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the use of and scientific application programming for supercomputers Knowledge in GPU-based programming and modelling of scientific simulations are desirable Programming experience in C, C++, or Fortran is
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rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 5 days ago
, synchronization, scalability, and familiarity with GPU programming; strong familiarity with Unix/Linux tools; solid experience with version control, debuggers, compilers, and profiling tools (e.g., perf, gprof
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, and Ising machines. The group possesses strong expertise in magnetic, electrical, and optical characterization techniques (particularly micro-focused Brillouin Light Scattering) and leverages GPU
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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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or more GPUs; ability to work with pre-existing codebases and get a training run going Research interest in one or more of the following: Applied ML, Natural Language Processing, Computer Vision
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molecular dynamics simulations and was specially designed for parallelisation on GPUs. It is open source and licensed under the LGPL. Details can be found on the website https://halmd.org Job-Description
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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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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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- into a GPU-enabled and parallel code to run efficiently on state-of-the-art exascale hardware Designing implementations and reviewing community contributions of library features and new statistical