PhD “Agentic Network and Flow management in a distributed data architecture for 6G networks” F/M

about the role

Your role is to carry out a PhD thesis on: “Agentic network and Flow management in a distributed data architecture for 6G networks.”

• Context

The rise of artificial intelligence (AI) is radically transforming the telecommunications landscape. AI opens the way to innovative applications requiring the integration of LLM techniques associated with networked AI agents (agentic networks). In this context, it becomes necessary to manage massive flows of heterogeneous data to effectively train AI models and process certain services in real time (inference).

In this context, telecom operators face a major challenge: managing, adapting, filtering, “augmenting” the data (data flows) generated by or for these AI agents, in a constantly evolving environment, while ensuring reliable and relevant responses from LLMs and AI agents.

• Objectives

The thesis aims to study and define a distributed and intelligent management of data flows in operator networks, aiming to feed AI agents with formatted data (data preprocessing for learning new AI models) to be able to dynamically adapt to the needs of services mainly using LLMs.

Locks:

There is no technical model for a distributed dynamic management of data flows for AI in mobile networks, while guaranteeing the reliability of the results.

There are technical locks to be overcome such as:

• Real-time processing: Design architectures capable of processing and analyzing in real time massive volumes of data for AI applications and/or generated by AI applications in a wide area mobile network.
• Heterogeneity of resources: Efficiently manage resource allocation in a heterogeneous environment comprising equipment with varied capacities (NFs plane control, NAS, UPFs, routers mobile terminals of the user plane, edge servers, etc.).
• Robustness and resilience: Ensure service continuity and the quality of allocation decisions in the presence of network disruptions, equipment failures or malicious attacks.
• Scalability: Guarantee the performance and efficiency of the proposed system when scaling up, with an increasing number of nodes and AI applications.
• Interoperability: Design interfaces and protocols that enable the seamless integration of the proposed system with existing and emerging network technologies (5G, 6G, SDN, NFV).
• Confidentiality and security: Develop mechanisms that ensure the protection of sensitive data and the security of the resource allocation system, while preserving its performance.

about you

1/ Skills (scientific and technical) and personal qualities required by the position

• Good knowledge of the data / AI field
• Good knowledge of cloud environments, K8s
• Developer (python, …)
• Fairly good knowledge of data brokers (like kafka, …).
• Knowledge of mobile networks

The candidate must be very open, curious, and enjoy teamwork. He also has a strong work capacity.

2/ Training required (master’s degree, engineering degree, doctorate, scientific and technical field, etc.)

Master 2 or engineering degree in data / AI and / or cloud.

3/ Desired experience

Experience desired in the field of AI / cloud.

additional information

What is the added value of this offer?

You will be integrated into a research team at the forefront of innovation and expertise on the networks of the future (6G). You will be part of a research ecosystem alongside design engineers in anticipation (in the shorter term) allowing the concrete implementation of the concepts studied, and benefiting from various simulation platforms.

The doctoral student will have the opportunity to participate in collaborative projects at the European and global level, in particular around the conceptualization and standardization of future 6G networks. This thesis could have high visibility at the international level since it should make it possible to define innovative solutions that can be proposed to feed into the reflections on the conceptualization of future 6G networks.

department

The ambition of the Innovation Division is to take Orange’s innovation further and strengthen its technological leadership, by mobilizing our research capabilities to fuel responsible innovation for the benefit of people, inform the Group’s long-term strategic choices and influence the global digital ecosystem.

We train experts in today’s and tomorrow’s technologies, and ensure continuous improvement in the performance of our services and our efficiency. The Innovation Division brings together 6,000 employees worldwide dedicated to research and innovation, including 740 researchers. With a global vision and a wide variety of profiles (researchers, engineers, designers, developers, data scientists, sociologists, graphic designers, marketers, cybersecurity experts, etc.), the women and men of Innovation listen to and serve countries, regions and business units to make Orange a trusted multi-service operator.

Within the Orange Innovation Division (INNOVATION), you will be integrated into a research team at the forefront of innovation whose ambition is to shed light on the future in the field of networks and services in order to transform current networks towards the development of AI techniques, network virtualization (NFV), connectivity for the Internet of Things (IoT), etc.

contract

Thesis

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