PhD in Scalable Network Digital Twins via Adaptive Fidelity Management

This PhD position at Université de Technologie de Compiègne (UT Compiègne) focuses on advancing Network Digital Twins (NDTs) for next-generation communication systems like 6G. The project aims to address the challenge of maintaining accurate, real-time virtual representations of highly dynamic networks—such as those integrating Open RAN, edge computing, and massive IoT—by designing an Adaptive Fidelity Management framework. The candidate will contribute to real-time optimization, predictive analytics, and resource-efficient NDTs, bridging gaps between physical and virtual network synchronization. The work aligns with cutting-edge research in software engineering, distributed systems, and AI-assisted network management. Applicants should have a strong background in computer science, software engineering, or related fields and a passion for tackling complex, real-world challenges in telecommunications.

• Design and develop an Adaptive Fidelity Management framework for scalable Network Digital Twins (NDTs) in highly dynamic communication networks.
• Implement AI-assisted prediction mechanisms to reduce synchronization overhead between physical and virtual network representations.
• Conduct real-time network optimization, operational what-if analysis, and troubleshooting using NDTs.
• Validate the framework through simulations and experimental deployments in 6G and beyond network environments.
• Collaborate with industry partners (CEA) to ensure practical applicability of the research outcomes.
• Publish findings in top-tier conferences and journals within the fields of telecommunications and software engineering.