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). Originally designed to make video games look realistic, GPUs have evolved into powerful engines for scientific computing. Unlike traditional computer processors, which handle one task at a time, GPUs can carry
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ARM architectures, and different GPU or NPU architectures would be a significant advantage. This role demands excellent communication, leadership, and presentation skills, with the ability
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 22 days ago
require repeated and highly accurate solutions of the acoustic (and elastic) wave equation on large-scale 2D/3D domains. Finite difference solvers dominate current industrial codes, but their limitations
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and optimization strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data
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infrastructure, driving the design and evolution of HPC and AI platforms at scale. This role architects and implements next-generation GPU/CPU clusters, high-bandwidth InfiniBand and Ethernet fabrics, large-scale
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 1 month ago
waveform inversion (FWI) and reverse time migration (RTM), which require repeated and highly accurate solutions of the acoustic (and elastic) wave equation on large-scale 2D/3D domains. Finite difference
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-performance computing on CPU and GPU clusters VR/AR or game development for applications including BCI Further information For an informal discussion relating to the role, please contact Prof Damien Coyle
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) for reproducible research workflows. Support Optimising GPU-accelerated workloads (e.g., PyTorch, TensorFlow), including multi-GPU scaling and distributed training. Develop training materials, documentation, and
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 1 day ago
, embeddings with transformers, training with flow matching) and high performance computing (e.g. handling large-scale parallel simulators, multi-node and GPU training on large supercomputers). When considering
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skills to run and adapt hydrodynamical simulations to be run in remote CPU/GPU clusters, and ideally have some experience producing synthetic observations of discs using radiative transfer software