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-based HPC services, this role will involve supporting SAS researchers who use Penn’s new PARCC (Penn Advanced Research Computing Center) centralized HPC services, including both CPU and GPU cutting-edge
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members in designing and integrating solutions into the AI(X) compute, software and data infrastructure stack, hardening these solutions, testing these on modern high-performance GPU compute clusters, and
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architectures. This includes among other: (a) design and implementation of machine learning and GenAI models, (b) efficient training and inference on GPU-based systems, (c) fine-tuning and optimization of large
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compute nodes and over 38,000 CPU cores, over 200 GPUs, 200 TB of memory, 2PB of high-speed data storage, and high-speed networking. The Meteorology program is co-located with the Iowa Environmental Mesonet
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2026, UTC will deploy a state-of-the-art scientific computing and storage infrastructure, comprising a high-memory, GPU-enabled HPC computing node and a modular, scalable RAID-based storage system
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, and interacting with pilots and passengers. Operates and becomes familiar with ground support equipment, such as the aircraft tug, ground power unit (GPU), lavatory service cart, de-icing cart, forklift
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computing (HPC) systems, including GPUs, and programming, such as using CUDA, MPI, AI/ML/DL, and advanced debuggers and performance analyzers. Familiarity with working on open-source projects. About UF
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home to HiPerGator, one of the most powerful high-performance computers at a US public university (https://www.rc.ufl.edu/about/hipergator/ ), and recently added the new AI NVIDIA GPU SuperPod (https
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computing environments for advanced research. B2 Knowledge of scaling and optimising software to take advantage of GPU / HPC infrastructure. Skills Essential: C1 Excellent written and verbal communication
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inference Develop distributed model training and inference architectures leveraging GPU-based compute resources Implement server-less and containerized solutions using Docker, Kubernetes, and cloud-native