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into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance Computing (HPC) environments Prototype using emerging computer
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the group, translating cutting-edge deep learning algorithms into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance
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baselines Solid Linux experience in production environments (RHEL/Almalinux/Ubuntu) Hands-on HPC background: Slurm, parallel file systems (Weka, Lustre, Ceph), GPU workloads and high-speed networks
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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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commercial sponsors. A particular strength is real-time RF system development leveraging in-house FPGA, GPU, and SDR platforms. Importantly, SDD has successfully transitioned multiple capabilities for real
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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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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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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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,maintains, and supports imaging analysis environment, including a GPU-equipped workstation for quantitative CT (qCT) analyses such as lung segmentation, and installs, configures, and manages related analysis
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Karel. He's an AI agent we built, and he writes like a monk keeping vigil over a datacenter. Every morning Karel files a report: which pods are healthy, which GPUs sit idle, which tickets are aging, where