Sort by
Refine Your Search
-
Employer
- CNRS
- European Synchrotron Radiation Facility
- ESRF - European Synchrotron Radiation Facility
- University of Luxembourg
- 3IA Côte d'Azur
- ECE - Paris - Ecole d'ingénieurs
- GUSTAVE ROUSSY
- INSERM
- Imagine Institute
- Inria, the French national research institute for the digital sciences
- Luxembourg Institute of Health (LIH)
- Université Grenoble Alpes
- Université Gustave Eiffel
- Université Paris-Saclay GS Sciences de l'ingénierie et des systèmes
- Université de Lorraine
- Vascular Brain Health Institute
- 6 more »
- « less
-
Field
-
programme, launched in 2021, has expanded to 14 centres across France, with further expansion planned (23 centers already planned). It integrates clinical activities for high-risk individuals with
-
Eligibility criteria - Education: Ph.D. degree in Robotics, Control, Optimization, Machine Learning, Computer Vision for Robotics, or related fields. - Technical Expertise: Strong background in optimization
-
, relies on a minimalist encoding of visual information. Unlike classical computer vision approaches — which require significant computational resources and memory — this method captures and memorizes only
-
vision frameworks, applied machine learning techniques, and medical imaging standards Develop user-friendly front-end interfaces, web dashboards, or software demonstrators to make biomedical image analysis
-
30 Aug 2026 Job Information Organisation/Company ECE - Paris - Ecole d'ingénieurs Research Field Physics Computer science » Digital systems Researcher Profile Recognised Researcher (R2) Leading
-
Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
-
€40 million from the France 2030 program, it will open a dedicated 3,500 m² university hospital facility by 2030, integrating state-of-the-art imaging, advanced laboratories, innovative clinical spaces
-
routes. The visual familiarity principle (ultra-frugal AI), inspired by invertebrate cognitive mechanisms, relies on a minimalist encoding of visual information. Unlike classical computer vision approaches
-
Additional Information Eligibility criteria - Education: Ph.D. degree in Robotics, Control, Optimization, Machine Learning, Computer Vision for Robotics, or related fields. - Technical Expertise: Strong
-
optical systems, force plates, EMG, etc.), as well as devices for field-based and real-life motion analysis and activity monitoring (sensors, wearables, computer vision, digital tools, etc.). Perform motion