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. Experience in developing and applying advanced parametric/machine learning postprocessing techniques, producing probabilistic forecasts of hydrometeorological variables, and parallel computing. Proficiency in
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thick and strongly scattering samples. Experience in high-performance computing, parallel programming, or GPU-accelerated computation for large-scale 3D reconstruction. Experience applying machine
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& Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management and analysis solutions that aid in
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, or parallel computing. Strong programming skills. First research experience through peer-reviewed publications is meritorious. After the qualification requirements, great emphasis will be placed on personal
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, Climate Science or a related field. Experience in earth system modeling, data assimilation, and remote sensing of land surface variables. Experience with parallel computing on high performance cluster
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expanding its focus to space-based missions. We are contributing to the High Energy cosmic-Radiation Detection (HERD) experiment, a next-generation detector for the Chinese Space Station. In parallel, we
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, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed tomography scans. Aid dental students, residents and/or faculty in four-handed dentistry and in routine chair
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Researcher (R1) Application Deadline 24 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description A tender is hereby opened
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
(supercomputer/cloud/edge) infrastructures. Developed by the KerData research team in the context of the STEEL project of the national PEPR CLOUD program, E2Clab (https://team.inria.fr/kerdata/e2clab/ ) is a