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Field
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background Preferred Qualifications • Experience with GPU programming, shaders, or advanced rendering techniques • Experience integrating external APIs or live data streams • Background in distributed systems
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for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components
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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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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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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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multiphase flows Your tasks Develop and extend the in-house GPU-accelerated multiphase Lattice Boltzmann (LBM) code for DNS-grade boiling multiphase flow related to nuclear reactor operation, including bubble
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 7 days ago
approaches for automated medical devices (e.g., physiologic closed-loop controlled devices). Developing multi-spectral computational modeling tools using GPU-based processors to map light propagation
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samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize, and validate a refractive