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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
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Deadline 8 Oct 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
Framework Programme? Not funded by a EU programme Reference Number 2026-10284 Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD project will be carried out in
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is to learn and repeat a path using both electric sensing and underwater vision, combining their strengths to improve robustness and flexibility. Approach This PhD project draws inspiration from
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PhD thesis student (f/m) at ESRF and University of Bath to study CO₂ capture by coupling X-ray Raman
are shortlisted for interview will be invited to apply for the relevant Bath PhD programme at a later date. Working conditions The successful candidate will be enrolled in the doctoral school atUniversity of BATH
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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
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expertise in the fields of vascular brain health, neurosciences, or related field (MD-PhD or PhD profile), while managing multi-founder organizations in a bilingual environment. Translational vision: develop
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and computer vision”, “AI and robotics perception”, etc.. The recruited person will be in charge of contributing to present modules or even developing new modules. He/She will intervene in the Master's
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technologies have demonstrated remarkable performance in areas such as computer vision, predictive maintenance, anomaly detection, quality inspection, forecasting, and decision support, their adoption in
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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