PhD " API-based approach for E2E green connected mobility " F/M

Orange SA; Belfort; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

A leading telecommunications company in France seeks a researcher for a position focused on energy optimization in vehicular networks. The role involves developing AI-driven models to enhance energy efficiency in connected green mobility solutions. Candidates should have a Master's degree in computer science or telecommunications, alongside strong skills in Data Science and Machine Learning. Proficiency in both French and English is required, with a focus on innovation and teamwork. This position emphasizes research and technical skills.

Qualifications

• Experience in Data Science or related field.
• Proven skills in Machine Learning.
• Strong knowledge in telecommunications networks.
• Ability to work in international settings.

Responsabilités

• Conduct research on energy optimization in vehicular networks.
• Develop an API-based approach for connected green mobility.
• Predict energy consumption in green V2X networks.

Connaissances

Data Science

Machine Learning (R, Python)

Telecommunications Networks

3GPP Cellular Networks

Curiosity and Creativity

Analytical Skills

Advanced French

Advanced English

Formation

Master of Science or Engineering Degree in computer science, telecommunications, or mathematics

Description du poste

about the role

Your role is to conduct research on the complex resolution of end-to-end energy optimization in vehicular networks involving vehicles, base stations, Cloud/Edge networks, and AI models.

Global Context and Problem Statement
In a world transitioning towards more sustainable and connected solutions, the emergence of connected green mobility represents a major challenge. This evolution is driven by the need to reduce greenhouse gas emissions while offering efficient and integrated transportation solutions. The research context is based on the increasing demand for energy optimization in 5G-V2X networks, resulting from the convergence of telecommunications technologies and connected vehicles. The central problem lies in the complex management of energy consumption across various network elements and vehicles, while ensuring optimal performance. Thus, there is a need to develop innovative strategies to minimize energy consumption while maintaining high service levels.

Scientific Objective – Results and Challenges to Address
The objective of the thesis is to develop an API-based approach for connected green mobility, aiming to optimize energy efficiency throughout the vehicle's journey using AI models capable of accurately predicting energy consumption in green V2X networks, considering operational and mobility constraints. This involves addressing challenges such as modeling energy consumption patterns, optimizing AI algorithms for precise consumption prediction, and seamlessly integrating mobility services into existing infrastructure. Expected results include the design of innovative models and the identification of key parameters influencing energy consumption for scalable connected green mobility. This will guide future energy optimization strategies, and ultimately, the exposure of these results through APIs.

References

[1] Ilhem Souissi, Rihab Abidi, Nadia Ben Azzouna, Tahar Berradia, Lamjed Ben Said, « ECOTRUST: A novel model for Energy COnsumption TRUST assurance in electric vehicular networks », Ad Hoc Networks, Volume 149, 2023,

[2] B. Mao, F. Tang, Y. Kawamoto and N. Kato, "AI Models for Green Communications Towards 6G," in IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 210-247, First quarter 2022, doi: 10.1109/COMST.2021.3130901.

[3] Lv, Zhihan, and Wenlong Shang. "Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review." Green Technologies and Sustainability (2022).

about you

Technical and Personal Skills Required for the Position:

• Proven skills and experience in Data Science.
• Good knowledge of languages associated with Machine Learning techniques (R, Python...).
• Strong knowledge and expertise in telecommunications networks.
• Solid understanding of 3GPP cellular networks, including 5G and 6G networks.

Transversal Skills:

• Strong interest in research and innovation, accompanied by curiosity and creativity.
• Autonomous, motivated for innovation, and enjoys teamwork.
• Ability to address complex problems and propose innovative solutions.
• Rigorous, strong analytical, and synthesis skills.
• Ability to work in an international environment and communicate effectively in written and oral form. Able to vulgarize your work to make it understandable to a wide audience, and you enjoy persuading others.
• Advanced level in French and English (document writing, presentations, meeting facilitation, missions...).

Required Education:

• Master of Science or Engineering Degree in computer science, telecommunications, or mathematics

Experience:

• Experience or internship in research-oriented Data Science will be a plus.