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Field
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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anesthesia care, such as PICC line placements, lumbar puncture, IT chemo, bone marrow aspirates, sedated hearing tests, and phlebotomy. Additionally, the GPU is home to the GI Division's Motility program
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datasets. The Research Associate will: Design and implement high-performance workflows integrating GPU programming, deep learning, and large-scale data integration. Apply advanced methods such as ColabFold
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possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. We don’t believe in “one-size-fits-all
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pipelines for large-scale biological datasets. The Research Associate will: Design and implement high-performance workflows integrating GPU programming, deep learning, and large-scale data integration. Apply
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NASA's Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with
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Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with oceanographers
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and scripting languages. Extensive knowledge of parallel programming techniques, including shared memory and message passing parallel programming, and knowledge of GPU programming. Experience with
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Researcher (R1) Country Singapore Application Deadline 24 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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fields. What we offer State of the art on-site high performance/GPU compute facilities A team of 30+ expert colleagues A family-friendly, green campus with on-site kindergarten Ample training