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Field
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research. What about computing power? Well, BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent
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projects, deploying workflows on large-scale computing environments, leveraging ORNL’s Frontier for its dense GPU-based high-performance computing resources to train large GeoAI models. Major Duties
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a broad-based university with a
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, microfluidics, laboratory automation, and GPU computing infrastructure. The opportunity to develop AI methods and scientific software that are directly deployed on cutting-edge experimental platforms. Vacation
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Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable calculus, and linear algebra Exploratory data analysis
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research skills, evidenced by high-quality publications in top-tier machine learning/AI conferences and/or leading scientific journals. Excellent programming skills and hands-on experience with leading
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collaboratively in a research-focused environment. Project background We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in
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track record of open-source contributions. Project background We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in
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2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? Yes Offer Description Our group
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract