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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 1 month ago
- Parallel Programming (emergency posting) Course description: Introduction to aspects of parallel programming. Topics include computer instruction execution, instruction-level parallelism, memory system
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Roth at Perrett Laver on Claudia.Roth@perrettlaver.com . Applications close at 9am AWST, Monday 29 September. Perrett Laver will conduct an executive search process in parallel with the public
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computing architecture and/or system software such as massively parallel computing, big data infrastructure, large-scale data system, or system software in general has been considered as important
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parallel computing systems. Familiarity with git and GitHub. Experience building pipelines for the processing of medical images. Fluency in Python programming language. Familiarity with Bash. Excellent
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research environments Hands-on experience managing HPC clusters, job schedulers, and parallel file systems PREFERRED QUALIFICATIONS Experience in a university or research institution setting Knowledge of IT
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parallel programming; and tracking the use of HPC resources and the resulting research outcomes and publications. verall, the position provides leadership and guidance on facilitation services and reports
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tissue referred to the Department of Pathology from outside coroners, hospitals, or foundations. These would be logged in through the department and may be processed using individualized protocols. Work
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equality and diversity as a strength and an asset. Description of the workplace: The Neurodegenerative Research group is focused on defining and understanding biological processes in Alzheimer’s disease and
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an enrollment of approximately 5,000 students in occupational/technical programs and university-parallel/college transfer programs. Teach 18 credit hours (in-person day and evening classes as well as synchronous
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is focused on defining and understanding biological processes in Alzheimer’s disease and other neurodegenerative diseases. We analyze large datasets collected from patients and cognitively unimpaired