7 bayesian-object-detection PhD positions at Swedish University of Agricultural Sciences
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insights that inform biodiversity management. The project includes: · Apply of deep learning models to annotate bird and bat species from sound recordings. · Develop a Bayesian statistical
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ecology, biodiversity monitoring, and molecular methods. The project explores how airborne environmental DNA (eDNA) can be used to detect and monitor migratory species, invasive species, and pathogens
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and predict the sensitivity and resilience of Swedish conifer forests to interacting soil fertility and droughts. Specifically, we want to detect whether long-term fertilization practices have modified
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for tracking both the state of and changes in our environment. In this project, you will: deepen your knowledge of sampling for objective data collection, combine different data sources to create cost-effective
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Sweden’s national environmental objectives. Read more about the department: https://www.slu.se/ekologi Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work
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are looking for a PhD student in biogeochemistry of forest soils with a focus on N2 fixation in ectomycorrhizal tubercles. The objectives of the PhD project are to quantify N2 fixation in ectomycorrhizal
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areas include: indicators of functional or taxonomic diversity species-specific or habitat-based monitoring combinations of field data, remote sensing, and modelling new techniques for detecting and