16 image-processing-"Embry-Riddle-Aeronautical-University" PhD positions at Swedish University of Agricultural Sciences
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conventional harvesting. The research will involve practical DNA sampling, high-throughput genotyping, and data fusion using machine-generated harvest data, annotated images, and environmental information
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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
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production and bioelectrochemical systems. Their role becomes especially important under stress conditions, where slow growth and fragile cooperation can limit process performance. When this microbial teamwork
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the condition of Swedish surface waters with respect to water chemistry, pollution and aquatic biota. The research focuses on geochemical and hydrological processes, aquatic ecology and biodiversity, microbial
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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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combination of field-based sampling, controlled laboratory assays, computer-based data-driven analysis, and social science surveys. What we offer: · A supportive and collaborative research environment
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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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fields) with a focus on farm animal behaviour and welfare. interest and/or experience in animal behaviour, experimental studies, statistics, and computer-based data analysis. strong communication skills in
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membrane separation processes for separation of fat and proteins, as well use a number of techniques for physico and chemical charaterisation of the streams obtained. Experience within these fields is a
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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