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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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Microscopy Center. The project further benefits from excellent dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. This is a full-time, two-year
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. Knowledge and Professional Experience: DFT-based methods. Scientific programming in Fortran, in MPI/OpenMP-parallelised codes. Knowledge of other languages (in particular python) and of GPU offloading will be
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. Experience with graph-based data analysis or anomaly detection methods. Exposure to high-performance or GPU-based computing environments. Demonstrated ability to contribute to publications or technical reports
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tracking), dataset curation, HPC/GPU programming, blockchain for secure data, C-family languages, and embodied AI/robotics are a plus. Experience with general network resilience, cellular automata
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on retrospective Danish data. The research will include testing different levels of model scaling in terms of data amount and diversity, and training will take place both on a local GPU cluster and on the Gefion
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
. The postdoctoral scholar will be expected to improve on existing GPU-accelerated ocean models and develop laboratory experiments (in the Joint Fluids Lab at UNC), analyze results, publish in peer-reviewed journals
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(Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD also has guaranteed observing time on the Green Bank
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, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based