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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial
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address complex environmental challenges. About the Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies
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projects. Strong proficiency in the following areas, and the ability to integrate them into complex workflows: Computational design and 3D/4D modeling (e.g., Rhino/Grasshopper, Phyton, Unity, Blender). Point
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Researcher to join the group. The research project is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available
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large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data, it will examine how polarized content influences
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, programming, Linux, data, and infrastructure perspective: short-term projects helping researchers with specific tasks, so that the researchers gain competence to work independently. Provide good role models
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by integrating computational mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns
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. The composition affects the power of the jet and the presence or lack of hadrons is a crucial ingredient in modelling the multi-wavelength and multi-messenger emission of these jets. If the jets are hadronic
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. Integrate environmental, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy
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, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy). Contribute to policy