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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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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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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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computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine learning, with practical
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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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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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, with scientific areas ranging from fundamental chemistry, health and medical technology, materials science, renewable energy, to chemical engineering processing, material recycling, nuclear chemistry
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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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sequencing or spatial transcriptomics. Candidates without substantial practical experience in stereotaxic surgery combined with neural recording or imaging will not be competitive for this position. Duties