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- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
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results and absence of an explanatory condition) taken as a model of medically unexplained symptoms in adulthood. Analyses will be conducted using data from the French CONSTANCES population-based cohort
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and assembly) (3) the study of their structure and their properties and (4) analytical and numerical modeling. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5031-CORAME0-048
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University. The contract staff recruited will be integrated into the ModES 'Modelling and Spectroscopy' team and will work directly with Dr Morgane VACHER. Where to apply Website https://emploi.cnrs.fr
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 7 days ago
multi-expert segmentation databases. The postdoctoral fellow will focus on integrating segmentation variability into deep learning models, with the goal of assessing prediction reliability and enabling
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loss. In this project, we aim to validate the robustness of the central compensation in optical hearing on animal models that reproduce human hearing impairment. We will also study the underlying
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biology OR virology A solid background in virology, transcriptomics and imaging Hands-on experience with experimental animal and/or iPSCs models Technical expertise in working in BSL-3 environment A
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establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling
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analysis (Higgs physics and searches for Beyond the Standard Model phenomena). The group is in charge of the construction of the outer barrel mechanical structure of the CMS tracker, the integration
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BioEngineering Experience with fluidics devices, 3D printed devices, 3D cell culture models and bioinformatics/computational biology (e.g., R, Python) is an asset Team player Proficient knowledge in English is
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Process: designing, preparing, shaping and characterizing materials in order to discover, control and optimize specific functions. The ICMCB carries out fundamental research on model materials and/or