173 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD scholarships in Sweden
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creative and stimulating environment with the opportunity to network with both the business community and international contacts. Read more about our benefits and what it is like to work at SLU at https
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and administrative staff. For more information about the department visit: www.slu.se/aquatic-sciences Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu
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at https://www.slu.se/en/about-slu/work-at-slu/ Description: We are looking for a PhD to focus on separation of fat and proteins from dairy side streams and plant-based extracts. The project is a
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of 20 per cent of full-time. Your qualifications You have a master’s degree in electrical engineering, engineering physics, mechanical engineering, computer engineering, engineering mathematics or have
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today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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is to advance the understanding of forest ecosystems and how these should be managed today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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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/ Animal Science Description: We are looking for a motivated and committed PhD student who wants
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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