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

Università degli Studi di Napoli “Federico II\"; Italia; In loco; EUR 32.000 - 36.000; Tempo pieno

Descrizione del lavoro

Università degli Studi di Napoli “Federico II” in Italy invites applications for a PhD research position in Industrial and Information Engineering. The project aims to develop models, algorithms, and architectures for Digital Twin-enabled Smart Ecosystems, focusing on data interoperability and AI integration across Edge–Cloud–HPC continuum.

Research activities include studying energy consumption of AI models and creating methods to monitor, model, and optimize resource allocation in distributed

Competenze

• PhD in Industrial and Information Engineering.

Mansioni

• Develop models, algorithms, and architectures for Digital Twin-enabled Smart Ecosystems across the Edge–Cloud–HPC continuum.
• Address energy impact of AI by monitoring, modeling, and optimizing energy consumption and resource allocation.

Formazione

PhD 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 Recognised Researcher (R2) Positions PhD Positions Application Deadline 26 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 06/2026 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The research program aims to develop models, algorithms, and architectures for implementing Digital Twin-enabled Smart Ecosystems, with a particular focus on data interoperability and on the integration of AI models, multi-agent systems, and intelligent workflows deployed across the Edge–Cloud–HPC Continuum. The research activities will also address the energy impact of Artificial Intelligence by developing methodologies for monitoring, modeling, and optimizing energy consumption and computational resource allocation, with the goal of enabling efficient, sustainable, and scalable AI solutions for distributed computing environments.

Requirements

Research Field Engineering » Electronic engineering

Skills/Qualifications

PhD in Industrial and Information Engineering