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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
fields including health, agriculture and ecology, sustainable development. More information, please visit https://team.inria.fr/scool/projects Odalric-Ambrym Maillard is a permanent researcher at Inria. He
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are contributing to the High Energy cosmic-Radiation Detection (HERD) experiment, a next-generation detector for the Chinese Space Station. In parallel, we pursue R&D for future gamma-ray missions and play an active
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the most cost-effective approach in parallel with protocols that are implemented. Among the key duties of this position are the following: Provides key role in the development, execution, management and
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substantially in the past 15 years, from 40 to 120 faculty, in parallel with the remarkable growth of our hospital-based affiliates, as well as the city and county of Denver. Our work is value driven and focused
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single-cell proteomics approaches on patient samples to gain additional resolution on cell-state diversity within tumours. In parallel, you will collaborate closely with a postdoctoral researcher to
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technology. Your main focus will be the improvement and development of solid electrolytes to achieve better (electro)chemical stability with silicon anodes. In parallel, you will investigate strategies
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—governing the co-precipitation process. Leveraging the ASCC supercomputer at UM6P, three-dimensional CFD simulations based on the Reynolds-Averaged Navier–Stokes (RANS) approach will be performed to model two
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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statistical programs using STATA, SAS, and/or R and parallel computing • Learn about and implement novel/unfamiliar statistical methods, depending on the candidate’s skills and project needs • Perform
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techniques); giving mathematical proofs of their correctness and efficiency; building state-of-the-art implementations of these new techniques (e.g., by leveraging data-parallel functional array programming