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. Working collaboratively with clinical anesthesia staff, GPU nursing and multiple referring BCH specialty providers. Communicating necessity, preparation, nature, and anticipated effects of anesthesia
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conducted in collaboration with NVIDIA, leveraging state-of-the-art GPU-based simulation environments and AI platforms. The position will be hosted within the Medical Imaging and Robotics group led by Dr
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these codes in C++ or Fortran Adopting these codes for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in
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prediction. Working with the Principal Investigator (PI), the candidate will be responsible for the operation and administration of multiple projects spanning three consortia: (i) OpenFold for developing
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of the Postdoctoral Research Associate includes contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will
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preferred). Essential Functions of Position: Manage and maintain multiple GPU clusters and networked storage systems. Monitor system performance, troubleshoot hardware issues, and coordinate repairs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
collaborate with colleagues from multiple universities across the Research Triangle, the United States, and even the world. Position Summary The Research Assistant (RA) will support advanced research in
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site-specific and realistic radio propagation data through GPU-accelerated ray tracing to train AI/ML algorithms. Exploring the use of generative models for wireless channel modeling, e.g., to produce
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with AI inside HPC applications is considered a plus. Experience with performance modeling (such as computer architecture simulation) for multiple types of computer hardware (e.g. CPU/GPU/NPU, or network
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of the Postdoctoral Research Associate includes contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will