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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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both a learning environment and a social arena. Against the backdrop of increasing polarization recent policy developments concerning school safety and crime prevention Schools Against Crime (SOU 2024:14
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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cognitive agent embodied in a humanoid robot Unitree G1 which will collaborate with a human partner to solve a spatial problem (e.g. 3D puzzle). The tasks to be carried out are: (i) scene understanding
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. The research primarily centers on the aesthetic subjects in schools and teacher education, as well as the municipal culture schools, and collaboration. The research represents several areas, such as professional
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with supervisors and collaborators, develop an independent research direction within the theme of photothermal microscopy and its applications, based on your background and emerging project results Contribute
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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thaliana, with selected conditions validated in hybrid aspen, in close collaboration with experts in optical microscopy, plant defence, and synthetic biology. Eligibility and qualifications To be appointed