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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
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- GPU. What we offer As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below: 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure
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of automation systems for software deployment, configuration management, CI/CD, and environment lifecycle processes. Partner with researchers and domain experts to optimize applications for CPU/GPU architectures
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cases of next generation wireless communications systems. For details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom We're looking for people driven by excellence, excited about
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experience with accelerated architectures (e.g., GPUs or other accelerators) Experience with performance analysis, profiling, and optimization. Note that it is not necessary to fulfil all of these requirements
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influence the technological trajectory of the ecosystem. The core responsibilities of this position include developing and owning the overall SoC specifications and architecture, encompassing CPU, GPU, memory
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programme Reference Number AE2025-0506 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0506
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GPU clusters to enhance efficiency and scalability. Knowledge, Skills, and Abilities: Good communication and teamwork skills; Strong skill in large language model customization techniques including
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 2 months ago
methods (SFEM) offer superior accuracy per degree of freedom and are naturally suited to HPC architectures (CPU/GPU clusters). Two main Galerkin formulations exist: Continuous Galerkin (CG-SFEM): Memory
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | about 1 month ago
imaging datasets across modalities (X-ray, ultrasound, MRI). Scalable ML workflows: GPU-based training, experiment tracking, reproducible pipelines, model validation and deployment. Research excellence