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, United States of America [map ] Subject Areas: Engineering / Computational Science and Engineering , Machine Learning , Quantum Science and Engineering Appl Deadline: (posted 2026/03/05 05:00 AM UnitedKingdomTime, listed
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are in compliance with the necessary trainings (both at the lab and at the institutional level). Minimum Education and Experience: A PhD degree in Computer Science, Electrical/Computer Engineering, or a
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: Knowledge on floating point arithmetic and mixed/reduced precision computing techniques Experience with programming GPUs and/or other accelerators Proficiency in mathematical reasoning and numerical analysis
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, forward-looking, and varied research fields and projects, with numerous development opportunities Modern hardware and infrastructure at the workplace, from compute and GPU servers to supercomputers
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. Due to the interdisciplinary nature of the work, we are looking for a person with a background in performance engineering and high-performance computing hardware (high-performance CPUs and GPUs) as well
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simulated and measured results to assess quantities of interest. Interface with world-class exascale computing clusters. Work with a dynamic team of researchers, developers, experimentalists, and model
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geophysical sciences, computer science, or machine learning with 0 to 2 years of experience Knowledge of deep learning, PyTorch/JAX, and scaling deep learning models to large GPU-based machines Technical
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learning architectures for scientific or high-performance computing applications. Background in software performance evaluation, profiling, and optimization on CPUs and GPUs. Knowledge of common numerical
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
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disease insights. The lab has state-of-the-art computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224