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of computer vision models is comfortable working in multidisciplinary research environments, where methods are applied to biological or real-world problems Qualifications The applicant must: hold a PhD in a
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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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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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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position within a Research Infrastructure? No Offer Description Subject description The postdoctoral fellow will join a project focused on developing protein-based electronic components, with the ultimate
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around 200 dedicated staff, including 65 PhD students . We are a joint department between Chalmers University of Technology and the University of Gothenburg, combining the best of two academic worlds in
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. Qualifications In order to be eligible for employment as post doctor you must have a PhD or a foreign degree equivalent to a PhD in Automatic control or electrical and electronics engineering or related subject. A
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a PhD in Automatic control or electrical and electronics engineering or related subject. A doctoral degree awarded no more than three years before the application deadline provides a useful
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equivalent to a PhD in Automatic control or electrical and electronics engineering or related subject. A doctoral degree awarded no more than three years before the application deadline provides a useful
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international journals and at major conferences. The position will include supervision of PhD and MSc students, teaching and supporting in acquiring funds for future research projects from research funding