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emerging models by collaboratively exploring various computation models leveraging physical devices properties. This PhD work will focus on FPGA devices in order to build an accelerated spiking neural
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the umbrella of the CNRS and the University of Paris-Saclay. The laboratory's research focuses on nuclear physics, high-energy physics, astroparticles and cosmology, theoretical physics, accelerators and
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The PhD work will take place in the framework of the ANR funded HENBoS project (2025 – 2029), which seeks to describe with unprecedented accuracy and scope massive black hole systems as cosmic accelerators
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Accelerator Laboratory (LAL), and the Laboratory of Theoretical Physics (LPT). The laboratory's research topics include nuclear physics, high-energy physics, astroparticles and cosmology, theoretical physics
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of Higher Education and Research (MESR). PINNACLE: Physics-Informed Neural Networks for Accelerated Cloud Light-Scattering Emulation Artificial intelligence is profoundly transforming atmospheric
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the national "Solutions for the Industry of the Future" label. Its objective is to accelerate innovation and promote the development of Industry 4.0 solutions. In the global context of the energy transition and
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fundamental understanding of climate change and its impacts, extending to the development of prototype climate services co-designed by stakeholders and climate modeling experts. The goal is to accelerate
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healthcare. The Exa-DI project, one of the five projects under NumPEx, aims to accelerate the development of exascale applications by providing "development kits" based on the NumPEx software stack, which can
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
solution for deploying accessible embedded AI-based real-time audio DSP systems will be explored. Smartphones provide a large amount of computational power (including AI accelerators in some recent models
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accelerate Europe’s energy transition. This ambitious goal will be achieved by developing advanced experimental and computational tools to characterize e-fuel combustion processes, optimize fuel-flexible