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programming, GPU programming) Astrophysical fluid dynamics and/or magnetohydrodynamics Radiative transfer in astrophysics Machine learning or data analysis for physical sciences Strong programming
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: computer graphics or computer vision, machine learning, 3D reconstruction or representation, GPU programming or high-performance computing, robotics or embodied AI, geometry processing, scientific
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and comprehensive grasp of how GPU architecture affects performance for datacenter applications, especially Large Language Models (LLMs) Drive the discovery of opportunities for innovation in GPU
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mathematics, computational science or a related field. Solid programming skills (e.g. C++ and Python); experience with GPU computing (CUDA), high-performance computing or machine learning is a plus. A
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networks, and deploy scalable solutions on modern HPC and GPU-accelerated systems. This role includes supporting climate and geophysical science applications, enabling large-scale AI training and
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science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed
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, memory, computational resources, robustness, and adaptability matter alongside conventional accuracy measures? Depending on the research direction, the work may range from low-level GPU and systems
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coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
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electromagnetics-related field with a solid background in computational electromagnetics and a good understanding of the physics of scattering and antenna radiation. Programming experience in C/C++ is
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, infrastructure reliability, and secure multi-GPU model serving, ensuring our team delivers exceptional and groundbreaking results. Your primary responsibilities include: Evaluating generative and agentic AI