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division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD also has guaranteed observing time on the Green Bank Telescope, the Very Long Baseline Array
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on them Work on the design, development and operation of GPU and compute cluster systems together with an interactive team Serve as the first point of contact for users for help or problem analysis and
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multiple languages. Proficient on a computer cluster and ideally programming with GPU nodes. Preferred Competencies Knowledge of relevant scientific fields and procedures. Work both independently and in
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Linux kernel internals, computation accelerators (e.g., GPU computing, CUDA), MPI, and OpenMP. Highly resourceful and adept at juggling multiple simultaneous projects. Must demonstrate ability to work
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of six Campus Resource Core Facilities, over 70 Faculty Research labs, and Administrative support staff. Currently, the largest HPC Cluster on campus, it totals more than 10,000 CPUs, 60,100 GPU Cores, and
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. Prior work with databases used for organizing large-scale processing. Prior use of and/or software development with GPUs. Experience with visualization of large data sets. An understanding of how to make
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more than 10,000 CPUs, 60,100 GPU Cores, and over 7,000 Terabytes of storage. Additionally, the number of connected workstations, laptops, and servers totals over 1,000. Windows, Mac, and Linux/UNIX systems
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-efficient designs, GPUs and HPC), Data Science/AI/Machine Learning (e.g., fundamentals, trust and explainability, LLMs, autonomous systems, computer vision), Security (e.g., fundamentals, hardware/software
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-on experience in one or more of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high
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work environment, collaborating with faculty, staff, students, and the broader UChicago community. Experience working with GPUs and remote computing environments. Knowledge of best practices around