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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 29 days ago
minimum of 3.0 FCEs of CSC courses, including at least 1.0 FCEs of systems courses. Note that CSC-like courses offered in different departments do not count towards the FCE requirement as the courses
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are essential. Multitasking, ability to work with different teams and with varied customer needs. Ability to gather data about the use of HPC systems, analyze the data and prepare reports for leadership. Ability
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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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MPI, OpenMP, CUDA or OpenACC. Familiarity with scientific software stacks or domain-specific tools (e.g., BWA, Samtools, GATK, Gromacs). Experience supporting research involving regulated data (e.g
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duties assigned to the Inpatient Pharmacy (CUDA, CIVA) Department Overview UC Davis Health is a nationally recognized leader in the provision of high-quality, patient-centered care, based in the Greater
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Actions Home Help Job Description More Actions UC Davis Health Careers Sign In New User Previous Job Job Title Pharmacy Technician 2 (CUDA EVE) Next Job Apply for Job Job ID 78096 Location Sacramento Full
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to undertake the duties associated with this level of post having acquired the necessary professional knowledge and management skills in a similar or number of different specialist roles. Or: Scottish Credit and
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at UMBC. This position will test different technologies, build modern and cutting-edge software, and ensure the reliability of the IT resources used by a large cohort of UMBC faculty and students
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to make a difference. Make something out of it! In our video you will find information about our student assistants and their work. What you bring to the table You are studying a master's degree in
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libraries like NCCL/RCCL and experience with high performance computing middleware is highly desirable. Optimizations of large parallel code bases and experience with GPU programming languages such as CUDA