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Jülich (FZJ). The main objective of the project is to incorporate a memristor-based template library into the processing elements of a cellular neural network in order to achieve programmable parallel
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volume, OpenFOAM, parallel computing, HPC. Knowledge and experience in suspension fluid mechanics, continuous modelling of granular media, non-Newtonian fluids, and smoothed particle hydrodynamics will be
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Introduction to the university’s talent recruitment policy Main forum of the International Youth Scholars Forum Keynote report I Keynote report II 2:00 PM-17:30 Sub-forum of Capital Medical University Parallel
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Learning codes using high performance computing (HPC)” Specifically, the candidate will carry out research tasks for the design, implementation, and evaluation on HPC systems of parallel algorithms in
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simulation environment. Contribute to the implementation of search systems and optimization of the parallelization of AI models or system topology to minimize time and energy consumed. Where to apply Website
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(AWS, Azure/GCP) Experience in open source software development. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques will be valued. Fluency in spoken and written
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including knowledge of PyTorch, Tensorflow, Pandas, Scikit-learn and/or Numpy. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques. Fluency in spoken and written