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. Experience in parallel programming (MPI, GPU, etc.). Proficiency in biostatistical methods. Ability to work independently and in group settings. Ability to learn quickly and apply new analytic techniques. Job
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: Ability to work with large structured and unstructured datasets, and GPU-accelerated computing. Proven experience with Large Language Models. Required Skill/Ability 3: Sound background in theoretical and
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analysis, and GPU/FPGA-based acceleration. Ability to work in a multidisciplinary team, collaborate with industry and international partners, and contribute to the design of next-generation electron imaging
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the models and algorithms on GPUs and mainframe computing platforms. Essential Function Yes Percentage of Time 40 Job Duty Mentoring graduate and undergraduate students. Assist the PI (Qi Wang) to mentor
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allowance. Generous travel, equipment, and publication funds. Access to NYUAD’s world-class research facilities, including a high-performance computing (HPC) cluster with ~30,000 cores and 34 GPU nodes. Start
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~30,000 computing cores and 34 GPU nodes. The position may start as early as September 2025. Applications will be accepted until the position is filled. To be considered, all applicants must submit via
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Qualifications: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent
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parallel/GPU computing. Job Duties Job Duty Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research projects
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. This support includes access to a Titan Krios and Tundra TEMs, fast network interconnects, all-flash network storage, high core density CPU servers, and AI-optimized GPUs. The position is for 2-4 years depending
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will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD