Mines Saint-Etienne
Just Landed
Posted Yesterday
PhD in Orchestrating Concurrent AI Services on Constrained Industrial Edge Devices Mines Saint-Étienne in France
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
France
University
Mines Saint-Etienne

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
About this position
PhD opportunity in France on Orchestrating Concurrent AI Services on Constrained Industrial Edge Devices. The project focuses on how multiple AI applications can share limited computing resources on industrial edge hardware such as NVIDIA Jetson, MCUs, and NPU-enabled devices, reducing the need for additional hardware while improving efficiency.
Research directions include AI/ML resource orchestration and scheduling, Edge AI and distributed intelligence, Federated Learning for industrial cybersecurity and intrusion detection, Split Learning and TinyML, energy-aware and multi-objective optimisation, model compression/pruning/quantisation/knowledge distillation, Neural Architecture Search (NAS), IoT–Edge–Cloud / 5G-6G networking, and privacy, robustness, security, and bias in Federated Learning. The project also emphasizes real-world Industry 4.0 deployment and evaluation.
Supervision is listed by Guillaume Muller (Mines Saint-Étienne), Rosario Patane (Telecom SudParis), and thesis director Nadjib Achir (Inria Saclay). The project is expected to involve industrial collaborations with Orange, Siemens, and NVIDIA, plus access to industrial testbeds, datasets, and deployment environments.
Ideal applicants should have a background in Machine Learning / Deep Learning, Python and/or C/C++/Rust, Edge AI / IoT, Federated or Distributed Learning, Networking / SDN / 5G-6G, cybersecurity, or embedded/resource-constrained computing. Experience with Jetson, Raspberry Pi, MCUs, NPUs, or similar platforms is an advantage.
Expected start: November 2026. Location: Lyon area and Évry/Palaiseau, France. To apply, send a CV, personalised motivation letter, academic transcripts, and at least one reference contact to the supervisors by email. Applications should be tailored and show a genuine understanding of the research topic.
Funding details
Available
What's required
Motivated candidate with a background in Machine Learning or Deep Learning, Python and/or C/C++/Rust, Edge AI or IoT, Federated or Distributed Learning, Networking or SDN or 5G-6G, cybersecurity, or embedded/resource-constrained computing. Experience with Jetson, Raspberry Pi, MCUs, NPUs, or similar edge platforms is an advantage. Applicants should provide a personalised motivation letter and demonstrate a genuine understanding of the proposed research topic.
How to apply
Send a CV, personalised motivation letter, academic transcripts, and at least one reference contact by email to the listed supervisors. Tailor the application to the research topic and avoid generic submissions.
More information can be found here
Ask ApplyKite AI

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.