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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 months 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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position within a Research Infrastructure? No Offer Description The position targets the design and evaluation of novel architectures, programming paradigms, and parallel algorithms for AI accelerators
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for the leadership and management of the EPSRC programme grant: Advancing Parallel Mesh Generation and Geometry Representation to Enable Industrially Relevant, High-Fidelity Simulations (REMODEL). The REMODEL project
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. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 administrative
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. The successful candidate will play a central role in SLAS’s Parallel Degree Programme (PDP) in partnership with the University of London (UoL), particularly through teaching contributions
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courses about parallel computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: • Completed doctoral/PhD studies in Computer Science
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fundamentals and hands-on experience with HPC systems; parallel/distributed programming and/or solid UNIX skills Proven experience operating Machine Learning (ML) in production. Able to design, automate, and
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, pursuing their own research project during the mobility period, parallel to joining a research group and having a host supervisor at Lund University. For information about eligibility and selection criteria
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of the provisions of the collective bargaining agreement. Here, you supervise your students in courses about parallel computing, computer architecture, programming models and high performance computing
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA