Two Tenure-Track Hi! PARIS Chairs in Robotics & AI at ENSTA (Paris-Saclay)

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Gianni Franchi

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11:50 AM (6 hours ago) 11:50 AM
to ml-...@googlegroups.com, goran....@ensta.fr
Dear colleagues,

We are pleased to announce two tenure-track faculty positions in Robotics and Artificial Intelligence at ENSTA, located on the Paris-Saclay campus. Each selected candidate will hold a prestigious Hi! PARIS Chair, awarded following evaluation by an international scientific advisory board. These Chairs come with competitive hiring packages, dedicated funding for three years, and access to world-class computational and experimental resources. The recruited faculty members will work at the U2IS Laboratory (Unité d’Informatique et d’Ingénierie des Systèmes), which is recognized for its strong research record in human-robot interaction, computer vision, autonomous systems, and learning-based robotics.

Application deadline: April 17, 2026
Start date: September 2026

Open Positions

This posting concerns two faculty positions that are supported by the Hi! PARIS Cluster 2030 program, a major national initiative bringing together top French institutions such as IP Paris, HEC Paris, INRIA, CNRS, and the Université de Technologie de Troyes, with the ambition to build a global center of excellence in AI and Data Science. 


Founded in 1741, ENSTA is France’s oldest engineering school and is consistently ranked among the top engineering institutions in France; in the 2026 l’Étudiant ranking of French engineering schools, ENSTA placed second nationwide, reflecting both research excellence and strong academic reputation. As a founding member of the Institut Polytechnique de Paris (IP Paris), a consortium that includes École Polytechnique, École des Ponts, Télécom Paris, Télécom SudParis, and ENSAE Paris, ENSTA benefits from a world-class research ecosystem and a highly international scientific environment. Located in the heart of the Paris-Saclay innovation cluster, ENSTA offers direct proximity to leading institutions in AI, robotics, and engineering, forming one of the largest research ecosystems worldwide.


Together, both positions aim to reinforce ENSTA’s research in robotics and AI, along the research profiles outlined in the following. 
For both research profiles, applications in unstructured environments, such as assistive robots, search and rescue, or off-road navigation for defense, agriculture, or security, are especially encouraged. Interest in human–robot interaction and embodied AI is a plus.
The successful candidates will join the teaching faculty at ENSTA's Information Science and Computer Science Department (S2I) at the campus Paris-Saclay, and participate in teaching various courses at all levels (engineering programs, master's degrees, continuing education).

1. Large Models for Robotics

The first position concerns research in large models for robotics, aligned with the emerging field of Embodied AI, i.e., extending the capabilities of large language models to physical interaction and robotic control. The goal is to design and train large, multimodal models capable of managing diverse robots across tasks with minimal fine-tuning. Example topics include:

  • Vision-language-action models

  • Multimodal perception and learning

  • Imitation learning and reinforcement learning

  • Transformers and large-scale pretraining for robotics

2. Multimodal Domain Adaptation for Vision Foundation Models

The second position concerns research in adaptation techniques for multimodal foundation models, enabling robust learning and perception in dynamic environments across various applications, including robotics and beyond. Relevant research topics include, but are not limited to:

  • Multimodal models: cross-modal learning with representation fusion of data (RGB/IR videos, 3D, audio, text, proprioception, IoT)

  • Dynamic data: Building efficient representation models of temporal data
  • Online adaptation and learning: Fine-tuning foundation models dynamically
  • Active learning methods: Modeling natural mechanisms for multi-task learning
  • Self-supervised and semi-supervised adaptation: Leveraging unlabeled data for realistic and scalable model adaptation.

Responsibilities

  • Conduct high-impact research in robotics, computer vision, or AI

  • Publish in leading venues and develop industrial and academic collaborations

  • Teach in ENSTA and IP Paris programs in computer science, AI, and robotics

  • Supervise Master’s and PhD students

  • Contribute to innovative bi-campus teaching initiatives

Candidate Profile

Applicants must hold a PhD in Robotics, Computer Science, or related fields, with a strong research record in machine learning, computer vision, or robotics. Teaching experience, teamwork, and international exposure are highly valued. We welcome applicants at all career stages, including outstanding early-career researchers and established scientists seeking to develop ambitious research programs. Candidates will be considered at the Assistant, Associate, or Full Professor level, depending on experience. Many courses are taught in English, and French is not required at hiring.

Application Procedure

Applications must be submitted through the ENSTA recruitment platform (https://enstaparis.recruitee.com/) :

Required documents:

  • Detailed CV and publication list

  • Research and teaching statement (max. 5 pages)

  • Contact information for at least two references

Candidates are strongly encouraged to contact members of the laboratory prior to the application, to discuss and refine their teaching and research plans:

U2IS / laboratory: goran....@ensta.fr

UFR S2I / department: benoit....@ensta.fr

Teaching: alexandre...@ensta.fr

If you have colleagues who may be interested, please feel free to share this announcement.

Best regards,
Goran Frehse

Director U2IS, 

Deputy Director UFR S2I

ENSTA, IP Paris

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