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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological
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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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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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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 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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spectroscopic signals in scientific payloads for astrophysics, planetary exploration, and satellite-based earth observation. Space missions such as ISO, Herschel, Webb, and SPHEREx demonstrate the continued
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Website https://phd.fbk.eu/calls/detail/formal-verification-of-configurable-safety-crit… Requirements Research FieldOtherEducation LevelMaster Degree or equivalent Additional Information Work Location(s
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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