183 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" PhD positions in Sweden
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to apply Website https://www.hb.se/en/about-ub/work-at-ub/how-to-apply-for-a-job-with-us/ Requirements Research FieldTechnology » Materials technologyEducation LevelMaster Degree or equivalent Skills
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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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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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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 in urban areas. See also: https://www.slu.se/en/about-slu/organisation/departments/ecology/ About the position The researcher will work in the field (in southern Sweden), with statistical analyses, and
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Description of work You will be working in the laboratory of Marta Bally (https://ballylab.com/ ), in close
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) and Machine Learning/NLP (Natural Language Processing) to capture both the network embeddedness and the qualitative B2B relationship features of supply chains. The project identifies key bottlenecks