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patterns, deploying high-performance systems, and ensuring emerging platforms are safely and effectively integrated into the fabric of the university to support institutional strategy. About the Position
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candidates should have a strong background in computer science, parallel computing, compilers, performance optimisation, and high-performance computer systems. Excellent knowledge of C and C++ is
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entrepreneurship, partnerships, policies and procedures, and institutional awards and honours. SciNet, within the division of VPRI, is a University of Toronto advanced research computing facility and
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Übersicht Platform Engineer (HPC & AI Infrastructure) 80%-100%, Zurich, permanent Drucken The High Performance Computing group at ETH Zurich provides world-class HPC and AI/ML infrastructure to
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designing and supporting high-performance computing (HPC) environments, including compute clusters, GPU-enabled systems, job schedulers (e.g., Slurm), and parallel computing workflows supporting
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Research Associate (m/f/x) Mixture of Experts for High
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knowledge in parallel or high-performance computing is desirable, and applicants should be comfortable working on shared HPC clusters. Experience with software engineering practices, including version control
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CRC2 & Mitchell Funded Tenure-Track Faculty Positions in Supercomtuping and High-Performance Computi
Queen's University - Electrical and Computer Engineering, Smith Engineering | Kingston (Downtown), Ontario | Canada | 5 days agoSupercomtuping and High-Performance Computi Employer Queen's University - Electrical and Computer Engineering, Smith Engineering Location Kingston, Ontario (CA) Salary $150,000 to$180,000. Actual
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, and international collaborators. The work will involve large 3D datasets and reproducible computational workflows, including scripted quality control and, when appropriate, parallel processing on high
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modelling is an advantage. Background knowledge in parallel or high-performance computing is desirable, and applicants should be comfortable working on shared HPC clusters. Experience with software