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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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Battery Systems and the COMPEL initiative. Interact with the research team to develop innovative methodologies in battery safety, CFD, and GPU computing. Contribute to applications for external
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Python and/or C++ and modern machine-learning or GPU-computing frameworks is particularly relevant. We do not expect candidates to already be experts in all of these areas. We particularly value
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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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Computing (HPC). Proficiency in programming; experience with GPU architectures, C++, and Python is highly valued. Excellent communication and collaboration skills in English. Soft skills: analytical
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roles on multidisciplinary teams supporting cutting-edge research and engineering projects, deploying workflows on large-scale computing environments, leveraging ORNL’s Frontier for its dense GPU-based
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und Stellenangebote > Academic staff > Wissenschaftliches Personal High Performance Computing Back to News Board Browse in News PhD Position in High Performance Computing
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, engineering and the life sciences. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit
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) or HPC programming (MPI, OpenMP, CUDA, GPU computing) is considered an advantage but is not required Motivation to conduct excellent scientific research and publish in leading international journals
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group working on the LHCb experiment at the Large Hadron Collider. The successful candidate will focus on developing LHCb’s real-time data analysis systems, including the GPU -based software