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culture facility in the Savannah Research Center. Georgia Southern University's Talon High-Performance Computing Cluster is equipped with GPU acceleration and large-memory nodes to support AI-predictive
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goals on our lab website (https://hscrb.harvard.edu/labs/arlotta-lab/). In addition, the Arlotta lab is actively working to foster an equitable and inclusive community. Basic Qualifications · Ph.D. degree
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Within the Faculty of Life Sciences & Medicine (FoLSM), the School of Biomedical Engineering and Imaging Sciences (https://www.kcl.ac.uk/bmeis ) is a cutting-edge research and teaching School dedicated
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GPUs (e.g., B200, RTX 6000 Blackwell Pro, H200) and CPU architectures that, even if they increase complexity, generate the kinds of problems we love! This role in our Operations Team provides support for
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Competencies Experience deploying and optimizing workloads on GPU-accelerated systems. Experience with AI/ML frameworks such as PyTorch or TensorFlow. Familiarity with scientific computing libraries such as
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provide GPU computing for machine learning on Aalto's Triton high-performance computing cluster, alongside industry-standard circuit simulation tools (Cadence, Synopsys, etc.) on our own computing cluster
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), the School of Biomedical Engineering and Imaging Sciences (https://www.kcl.ac.uk/bmeis ) is a cutting-edge research and teaching School dedicated to development, translation and clinical application within
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find and assess the most promising habitable exoplanets around solar-like magnetically active stars? Join us to build next‑generation GPU‑accelerated models of stellar dynamos and connect them
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, e.g in a GPU architecture, and their applications to magnetic phenomena is meriting. About the employment The employment is a temporary position of two years according to central collective agreement
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collaborators and strong access to compute through national GPU systems (NAISS, e.g. Berzelius and Arrhenius) and local GPU infrastructure. Project description The position offers significant scientific freedom