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vision researchers to design algorithms specifically tailored for the extraction and analysis of these historical diagrams. EIDA considers these diagrams both as visual heritage and as tools
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the framework of the ANR EmergeNS whose aim is to understand, through mathematical and computer models, the role that autocatalysis, multistability and spatial heterogeneity may have played in the emergence
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-EHESS, located in Paris in the 6th arrondissement. CAMS is a multidisciplinary research unit bringing together mathematicians, physicists, computer scientists and researchers in cognitive and social
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station, computer, access to computer cluster Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-191/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD
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- integration within the BioDiv team at IBENS - availability of work station, computer, access to computer cluster Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-189/Candidater.aspx
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applied mathematics, physics, computer sciences or social sciences with outstanding skills in quantitative methods ; - Provable experience working with social media data, specially very large datasets (we
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Mathematics, Computer Vision, or Data Science. -Knowledge of statistical inference methods and machine learning. -Experience in spectroscopy and imaging is an asset. -Strong programming skills in Python
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the Boolean response of the modal plasmonic processors. The candidate will develop a cw excitation / linear photo-luminescence detection scheme in collaboration with near-field optical microscopy experts in ICB
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. - Experience in coding (python or other computer language). - Proven track record of publications in peer-reviewed journals. - English (written/oral) level of at least B2 (according to the common European
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). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines