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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 11 hours ago
. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
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. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development
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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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running smoothly. Collaboration: Work closely with researchers and colleagues to plan maintenance, ensuring the day-to-day reliability of our computing infrastructure. Automation & DevOps: Use scripting and
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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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. The successful applicant will be expected to teach both undergraduate and graduate courses in Psychology and Neuroscience, and to establish an active, internationally-recognized research program. To
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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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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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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