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with AMD MI300A GPU+CPU. 2. Perform benchmarking studies to enhance scalability and achieve high node-level efficiency, surpassing existing AMR frameworks. 3. Contribute to communication optimizations
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population and comparative genomics to examine genetic diversity, selection, pangenome relationships, and functional conservation. You will also develop reproducible GPU- and CPU-based high-performance
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efficient inference. Experience with GPU computing and high-performance or distributed computing environments. Exposure to planning, scheduling, workflow engines, or reasoning systems, and to scientific
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, over 20 dexterous robotic hands and 12 robot arms for real-world data collection and teleoperation, high-resolution tactile skins, and a dedicated GPU cluster with eight NVIDIA H200 GPUs alongside access
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to gather requirements, manage expectations, and balance competing priorities. Experience supporting high-performance or GPU-enabled scientific computing environments, including NVIDIA/CUDA, performance
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or machine learning infrastructure, model deployment environments, or GPU-enabled systems. Familiarity with CI CD pipeline design and automation. Experience with hybrid infrastructure spanning on-premises and
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practices and international standards.Leverage VIB Data Core services, including high-performance computing pipelines and large-scale GPU resources, to scale ML development and deployment. Your profile PhD
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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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-related discipline. 2) Strong programming ability in optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus
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tactile skins, and a dedicated GPU cluster with eight NVIDIA H200 GPUs alongside access to ETH's central compute and the Alps supercomputer at CSCS A multidisciplinary team of mechanical engineers