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Field
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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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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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at http://www.sci.utah.edu/ . Work Environment You will be contributing to cutting-edge computational methods for data management, HPC, edge computing and more. You will work with a diverse team of students
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Position Summary Functional Genomics of circular RNAs in Alzheimer's Disease. The Cruchaga Lab, member of the NeuroGenomics and Informatics Center, is recruiting a motivated, creative, self-driven
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experience in a large distributed computing environment. Previous experience in providing support for Linux HPC cluster used for scientific research. Technical Skills or Knowledge: Experience with installing
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operate equipment to take a full range of routine and complex digital intraoral and extraoral radiographs, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed
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, computer graphics, computer science education, computer vision, cybersecurity, data mining, high-performance computing, human factors in computing, Internet of Things, parallel and distributed computing
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science education, computer vision, cybersecurity, data mining, high-performance computing, human factors in computing, Internet of Things, parallel and distributed computing, social computing, software engineering
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operate equipment to take a full range of routine and complex digital intraoral and extraoral radiographs, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed
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parallel processing, distributed computing, and resource management techniques for efficient resource utilization. Resource Allocation: Oversee the allocation of computational resources, ensuring scalability