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of organoids in 96-well plates R and Python programming from YAML in VS Code Statistical analyses using mixed models Personal Skills The candidate should demonstrate: A genuine service-oriented attitude, good
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that can be rapidly deployed in production. The most effective supervised AI solutions rely on a prior, lengthy, and costly image-labelling process by process experts (several hundred labelled images
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), and for evaluating the approach for assimilating this data into the FAO-56 model (existing code). This assignment is part of a project funded by CNES in preparation for the TRISHNA mission and is co
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prototype (high-density surface electromyography). As a key player in the project, you will be involved in a complete process of creating technological "bricks": specifications, programming, characterization
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(Rietveld refinement and PDF analysis), of Dr. Marie-Ingrid Richard’s group at CEA Grenoble, experts in Bragg Coherent Diffraction Imaging (BCDI) and of Dr. Frédéric Maillard group at LEPMI, which is
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). Proficiency in image processing and spatial data libraries (scikit-image, rasterio, GeoPandas). Ability to produce clean, readable, reproducible, and documented code. Experience with version control tools (Git
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. • Experience with advanced optical diagnostics (e.g., high-speed imaging, spectroscopy, pyrometry, Particle Image Velocimetry (PIV), Laser-Induced Fluorescence (LIF), or related techniques) is highly desirable
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the autonomy of some parts of the WDS, those suitable under a paradigm of maximum security, safety and robustness, and the project will take care to frame this autonomy in a global and general concept