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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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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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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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• 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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, 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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, more than 11,000 faculty and staff and 350,000+ living alumni, UC combines a Top 35 public research university with a physical setting The New York Times calls “the most ambitious campus design program in
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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
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, more than 11,000 faculty and staff and 350,000+ living alumni, UC combines a Top 35 public research university with a physical setting The New York Times calls “the most ambitious campus design program in
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languages such as CUDA. Strong understanding of computer architecture, memory systems and parallel algorithms. Experience with profiling and debugging tools for GPU applications desired, such as NVIDIA