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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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, conducting, and reporting scientific studies, as well as familiarity with statistical analyses (e.g., R), is also considered an advantage. You should be able to work both independently and as part of a team
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of full-time. Your qualifications You have graduated at Master’s level in biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered
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-microbe interactions, mycology, and microbial ecology. The position is placed in the Forest Microbiology group. Read more about what it is like to work at SLU at: https://www.slu.se/en/about-slu/work-at-slu
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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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Infrastructure (https://svenskahistoriskapatent.se ). The group’s research centers on inventors, intermediaries in markets for technology, and the development of firms’ innovation capabilities and technology
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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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good English skills are necessary, both written and spoken. Other Meritorious Qualifications Particularly meritorious are previous research experience in biomarkers, statistical knowledge, and experience
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Mathematical Statistics: https://www.umu.se/en/department-of-mathematics-and-mathematical-statis… We look forward to receiving your application! Where to apply Website https://umu.varbi.com/en/what:job/jobID
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sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation of the ongoing environmental monitoring programs the National Forest Inventory