53 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Swedish University of Agricultural Sciences
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Swedish University of Agricultural Sciences (SLU) is seeking a postdoctoral researcher with strong methodological expertise in AI and computer vision for research focusing on animal welfare and
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and advanced level. Read more about the department here (https://www.slu.se/en/departments/soil-environment/ ). And about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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/about-slu/organisation/departments/forest-biomaterials-technology/division-of-biomass-technology-and-chemistry/ Read more about our benefits and working at SLU by visiting: https://www.slu.se/en/about-slu
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have a veterinary degree valid in Sweden and have post-graduate training in diagnosic imaging. It is a merit if you have completed a ECVDI residency programme or a national education programme in
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will work at the Department of Molecular Sciences, SLU and collaborate with the interdisciplinary research center PAN Sweden, https://www.oru.se/strategiska-satsningar/mat-och-halsa/pan-sweden.The
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Sweden Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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program. We expect you to work methodically and meticulously, as some tasks require high precision. You should be interested in both practical silvicultural issues and the forest ecosystem as a whole. You
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The Department of forest genetics and plant physiology is part of Umeå Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest
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about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for environmental monitoring Mathematical statistics Description
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical