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Field
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obtained. The simulation activities must be conducted using high-performance scientific computing systems, with particular reference to the use of advanced architectures and GPU accelerators, in order to
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minimum of ten years of experience in high-performance computing, including five or more in a leadership capacity managing large-scale GPU-based systems; a strong technical background in HPC infrastructure
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 11 hours ago
operational improvements. PREFERRED: Familiarity with IT service management frameworks, vendor coordination, and GPU or cloud-based infrastructure. Revised 12/19/2025
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 11 hours ago
GPU computing; scripting in Python or Bash; and container orchestration tools like Docker and Kubernetes; and experience in cloud-based HPC or AI/ML workloads. 12/3/2025
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. Conduct experimental studies using GPU-enabled computing resources for model training, inference, and simulation-based evaluation. Support rapid prototyping and iteration of research ideas, from concept
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
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commonly used on Unix systems. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP
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programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
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GPU utilization and allocate computing resources efficiently across users. c) create and manage user accounts for faculty and students; troubleshoot user issues; and design and deliver
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administrative use of Macs and Windows, as well. The Division's research and teaching bring a strong requirement for GPU compute and mass data storage, with GPU workstations across large parts of the Division, HPC