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software aspects of large-scale AI systems. Areas of interest may include, but are not limited to: • Advanced accelerator chip technologies, such as GPUs or other specialized chips for large-scale AI
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the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en The position As AI Training Program Officer, you
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fonctionnant sur CPU et GPU, cette thèse de doctorat vise à caractériser la dynamique de ces ondes de choc, leur évolution à long terme et leur signature observationnelle. Cette thèse est financée par une bourse
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-specialists E3 Experience handling large image datasets E4 Experience with HPC, GPU computing, or cloud-based computational workflows. E5 Experience in preparing analysis and presentation of data to publication
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-node GPU training and inference pipelines for foundational models. You'll also develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing
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managing supercomputer resources Strong skills in algorithm development for large sparse matrices Excellency in programming GPU accelerators from all major vendors Very good command of written and spoken
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/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g., concept bottlenecks, prototype
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background Preferred Qualifications • Experience with GPU programming, shaders, or advanced rendering techniques • Experience integrating external APIs or live data streams • Background in distributed systems
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projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities
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international work environment Learn more about CQT at https://www.cqt.sg/ Job Description The CQT S14 team is looking for candidates with strong background in Software Engineering, Computational Physics