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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 4 hours 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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Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network. This is partly
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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using
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chemistry, ideally with experience in performing reactions in parallel, handling automated kinetic instruments, and associated analytical techniques (HPLC, GC). Knowledge of Design-of-Experiment and automated
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. We are looking for highly motivated candidates with excellent analytical and programming skills, notably in a low-level language such as C and parallelization, and a sound working knowledge in quantum
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interactions among the office team as well as with the broader campus community. Effective with time management skills, including strategies for: prioritizing tasks; coordinating multiple events in parallel; and
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 4 hours ago
program, or acceptable combination of equivalent experience - Minimum three years in a heterogeneous Windows, Mac OS, and Unix/Linux environment - Must have diverse application experience including, but not
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| Computer Science and Engineering Initiates and leads research and development in the areas of data management systems for high performance computing (HPC), parallel computing systems; collaborates with
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets