14 agent-based-modelling PhD positions at Swedish University of Agricultural Sciences
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for multiuse purposes, addressing issues on climate change adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and
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biotechnology solutions based on scientific breakthroughs. www.SweTree.com Spray-induced gene silencing for control of damage agents SIGS (spray-induced gene silencing) is a promising biologically-based
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) analysing the effects of different trade-offs between timber production and biodiversity under the influence of climate change, and 3) developing optimisation models based on heuristic and AI-based methods
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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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) qualification. Alternatively, you must have conducted a minimum of four years of full-time study, of which a minimum of one year at second-cycle level. Applicants will be selected based on their written
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://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/ The Swedish University of Agricultural Sciences (SLU) has a key role in the development for sustainable life, based on science
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financial compensation. We have four specific goals: Identify evidence-based opportunities and challenges to the practice of payments for biodiversity, and forest ecosystem trade-offs Assess landowners' and
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, part of the Wallenberg Initiatives in Forest Research (https://www.slu.se/WIFORCE/en ), was created. We are looking for an industry/collaboration-based PhD student in remote sensing to develop methods
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. Alternatively, you must have conducted a minimum of four years of full-time study, of which a minimum of one year at second-cycle level. Applicants will be selected based on their written application and CV
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resistance potential of ash trees. The project aims to support conservation efforts by refining selection criteria for resistant ash based on a comprehensive understanding of disease dynamics and environmental