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Field
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metrics and usage statistics, identify inefficiencies on different levels (CPU/GPU, I/O patterns, etc.) and provide corresponding reports. You will work closely with researchers and HPC users and provide
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programming language (Fortran or C++) The ability to interface with, and potentially collaborate with, NCCS users on the users’ software Excellent interpersonal skills, oral and written communication skills
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one of the above fields Very good expertise in the programming languages Python and C/C++, the numba library, and in applying parallelization techniques using GPU programming (CUDA/OpenCL) and MPI
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in data science, computer science, computational biology, or a related field Solid programming and data science skills, including familiarity with Linux, Python programming, version control, continuous
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computing resources, with additional support involving HPC systems such as configuring GPU nodes, managing Slurm queues, containerising teaching notebooks, and enabling advanced pipelines Promote Robust
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programme of computer science, mathematics, physics, electrical engineering, computational linguistics, or similar with good grades PyTorch skills: experience in training machine learning models with one
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research. Strong technical expertise in large scale data analysis, statistical and simulation tools, machine learning, AI and GPU programming. Experience with one more of these scientific collaborations
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, advancing bioinformatics-driven research, facilitated by exceptional computational infrastructure including a centrally administered high-performance CPU and GPU cluster and network storage. This includes
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Hill consistently ranks as one of the nation’s top public universities . Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using