Methodologies and Technologies for the Development of AI- and Digital Twin-enabled Smart Ecosystems

Università degli Studi di Napoli “Federico II\"; Italia; In loco; EUR 36.000 - 48.000; Tempo pieno

Descrizione del lavoro

Università degli Studi di Napoli “Federico II" in Naples invites applications for a First Stage Researcher (R1) position in the Department of Electrical Engineering and Information Technologies (DIETI). The program focuses on Smart Ecosystems integrating Digital Twins, AI, and Edge–Cloud–HPC infrastructure to enable secure distributed applications.

The role includes designing Digital Twin architectures, developing Generative and Agentic AI for automation and decision support, and addressing

Competenze

• Master’s Degree in Industrial and Information Engineering.
• Education Level Master Degree or equivalent.
• Research focuses on Digital Twins, AI, and Edge–Cloud–HPC architectures.

Mansioni

• Develop Digital Twin architectures and platforms.
• Create Generative AI and Agentic AI solutions for automation and decision support.
• Explore Edge AI for distributed data processing on resource-constrained devices.
• Ensure scalability, interoperability, energy efficiency and sustainability.

Formazione

Master’s Degree in Industrial and Information Engineering

Descrizione del lavoro

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