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Field
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role We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training
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engineering. The work involves simulations for quantum error correction and mid-circuit operations, and will require both low-level optimization skills (e.g., SIMD, GPU, FPGA) and an understanding of quantum
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. This project seeks to overcome key workflow and precision limitations in HDR brachytherapy by enabling real-time adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU
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clusters, cloud computing, or GPU acceleration. Strong mathematical background in linear algebra, probability, and statistics. Prior research experience with publications or preprints. The University
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environment with access to domain expertise ranging from cyber-security over AI, electrical engineering, to clinical practice Extensive resources to support your work (e.g., CAD tools, GPU servers, wet lab
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Fellow of AAPM. Details about Dr. Ren’s profile can be found at the following link: https://www.medschool.umaryland.edu/profiles/Ren-Lei/ Equipment includes a computer cluster with high-end GPUs, and state
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 12 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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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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scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI/OpenMP; GPU experience a plus). Record of peer-reviewed publications appropriate to career stage
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and or Python required, experience with wireless testbeds desirable, some familiarity with GPU programming desirable (to support collaboration with NVIDIA) Duke is an Equal Opportunity Employer