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Description: Plants, like humans have developed adaptive immune systems to enable them to respond to disease threats. In parallel to what has recently been shown in human gut health, microbial diversity on both
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properties and processes, as well as how soil functions are affected by changes in environmental conditions, including climate change. Through research, environmental analysis and education, we contribute
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process models from the field of spatial statistics to model clustered patterns across the landscape, and develop methods for estimating plant population size and/or change. Qualifications: Requirements
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strong interest for microbial soil processes and an ability to conduct field work in remote places. A driving license valid in Sweden (required for accessing the field sites) Merits: Merits
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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oral communication skills in English. Meritorious: Knowledge and experience in: working with statistical methods and analyses. programming and data processing. We place great emphasis on personal
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to automate the process of species classification. However, there are still several methodologies that need to be developed to integrate these models into a functioning workflow for ecologists. In this 4-year
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adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and long-term experiments. Qualifications: The applicant
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collaboration with farmers who are already testing these systems. As a PhD student within this project, your work will include field station and on-farm experiments, as well as data processing and writing. You
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its dependency on the pre-fire forest structure and management practices in Fennoscandian boreal forests. Work includes e.g. developing methods to assess burn severity and fuel structure, processing