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6 Jan 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique de Grenoble Research Field Biological sciences Computer science Mathematics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 26 Jan 2026 - 23:59 (UTC) Type of...
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computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal
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genetics and/or evolutionary genetics • Proven experience in bioinformatics and large-scale genomic data processing • Excellent level of scientific English, both spoken and written • Experience with
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processing and synthesizing different types of social and ecological data at various spatial scales, as well as large spatial datasets in R or GIS ■ Experience working with R ■ Experience in socio
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macroscopic and nanoscale investigations on perovskite thin films and optoelectronic devices, in particular solar cells, in order to understand their metastability and the associated processes occurring
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experimental configurations et simulations to induce and study the transformation of silicon. The researcher will concnetrate on problems associated with control processing of pre-strcutures samples/systems
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project focusing on the neural markers of stuttering, the recruited individual will be responsible for the preprocessing, processing, and analysis of data obtained from functional neuroimaging (fMRI
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of developing, indicators to track CO₂ emission trends. Activities Process, calibrate, and validate datasets, including Lidar aerosol data, in collaboration with the Atmospheric Optics Laboratory of Lille
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will contribute to a better understanding of surface annealing processes, with the goal of achieving optimized control over the final material state, taking into account its crystalline structure as
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the creation of high-precision digital twins. Activity 1: Integration of Photometric Stereo in Meshroom - Implement processing nodes for normal field and intrinsic color estimation. - Integrate deep learning