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Field
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that integrates emerging non-volatile memory (RRAM or MRAM) with conventional I/O interfaces. This platform will showcase compute–memory co-design advantages, including enhanced data throughput, improved energy
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the thermal process from GPU computation to radiative cooling Integrate the algorithms into a larger computational satellite simulation environment Identify new cyber-physical systems research topics related
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components, including model runtimes, memory managers, schedulers, accelerator kernels, isolation mechanisms, and distributed communication, which significantly increases their trusted computing base and
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7 Sep 2026 Job Information Organisation/Company Fundació per a la Universitat Oberta de Catalunya Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc
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runtimes, memory managers, schedulers, accelerator kernels, isolation mechanisms, and distributed communication, which significantly increases their trusted computing base and attack surface, but also make
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. We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in Europe. The team counts more than a dozen full-time
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Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis
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the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by
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December 2032. About Us The ML Cloud team designs, runs and safeguards high-performance computing infrastructure tailored to machine learning workloads. Our state of the art systems are distributed across
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network analyzers, etc.) supporting bands up to 110 GHz. These capabilities complement a nearly $10M investment in secure computing infrastructure, housing expansive GPU and CPU clusters. Motivated