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Assistant/Associate Professor in Embedded and Distributed AI (Tenure Track)

Télécom Paris · Palaiseau

Hybrid 🇬🇧 English
pruning quantization edge computing adaptive learning hardware/software co-design lightweight foundation models (LLM, VLA)

Description du poste

About the role

Telecom Paris invites a talented researcher to join the Autonomous Critical Embedded Systems (ACES) team as an Assistant or Associate Professor. The position is a Tenure‑Track appointment with a prestigious Hi! PARIS Chair and a highly competitive hiring package designed to accelerate your research agenda. A reduced teaching load allows you to focus on cutting‑edge research in embedded and distributed AI for critical systems such as IoT, autonomous vehicles, and robotics.

Key responsibilities

  • Lead independent research projects on AI algorithms and architectures for constrained environments.
  • Develop and maintain scientific collaborations and contractual partnerships.
  • Contribute to curriculum design and deliver teaching in your field with a limited teaching load.
  • Secure research funding and manage large‑scale, interdisciplinary projects.

Required profile

  • PhD in Computer Science, Electrical Engineering, AI or a closely related discipline.
  • Strong publication record in embedded, distributed, or edge AI.
  • Demonstrated ability to obtain research grants and build collaborations.
  • Interest in interdisciplinary work within the Hi! PARIS Cluster ecosystem.

Required skills

  • Model compression, pruning, quantization, and Neural Architecture Search (NAS).
  • Edge computing deployment and optimization.
  • Continuous and adaptive learning techniques with security and resilience guarantees.
  • Hardware/software co‑design for multi‑agent systems.
  • Lightweight foundation models (LLM, VLA) for robotic or humanoid applications.
  • Formal verification methods for safety, real‑time, and cybersecurity properties.

What we offer

  • Prestigious Hi! PARIS Chair and an attractive hiring package.
  • Significantly reduced teaching load to prioritize research.
  • Access to the Hi! PARIS Cluster resources and a vibrant interdisciplinary community.
  • Opportunities to lead large‑scale, high‑impact AI projects.

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