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23 Oct 2025 Job Information Organisation/Company CNRS Department Laboratoire de physique de la matière condensée Research Field Chemistry Physics Technology Researcher Profile Recognised Researcher (R2) Country France Application Deadline 12 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job...
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eco-friendly sensor technologies, favoring collaborations between local industrials and academia and building innovations between local actors to create startups on disruptive technologies. Within
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the I. Foton laboratories at the University of Rennes and the CNRS, the postdoctoral researcher will contribute to the development of a miniaturised optical sensor based on infrared spectroscopy
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evaluation of algorithms for: perception in robotics; sensor based control and navigation ; interactive mobile manipulation; multi-sensor data modelling and fusion. This job offer takes place within
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trophic (phytoplankton growth and loss) variables of the Thau lagoon and the Mediterranean Sea (Station 00SETE) in an innovative way using in situ data from high-frequency automated sensors; 2) linking
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Digital Technologies, a joint project focused on sensor systems for movement analysis brings together the OASiS and SyEnsCES teams, located at the École Normale Supérieure de Rennes. Specifically, as part
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The position is focused primarily on the development of silicon sensors for the vertex
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Experience1 - 4 Additional Information Eligibility criteria DFT with periodic boundary conditions applied to materials; development and implementation of codes or algorithms for materials modelling, ideally in
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are looking for a postdoctoral researcher in the field of image generation algorithms (specializing in Deep Learning) for a 12-month position. The work will take place within the IMAGE research team
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algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters