PhD "Dynamic orchestration of distributed AI for energy-efficient 6G networks"
ref :2025-43456 | 01 Apr 2025
apply before : 30 Sep 2025
- 44-46 Avenue de la République, 92320 CHATILLON - France
about the role
Your role is to carry out PhD thesis on: “Dynamic orchestration of distributed AI for energy-efficient 6G networks”. This thesis will be carried out within the TREES collaborative project, which aims to reduce the carbon footprint of 6G networks by integrating distributed federated learning (DFL) as a tool for predicting orchestration actions and improving energy efficiency. DFL is an Artificial Intelligence (AI) paradigm, one of whose benefits is that it is considered more energy efficient. To achieve this goal, TREES will (i) design a new DFL architecture and algorithms to limit energy consumption; (ii) propose methods for pooling data and learning between several applications, taking advantage of the data partitioning offered by federated learning; (iii) develop network orchestration algorithms and AI functions to minimize the carbon footprint of deployed applications; (iv) set up, on an experimental environment, an autonomous network administration loop integrating the various tools developed in the project and real-world data to evaluate two use cases: “Leveraging Smart Power Grid for Telco” and ‘Energy-aware Multi-Tenant AI Function Orchestration’.
The objective of the PhD is the design and dynamic placement of distributed AI function topologies on network topologies and their integration on a testbed.
The main deliverables are:
- Integration on an Orange testbed.
- Evaluation on use-cases defined with project partners.
- Implementation or extension of open-source projects.
The main scientific challenges identified are:
- Dynamic placement of AI functions on network topologies, balancing the load (of data) on AI functions, considering the non-idd or idd nature of this data
- Lifecycle management of these AI functions
- Designing a frugal solution to control energy consumption and carbon footprint, while preserving QoS and security.
The approaches envisaged to overcome these obstacles are:
- Extending a Data Pipeline System to dynamic architectures
- Possible algorithmic approaches: Monte Carlo search algorithms, Reinforcement Learning, Federated Learning
- Consideration of cross-dependencies between telecom and energy networks
- Considering the specific constraints of distributed Federated Learning
about you
Your academic background or experience include courses in Optimization/Operational Research and/or Machine Learning.
You are methodical, autonomous, and curious.
You are willing and able to work as part of a project team with several partners.
You are fluent in written and spoken English.
You can present scientific work to an audience.
Being fluent in French, both spoken and written, would be a plus.
You have a master’s degree in computer science or applied mathematics.
Internship experience in Optimization/Operational Research and/or Machine Learning would be a plus.
A first experience of scientific publication would be a plus.
additional information
This PhD thesis contributes to one of Orange Group's major objectives which is to reduce its carbon footprint, with the aim of achieving carbon neutrality for the Orange Group by 2040: https://www.orange.com/en/commitments/to-the-environment/net-zero-carbon-by-2040
The PhD thesis is part of a collaborative project from Agence Nationale de la Recherche (ANR) that includes the universities of Avignon, Paris Dauphine and the CNAM in Paris as partners.
department
Orange Innovation brings together the research and innovation activities and expertise of the Group's entities and countries. We work every day to ensure that Orange is recognized as an innovative operator by its customers and we create value for the Group and the Brand in each of our projects. With 720 researchers, thousands of marketers, developers, designers and data analysts, it is the expertise of our 6,000 employees that fuels this ambition every day.
Orange Innovation anticipates technological breakthroughs and supports the Group's countries and entities in making the best technological choices to meet the needs of our consumer and business customers.
At the heart of Orange Innovation, the "Networks" Division is in charge of designing, integrating, and operating efficient and sustainable networks for all Orange Group operators and business units.
In a Telco/IT ecosystem undergoing deep transformations, it defines the Group's strategy for networks and IT infrastructure. Actively working on the development of 5G "stand-alone" and the new technologies it relies on, the Division also contributes to the definition of the networks of the future, such as 6G.
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