30 postdoctoral-image-processing-in-computer-science-"https:" Postdoctoral positions at CNRS
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. Postdoctoral researchers will have access to state-of-the-art imaging and cellular biology platforms, as well as a dynamic international research environment. Where to apply Website https://emploi.cnrs.fr
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conduct in vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Develop or adapt high-speed image acquisition and processing methods for simultaneous measurement
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; medicine and biology ; signal and data processing. The recruited person will join the scientific computing team of the laboratory and will also be associated to the INRIA Alpines team, a joint research group
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23 Jan 2026 Job Information Organisation/Company CNRS Department Centre de recherche sur l'hétéroepitaxie et ses applications Research Field Engineering Physics Technology Researcher Profile First
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, library preparation, cell culture, and imaging - Proficiency in computer languages (bash, python, awk, R) - NGS/omics data analysis - Proficiency in statistics for high-throughput data analysis - Generation
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to carry out the following tasks: Development of analysis scripts for the preprocessing and automated processing of functional neuroimaging data; Statistical modeling of imaging data and evaluation
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methodologies. • Proficiency in using computer tools and software dedicated to data processing. Personal qualities: • The postdoctoral researcher must be motivated, rigorous, well-organized, and able to work
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vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Developing or adapting high-speed image acquisition and processing methods for the simultaneous extraction
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has been produced, the postdoctoral researcher (M/F) may be involved in targeted field surveys to analyze and understand the role played by images in mobilization and by the actors who produce and
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in a highly competitive international context. The project aims to prototype energy efficient solutions that will enable the HL-LHC and SKA to reliably process and analyze the huge volumes of raw data