Job opportunities
Centres Inria associés
Type de contrat
Contexte
<p class="part" data-startline="8" data-endline="8">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).</p>
<p class="part" data-startline="10" data-endline="10">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.</p>
<p><strong>Context:</strong> 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.<br /><br />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.</p>
<h3 id="location-and-research-environment" class="part" data-startline="78" data-endline="78"><span style="font-size: 10pt;">Location and Research Environment:</span></h3>
<p class="part" data-startline="80" data-endline="80">The successful candidate will join a dynamic and international research team at Inria <a href="https://stack.inria.fr" target="_blank" rel="noopener">https://stack.inria.fr</a></p>
<p class="part" data-startline="82" data-endline="82">This Postdoctoral position is part of the SMARTNET project, a collaborative effort between Inria and Nokia, offering strong exposure to both academic excellence and industrial relevance.</p>
<p class="part" data-startline="10" data-endline="10">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.</p>
<p><strong>Context:</strong> 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.<br /><br />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.</p>
<h3 id="location-and-research-environment" class="part" data-startline="78" data-endline="78"><span style="font-size: 10pt;">Location and Research Environment:</span></h3>
<p class="part" data-startline="80" data-endline="80">The successful candidate will join a dynamic and international research team at Inria <a href="https://stack.inria.fr" target="_blank" rel="noopener">https://stack.inria.fr</a></p>
<p class="part" data-startline="82" data-endline="82">This Postdoctoral position is part of the SMARTNET project, a collaborative effort between Inria and Nokia, offering strong exposure to both academic excellence and industrial relevance.</p>
Mission confié
<p style="text-align: left;"><strong>Objective:</strong> 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.<br /><br />In particular, the research will aim to:<br /><br />- Improve the prediction, control, and optimization of utility metrics (e.g., availability, cost, latency, energy, QoS/QoE)<br />- Develop a holistic systems-level framework integrating:<br /><br /> - system states and observability,<br /><br /> - autonomous decision variables,<br /><br /> - external events and uncertainties,<br /><br /> - multi-objective utility functions.<br /><br />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.</p>
Principales activités
<p>- Identify emergent behaviors, feedback loops, and system dynamics in heterogeneous network environments involving local agent objectives and global system goals.<br />- Design and apply systems thinking methodologies (e.g., causal loop diagrams, system dynamics, soft systems methodology) to model complex resource allocation problems.<br />- Develop agentic AI architectures (e.g., autonomous agents, multi-agent systems, agent-based control/orchestration) for distributed decision-making in future networks.<br />- Investigate a video analytics use case as a representative scenario to design, implement, and evaluate intelligent agents, controllers, or orchestrators.<br />- Propose and validate novel adaptive, efficient, and fair resource allocation strategies for bandwidth, compute, storage, and energy in dynamic and heterogeneous environments.<br />- Collaborate closely with a multidisciplinary research team, including network engineers, systems scientists, and industry partners.<br />- Publish research outcomes in top-tier journals and international conferences.</p>
Compétences
<ul class="part" data-startline="53" data-endline="62">
<li class="" data-startline="53" data-endline="53">PhD in Electrical Engineering, Computer Science, Systems Engineering, or a closely related field.</li>
<li class="" data-startline="54" data-endline="54">Strong background in networking, resource allocation, optimization, and/or distributed systems.</li>
<li class="" data-startline="55" data-endline="55">Demonstrated interest in or experience with Agentic AI, autonomous systems, or multi-agent approaches.</li>
<li class="" data-startline="56" data-endline="56">Familiarity with systems thinking concepts, or strong motivation to develop expertise in this area.</li>
<li class="" data-startline="57" data-endline="57">Experience with modeling and simulation tools (e.g., Vensim, Stella, AnyLogic) and/or network simulation platforms (e.g., NS-3, OMNeT++, MATLAB).</li>
<li class="" data-startline="58" data-endline="58">Proven publication record in relevant research areas.</li>
<li class="" data-startline="59" data-endline="59">Knowledge of future network architectures (e.g., 6G, SDN/NFV, edge–cloud continuum).</li>
<li class="" data-startline="60" data-endline="62">Understanding of multi-criteria decision-making, agent-based modeling, game theory, or reinforcement learning is a strong plus.</li>
</ul>
<li class="" data-startline="53" data-endline="53">PhD in Electrical Engineering, Computer Science, Systems Engineering, or a closely related field.</li>
<li class="" data-startline="54" data-endline="54">Strong background in networking, resource allocation, optimization, and/or distributed systems.</li>
<li class="" data-startline="55" data-endline="55">Demonstrated interest in or experience with Agentic AI, autonomous systems, or multi-agent approaches.</li>
<li class="" data-startline="56" data-endline="56">Familiarity with systems thinking concepts, or strong motivation to develop expertise in this area.</li>
<li class="" data-startline="57" data-endline="57">Experience with modeling and simulation tools (e.g., Vensim, Stella, AnyLogic) and/or network simulation platforms (e.g., NS-3, OMNeT++, MATLAB).</li>
<li class="" data-startline="58" data-endline="58">Proven publication record in relevant research areas.</li>
<li class="" data-startline="59" data-endline="59">Knowledge of future network architectures (e.g., 6G, SDN/NFV, edge–cloud continuum).</li>
<li class="" data-startline="60" data-endline="62">Understanding of multi-criteria decision-making, agent-based modeling, game theory, or reinforcement learning is a strong plus.</li>
</ul>
Référence
2026-09823
Domaine d'activité