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the Distributed AI for dependable cyberSecuritY (DAISY) Unit, of FBK-CS, which focuses on developing novel AI-driven methods for cyber threat detection in distributed computing environments, with a particular
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Maps, which represent the entire regional tourism offer based on self-reported information. This enables visualisation of tourism distribution patterns on digital maps and the identification of key
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Italy | about 2 months ago
Infrastructure? No Offer Description The research fellow will contribute to the design, development, and evaluation of methodologies and prototypes that integrate autonomous AI agents (agentic AI) with distributed
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activities through field surveys and data analysis; 4. collection, processing and analysis of samples for environmental DNA (eDNA) aimed at species detection and spatial distribution assessment; 5. performance
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at the geochemical/isotopic characterization and protection of water resources 2. Study of areal distribution, using GIS and geostatistical techniques. 3. Isotopic mapping (2H and 18O) 4. Support for training and
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, Italy), https://phd.unibo.it/etit/en Supervisors: Prof. Anna Guerra, Dr. Francesco Guidi Project Context: The selected candidate will join the ERC Starting Grant project “CUE GO – Contextual Radio Cues
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, modeling, and simulation of electrical power systems for railway and road mobility considering their impact on electric transmission and distribution grids, with particular attention to the integration
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, leadership and communication, positioning you for enhanced career opportunities and empowering you to make a meaningful impact on society. For more details of STEM-CORE, please visit https://www.ru.nl/en
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the doctoral candidate Where to apply E-mail renovate_msca-dn@unicusano.it Website https://www.unicusano.it/wp-content/uploads/concorsi/incarichi_ricerca/2026.02… Requirements Research FieldEngineering
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the entire regional tourism offer based on selfreported information. This enables visualisation of tourism distribution patterns on digital maps and the identification of key segments for sustainability