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of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing
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following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing (HPC
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and have prior experience with remote GPU and HPC services. After the qualification requirements, great emphasis will be placed on personal skills. Target degree: Doctoral degree Information regarding
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or research experience in computer vision or machine learning. • Experience optimizing models for real-time inference on edge and embedded platforms using techniques such as quantization, pruning, and GPU
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megawatts. To transfer energy efficiently from the grid to CPUs/GPUs, higher system voltages are required in data centres/computer racks, and efficient power electronics converter systems based on SSTs
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include: Assist in porting quantum computing optimization codes to CUDA-Q for use with NVIDIA GPUs. Collaborate with NLR researchers on developing formulations and algorithms for solving optimization under
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for mechanical, electrical, cooling, and infrastructure systems that underpin Cornell’s computing environment, including High-Performance Computing (HPC) and Graphics Processing Unit (GPU)‑intensive workloads
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and equipment required for this project, including a confocal optical tweezer system housed in the Henry Royce Institute, an ever-expanding biophysics suite in the School of Bioscience, multi-user GPU
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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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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