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, particularly in forested and densely vegetated environments. Airborne LiDAR have demonstrated strong potential to penetrate vegetation and reveal micro-topography, yet many challenges in data processing
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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Job related to staff position within a Research Infrastructure? No Offer Description The design process of complex systems must guarantee not only the functional correctness of the implemented system
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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of the city, including the effects and impacts of external changes (eg, climate change) and internal processes (eg, urban transition policies and incentives). A challenge for the development of Urban Digital
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a strong background in artificial intelligence and 3D computer vision, with solid programming skills and an interest in 3D data processing (e.g. point clouds and neural scene representations), along
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processes for operational carbon reduction (mitigation) and simulate microclimate interventions to reduce heatwave vulnerability (adaptation). Where to apply Website https://phd.fbk.eu/calls/detail/urban
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Job related to staff position within a Research Infrastructure? No Offer Description How we measure and define performance shapes the systems we build. Current Natural Language Processing (NLP
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of artificial intelligence across public administrations and enterprises. Its impact, however, will depend on how legal obligations are translated into organizational processes, procurement strategies, and
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technical performance but also the impact on clinicians’ work practices, decision-making processes, and overall quality of care. The project aims to contribute a methodologically grounded and clinically