chemical engineering processing, material recycling, nuclear chemistry