Assistant/Associate Professor in AI for networks
Référence : 2025-1979247
- Fonction publique : Fonction publique de l'État
- Employeur : TELECOM Paris
- Localisation : Palaiseau
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- Nature de l’emploi Emploi ouvert aux titulaires et aux contractuels
- Expérience souhaitée Non renseigné
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Rémunération Fourchette indicative pour les contractuels Non renseignée Fourchette indicative pour les fonctionnaires Non renseignée
- Catégorie Catégorie A (cadre)
- Management Non renseigné
- Télétravail possible Non renseigné
Vos missions en quelques mots
Who are we?
Télécom Paris, a school of the IMT (Institut Mines-Télécom) and a founding member of the Institut Polytechnique de Paris, is one of the top 5 French general engineering schools.
The guiding mission of Télécom Paris is to train, imagine and undertake to design digital models, technologies and solutions for a society and economy that respect people and their environment.
We are looking for a teacher-researcher in AI for networks, the position is to be filled in the Computer Science and Networks department (INFRES).
There is increasing interest in projects related to AI for next-generation networks and the integration of data science techniques within the supporting infrastructure. The market for advanced networks (5G, 6G, and beyond) is expected to exceed 90 billion\$ in the next decade, with AI being the key driver of this transformation. In this context, MLOps engineers with expertise in both AI and networking will be crucial.
As networks evolve, AI is no longer a centralized layer - it is being embedded and distributed across the network fabric. This has led to the emergence of two distinct but interconnected paradigms: AI for Networks (AI4NET), where AI optimizes and manages network operations, and Networks for AI (NET4AI), where networks support distributed AI workloads, including training and inference. Wireless networks, in particular, present unique challenges—including variable latency, constrained edge computing resources, and the need for efficient spectrum utilization - which require tailored AI-driven solutions. At the same time, virtualized and cloud-native networks introduce their own complexities: containerized network functions (CNFs), and short-lived service chains must operate under stringent latency, reliability, and scalability requirements. Integrating AI into these environments involves balancing competing demands for performance, isolation, and energy efficiency, making the design of robust, adaptive AI solutions a critical priority.
It is essential to explore the limits of AI computation in converged cloud/network systems, and develop practical solutions that balance performance, energy use, and QoS. Addressing these challenges requires expertise in AI optimization, distributed systems, and energy management.
Your main tasks will be to:
- Participate in the design and implementation of courses in the field of AI applied to Networks
- Conduct research in your scientific field
- Participate in and contribute to the scientific activities of the Group in which you works.
- Participate in the development of partnerships, collaborations and contractual relations in the field of AI applied to Networks.
Localisation
À propos de l'offre
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Vacant à partir du 04/07/2025
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Chercheuse / Chercheur
