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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 8 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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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 28 days 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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) 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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architectures Analysis and preprocessing of different data types (texts, images,etc.) Review latest literature and data Orchestration and documentation of deep learning experiments Processing and visualization
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. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
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tools such as JupyterHub, and Kubernetes. Experience designing and operating massive-scale GPU and combining CPU/GPU workloads across these services. Design and debug platforms and will work closely with
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optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution
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the future. Here’s how you’ll make a difference: Collaborative research centers (SFBs) are the "Champions League" of the DFG-funded projects (Deutsche Forschungsgemeinschaft). They are spanned over 12 years
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Data Core services, including high-performance computing pipelines and large-scale GPU resources, to scale LLM development and deployment. Your profile PhD in machine learning, computer science