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project focuses on developing ultra-reliable spatiotemporal (4D) predictions using trustworthy, distributed AI-driven intelligence deployed across heterogeneous aerial nodes. To achieve this, an aerial
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PhD project investigates how children distribute visual attention across verbal and non-verbal communicative signals during storytelling. You will examine: children’s visual attention during
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, combining street-level information, citizen-generated data, and spatial analyses to assess how visible, accessible and equitably distributed different kinds of green spaces are. A key part of your work will
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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negatively impacting the growth performance by optimizing feed structure (particle size and distribution, and fiber fractions) of pigs and broiler diets. Furthermore, we aim to evaluate Near-Infrared
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; the use of AI in policymaking and in policy-relevant research; the distributional consequences of AI at local, national, or international levels; and how AI may affect citizens’ trust in government
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the coupled response of the tunnel and surrounding soil. Conventional techniques—such as visual inspection, strain gauges, and convergence measurements—often fail to detect distributed or deep-seated defects
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mental health condition in African urban centres. It will map various gambling practices to provide a better overview of the nature and prevalence of practices, their distribution and some of its root