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programme launched by the National Research Foundation (NRF) to anchor deep national capabilities in Artificial Intelligence (AI). The programme office is hosted by the National University of Singapore (NUS
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needs as well as the ability to work in teams Desirable qualifications Knowledge of German Special knowledge in one of these areas is a plus: HPC (e.g., Workload Scheduler, CUDA, Infiniband) Storage (e.g
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its
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training in the second area are encouraged to highlight this in their application. Experience with high performance computing and GPU acceleration tools (e.g. CUDA) and deep learning frameworks, such as
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• Familiarity with operating HPC clusters (e.g., bash, Python) Preferred Qualifications • HPC programming skills (e.g., modern Fortran or C/C++) • Parallel programming skills (e.g., OpenMP, MPI, OPENACC, CUDA
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LLM training Bright Cluster Manager Pyxis/enroot CUDA System and storage benchmarking DataDirect Networks (DDN) SFA high-performance storage systems Working Conditions This is a hybrid position, in
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, MATLAB, Git, debugging, and modern software engineering practices. Experience with GPU computing (e.g., CUDA, HIP), parallel computing (e.g., MPI, Actor Model). Familiarity with containerization (e.g
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program at Queen’s, which already includes 38 full-time Faculty and over 200 graduate students and postdocs. The preferred start date for the position is July 1, 2026. Tier 2 Canada Research Chair Canada
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, VMware. Experience building and running containerized applications in an HPC environment. Knowledge of Apptainer, Warewulf, Fuzzball. Experience managing systems using GPU/CUDA clusters for AI/ML and/or
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. Familiarity with data formats common in scientific domains such as medical imaging, genomic sequences, proteins, chemical structures, geospatial, oceanographic, and heath record data. Experience in CUDA GPU