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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
Engineer will support the development and operation of the GPU-accelerated, real-time data analysis pipelines that will turn images from the world’s largest digital camera into discoveries. Three years
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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metrics and usage statistics, identify inefficiencies on different levels (CPU/GPU, I/O patterns, etc.) and provide corresponding reports. You will work closely with researchers and HPC users and provide
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Vibrant campus life with a strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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oversights in science and IT research. We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences. If you
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global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in the world. Being a part of
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learning frameworks such as PyTorch, JAX, or TensorFlow. Experience with C++ and GPU programming. A strong growth mindset, attention to scientific rigor, and the ability to thrive in an interdisciplinary
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Facility computing infrastructure supports the diverse needs of over 2,500 researchers in the six UC Davis colleges and schools, totaling some 48,000 CPUs, over 200 GPU nodes, and dozens of petabytes in user
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infrastructure supports the diverse needs of over 2,500 researchers in the six UC Davis colleges and schools, totaling some 48,000 CPUs, over 200 GPU nodes, and dozens of petabytes in user data storage. Each