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Inria, the French national research institute for the digital sciences | Grenoble, Rhône-Alpes | France | 11 days ago
the supervision of Adrien Taylor and Scott Pesme. The successful candidate will implement and compare different parallel and stochastic numerical optimization paradigms accurately study the selected
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 11 days ago
core of the project is the exploration of leveraging task-based parallel and distributed programming techniques in the DDF-pipeline software components with the aim to accelerate such processing on high
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involving several PhD students and postdocs, and strong regional and international connections, with collaborations with the University of Geneva and CERN. Terms of Employment : The appointments are
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Model The 17-kton Liquid Argon Time Projection Chambers are currently under construction at SURF. Large-scale prototypes are being tested at CERN. The postdoctoral researcher will analyze ProtoDUNE-VD's
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postdocs to the institute’s interdisciplinary AI community; the group also benefits from its proximity to the University of Geneva and CERN. Terms. Position 1 is a two-year appointment; Position 2 is a
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, August). ExaNBody: A HPC framework for n-body applications. In European Conference on Parallel Processing (pp. 342-354). [2] https://github.com/MarcJos/Merope [3] https://github.com/MarcJos/RSA_MPI
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lake and river water levels. In parallel, socio-environmental signals on water-related extremes and pressures will be extracted using natural language processing and text-mining techniques, drawing
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and application of the AgroC agroecosystem model for simulating water, carbon, nutrient and energy fluxes at the field and farm scale Integration of AgroC with the Parallel Data Assimilation Framework
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, and the evaluation of detector performance in the context of physics analyses. FCC-ee has emerged as the preferred option for the next collider at CERN. Designed as a high-luminosity, high-precision
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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing