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working in interdisciplinary teams Clear record of communicating original results in writing and presentations Desired Qualifications: Knowledge of GPU architecture and experience programming GPUs
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. Ability to succeed in an interdisciplinary team and communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest
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oral communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs
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work experience. Experience in contributing to peer-reviewed journal articles and funding proposals. Experience working in high-performance computing environments, including on both CPU and GPU clusters
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other scalable approximations. Experience running large-scale computations on supercomputers (e.g., SLURM job scripts, GPU acceleration, MPI communication). Notes: This is a full-time, 2 year
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service deployments, or publications in AI/science venues. Experience with GPUs and performance optimization of ML at scale. Familiarity with containerization and HPC workflows. For full consideration
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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
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, e.g. HPC cluster (CPUs and GPUs) or cloud. Proficiency with high performance computing and system architecture. Advanced skills and experience associated multiple of the following: artificial