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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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to analyse and compile data and video material from a random sample of Swedish dog owners. The long‑term goal is to create a more complete picture of the Swedish dog population – including personality types in
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026/postdoc
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assignments Your main tasks will be to analyse and compile data and video material from a random sample of Swedish dog owners. The long‑term goal is to create a more complete picture of the Swedish dog
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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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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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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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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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postdoc rules). - Strong experience in in vivo rodent experiments, with competence in at least one of: Stereotaxic surgery and viral/vector delivery, in vivo imaging (miniscope, 2P), optogenetics
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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