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of the collected data. This main goal of this particular PhD fellowship is to develop innovative applications, tools and models for AI game-based learning. Further, in collaboration with a postdoc, the candidate
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of this particular PhD fellowship is to develop innovative applications, tools and models for AI game-based learning. Further, in collaboration with a postdoc, the candidate should establish models, frameworks, and
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to develop state-of-the-art multi-agent communication protocols and innovative educational technologies based on it. Further, in collaboration with a postdoc, the candidate should establish models
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characterize forest structure. Remote sensing data, such as images, lidar, and photogrammetric point clouds acquired from drones, aircraft, and satellites, will play a central role in the development
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of SecurEL. The PhD candidates funded by the Centre will contribute with cutting-edge knowledge and research. Overall, the Centre will directly finance 17 PhD and postdoc positions, and also have several
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“Female Heart”. The researcher position has a temporary financing for two (2) years from 01.11.25. About the project/work tasks: Advanced image analysis of ultrasound images Statistical analysis
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will focus on integration of the extensive amount of data collected by forest machines with remote sensing data to further characterize forest structure. Remote sensing data, such as images, lidar, and
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integrate advanced 3D cell culture, confocal and nano-CT imaging, and cutting-edge transcriptomic techniques, including single-cell and spatial transcriptomics, to map receptor-driven pathways involved in
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of SecurEL. The PhD candidates funded by the Centre will contribute with cutting-edge knowledge and research. Overall, the Centre will directly finance 17 PhD and postdoc positions, and also have several
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utilizing human cell cultures (2D and organoids), advanced fluorescent imaging, live imaging, FACS, RNAseq + bioinformatic analysis, Click-IT technology, RT-qPCR, Western Blot, and possibly animal experiments