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eDNA and Forest Biodiversity Monitoring (TRACE-AIR Project) Research subject Biology Description: The main objective of this PhD project is to use a globally unique and most extensive (1974 onwards
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: The main objective of this PhD project is to use a globally unique and most extensive (1974 onwards) airborne environmental DNA (air eDNA) dataset from Sweden, to test if the air-eDNA method can be used as
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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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to AIDS is highly variable among individuals, developing an average of 9-10 years after infection in most adults in the absence of antiretroviral therapy. The overall objective of the PhD project is to
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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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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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for hypergraphs and partially ordered sets (POSets), funded by the Swedish Research Council. This project is concerned with saturation problems for two classes of combinatorial objects: hypergraphs and posets
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carried out at Stockholm University will focus on prosumers in energy markets in order to inform market design. As an overarching objective, the project will tackle how the rise of prosumers and
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decoupling the key thermoelectric characteristics using a “nanoparticle-in-alloy” design strategy within an inorganic thin-film system. The core objective of the research is to tailor the interface structure
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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