Descrizione dell'offerta
Organisation/Company Università degli Studi di Napoli “Federico II" Department Department of Electrical Engineering and Information Technologies (DIETI) Research Field Engineering » Electronic engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application Deadline 6 Oct 2026 - 12:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Offer Starting Date 25 Sep 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number RIF. DIETI 07/2026 Is the Job related to staff position within a Research Infrastructure? No
Offer Description The research program aims to develop methodologies, models, and architectures for the implementation of Smart Ecosystems based on the integration of Digital Twins, Artificial Intelligence, and Edge–Cloud–HPC distributed infrastructures. Research activities will include the design of Digital Twin architectures and platforms, the development of Generative AI and Agentic AI solutions for process automation and decision support, as well as Edge AI methodologies for distributed data processing and the efficient deployment of AI models on resource-constrained devices. Particular attention will be devoted to scalability, interoperability, energy efficiency, and sustainability, with the goal of enabling reliable, resilient, and secure intelligent ecosystems for distributed applications.
Requirements Research Field Engineering » Electronic engineering Education Level Master Degree or equivalent
Specific Requirements
Master’s Degree in Industrial and Information Engineering
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Offer Description The research program aims to develop methodologies, models, and architectures for the implementation of Smart Ecosystems based on the integration of Digital Twins, Artificial Intelligence, and Edge–Cloud–HPC distributed infrastructures. Research activities will include the design of Digital Twin architectures and platforms, the development of Generative AI and Agentic AI solutions for process automation and decision support, as well as Edge AI methodologies for distributed data processing and the efficient deployment of AI models on resource-constrained devices. Particular attention will be devoted to scalability, interoperability, energy efficiency, and sustainability, with the goal of enabling reliable, resilient, and secure intelligent ecosystems for distributed applications.
Requirements Research Field Engineering » Electronic engineering Education Level Master Degree or equivalent
Specific Requirements
Master’s Degree in Industrial and Information Engineering
#J-18808-Ljbffr
Candidatura e Ritorno (in fondo)
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