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and image processing. Prior experience with data fusion, machine learning, or super-resolution methods will be considered an asset. Candidates should be motivated to conduct independent scientific
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 16 days ago
opportunity in computational inverse problems in the context of the ERC-StG European project Incorwave which aims to develop advanced numerical and mathematical strategies for passive imaging. This postdoctoral
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present on expedient osseous tools. This methodological breakthrough relies on discriminant analysis of surface textural data (ISO 25178 and SSFA) acquired by confocal microscopy combined with image
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The IMMENSE project is funded by the University of Lille, France. Our overarching goal is to image
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multitechnique approach, using ion beam imaging/spectroscopy, for example. In this context, the postdoctoral associate will be in charge of developing an operando/in situ cell compatible with ion beam analysis
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 10 days ago
of this project is to develop advanced numerical strategies for passive imaging of the Earth and the Sun. The position focuses on enhancing the capabilities of our massively parallel software, Hawen (https
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-leading international research facility for synchrotron X-ray imaging, located in a dynamic, multicultural environment in the heart of the French Alps. Beamline BM05 is dedicated to micro-CT, topography and
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monitoring using SAR and multi-spectral images, GIS, scientific programming - English proficiency, team work, reporting, redaction of scientific publication, organization and project management
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medicine. State-of-the-art core facilities (imaging, histology, cytometry, cell culture, etc.) are available onsite. The successful candidate will work on a project funded by Open Innovation AstraZeneca and
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(photogrammetry, multispectral imaging, and LiDAR) will be used to finely characterize road edges in relation to hydrosedimentary transfers. On smaller scales, aerial data (IGN LiDAR data and IGN BD Ortho IRC ortho