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Field
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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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, Azure) Exposure to GPU computing for data analysis Knowledge of AI/ML approaches relevant to omics data Practical understanding of biostatistics and statistical modeling Experience delivering
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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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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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environment. This includes a HPC cluster with NVIDIA H100 nodes, parallel storage and fast interconnects, dedicated workstations with multiple A6000 GPUs, and web-based services via Microsoft Azure
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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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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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for applications targeting HPC systems Digital twins, especially of HPC systems Development of performance portable software for scalable GPU-accelerated HPC systems using approaches like the Kokkos abstraction
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 13 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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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