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and writing scientific code - Knowledge of at least one of the parallel programming paradigms (MPI, OpenMP, GPU) - Proficiency in both spoken and written English is essential (work will be carried out
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construction of a new dataset from Subaru Hyper Suprime-Cam (HSC) and N-body simulations and science projects using those datasets. In addition, the successful candidate will be required to maintain a new GPU
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 24 days ago
collaborators # Ability to set individual goals, self-structure and fulfill milestones # Parallel programming, ideally in C++ and with GPUs # Knowledge with Python # Excellent command of English (spoken and
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algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
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programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
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development. You’ll have access to state-of-the-art high-performance computing infrastructure and GPU clusters essential for conducting cutting-edge AI, software engineering, and security research. Salary range
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would
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communication skills. First-author publications at NeurIPS, ICLR, ICML, AAAI, KDD, or IJCAI. Experience working with large-scale, noisy, or real-world datasets. Experience with GPU-based training and high-performance
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. Skilled in MATLAB and Python. Experience with C++ and GPU programming (CUDA) is an advantage. Ability to work in a team, communicate effectively, coordinate multidisciplinary collaborations, and manage