Agentic AI resource allocation in networks

Agentic AI for resource allocation in future networks

The Inria center at the University of Rennes is one of eight Inria centers and has more than thirty research teams. The Inria center is a major and recognized player in the field of digital sciences. It is at the heart of a rich ecosystem of R&D and innovation, including highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education institutions, centers of excellence, and technological research institutes.

We invite applications for a Postdoctoral Researcher position focused on resource allocation in future communication networks, with Agentic AI and systems thinking as central methodological approaches. The successful candidate will conduct interdisciplinary research at the intersection of network engineering, systems science, and autonomous decision‑making, addressing challenges of complexity, scalability, and sustainability in next‑generation networks (e.g., 6G, IoT ecosystems, and device–edge–cloud infrastructures).

This position offers a unique opportunity to explore how autonomous, goal‑driven agents can perceive, reason, and act within complex networked systems to optimize performance, cost, and availability under uncertainty.

Context: Device–Edge–Cloud infrastructures combine the architectural and algorithmic challenges of heterogeneous computing and communication environments while introducing new challenges in control, coordination, and adaptation. As application requirements become increasingly dynamic, managing trade‑offs among performance, availability, cost, and energy efficiency across distributed resources is growing more complex. Traditional centralized or static optimization approaches struggle to cope with these dynamics. Agentic AI, combined with systems thinking, offers a promising paradigm to enable distributed, adaptive, and self‑organizing decision‑making across network layers and domains.

Objective: The primary objective of this position is to design and analyze agent‑based and agentic AI‑driven frameworks for the adaptive allocation of network and computing resources in Device–Edge–Cloud environments.

• Improve the prediction, control, and optimization of utility metrics (e.g., availability, cost, latency, energy, QoS/QoE).
• Develop a holistic systems‑level framework integrating:
  • system states and observability
  • autonomous decision variables
  • external events and uncertainties
  • multi‑objective utility functions
• Agentic AI will serve as the main approach to model intelligent agents (e.g., controllers, orchestrators, or digital twins) capable of reasoning, learning, and coordinating at both local and global levels.
• Identify emergent behaviours, feedback loops, and system dynamics in heterogeneous network environments involving local agent objectives and global system goals.
• Design and apply systems thinking methodologies (e.g., causal loop diagrams, system dynamics, soft systems methodology) to model complex resource allocation problems.
• Develop agentic AI architectures (e.g., autonomous agents, multi‑agent systems, agent‑based control/orchestration) for distributed decision‑making in future networks.
• Investigate a video analytics use case as a representative scenario to design, implement, and evaluate intelligent agents, controllers, or orchestrators.
• Propose and validate novel adaptive, efficient, and fair resource allocation strategies for bandwidth, compute, storage, and energy in dynamic and heterogeneous environments.
• Collaborate closely with a multidisciplinary research team, including network engineers, systems scientists, and industry partners.
• Publish research outcomes in top‑tier journals and international conferences.

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours)
• Possibility of teleworking
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities

Please submit online: your resume, cover letter and letters of recommendation eventually

• A motivation letter describing their background, research interests, and vision, and explaining how their expertise aligns with the goals of this position.
• A full CV, including at least two references.
• One to two relevant scientific publications authored or co‑authored by the candidate.

• Interviews will typically be conducted online.
• Applications will be reviewed on a rolling basis, and the position will be filled as soon as a suitable candidate is identified.