11 parallel-processing-bioinformatics PhD positions at Swedish University of Agricultural Sciences in Sweden
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help reconstruct biodiversity time series and assess how forest management impacts species dynamics. The position will involve lab and field work, bioinformatics, and ecological modeling. Results will
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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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transcription initiation and termination during several years in growing spruces and pines that are exposed to stress. The project includes both wet lab work and bioinformatic analysis. With our research, we will
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approaches (plant physiology, quantitative genetics and bioinformatics) to understand how heritable plastic responses work at both the individual and population levels. The student will be based in the Swarts
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well as high motivation to pursue doctoral studies. Previous experience with plant nitrogen physiology, trees as a model system, genetics, genomics, and bioinformatics are valuable merits. Place of work: Umeå
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, pharmacology, toxicology, immunology, microbiology, bioinformatics, and One Health. We study production animals, companion animals, laboratory animals, and wildlife to advance sustainable animal health, welfare
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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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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