884 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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) , was created. 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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Sweden’s national environmental objectives. Read more about the department: https://www.slu.se/ekologi Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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teaching environment at the department. The main language of the PhD program is English. However, non-Swedish speaking students are expected to acquire basic skills in Swedish during the period of employment
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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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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working at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Grimsö wildlife research station Form of employment: Fixed-term employment for 4 months, with a possible extension. Scope
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experience) of their research career and must not have been awarded a doctoral degree. Where to apply Website https://umu.varbi.com/en/what:job/jobID:907734/ Requirements Research FieldBiological