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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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engineering processing, material recycling, nuclear chemistry, theory and modelling. About the research project The project focuses on the development and synthesis of new π-conjugated organic semiconductors
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, renewable energy, to chemical engineering processing, material recycling, nuclear chemistry, theory and modelling. About the research project The project focuses on the development and synthesis of new π
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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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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
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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
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and molecular genetics as well as hands-on experience with cloning, live-cell fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model