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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 7 days ago
. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09447 Requirements Skills/Qualifications Expected skills include Knowledge on distributed, parallel computing and numerical
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Computational Astrochemistry/Algorithm development for Quantum Dynamics Calculations School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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optimizing and parallelizing workflows to run on compute clusters. This position is ideal for someone who is looking to gain research experience, enhance their technical skills, or is considering graduate
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training and inference of GMMs for large, high-dimensional datasets Explore parallelization strategies to leverage modern GPU architectures Benchmark GPU-based implementations against CPU-based approaches
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Requirements: The candidate must be able to demonstrate a deep knowledge of supercomputing software development for massively-parallel computer architectures, and expertise in working with large-scale software
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or OpenMP. Experience in heterogeneous programming (i.e., GPU programming) and/or developing, debugging, and profiling massively parallel codes. Experience with using high performance computing (HPC
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for the leadership and management of the EPSRC programme grant: Advancing Parallel Mesh Generation and Geometry Representation to Enable Industrially Relevant, High-Fidelity Simulations (REMODEL). The REMODEL project
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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programming proficiency in Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 2 days 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