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impacts. The research will be quantitative and based on multiple data sources including field experiments and agricultural statistics. The PhD student will use and develop biophysical models of nutrient
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education credits. Qualifications You should have an MSc degree in microbiology, ecology, bioinformtics, or a subject relevant for the position. Skills in statistical, database management and scripting
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education and research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible
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publications Proficiency with data synthesis and statistical analysis. Valid driver’s license (B) Note, the project will include field work which requires carrying field gear and climbing on ladders, requiring
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, statistics, applied mathematics, agronomy, or related fields. Written and oral proficiency in English is required. Interest and previous experience in developing mechanistic models coupling plants
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pathology, plant breeding, plant ecology or equivalent. Knowledge of statistics and experience in R is required. You should have the ability to work independently as well as in a team. You should be motivated
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to work with tasks outlined above, she/he is expected to establish own initiatives to move the PhD project forward and to work well in a team. Advanced knowledge related to statistical analyses will be
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. Advanced knowledge related to statistical analyses, an understanding about the Swedish food system and about behavioral approaches will be of merit. Personal merits will play a significant role in the
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of methodology, we have extensive competence in System Analysis including Environmental Systems Analysis and LCA, as well as Biometrics (statistics and mathematics with applications in biological systems). Read
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how to use various statistical software applications for data analysis is required. Experience working with plants under field and greenhouse conditions, preferably including crossbreeding, is needed