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University of California Davis Health System | Sacramento, California | United States | 3 months ago
Number: 6235151 Pharmacy Technician 2 (CUDA EVE) Job Summary #CA-DS The Technician staff are responsible for drug storage, preparation and distribution of medications throughout UCDMC under the supervision
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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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, OpenFOAM), and plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 9 days ago
distributed computing setups, and the CUDA framework. Must have demonstrated expertise in marking parallel programs in various frameworks taught in the course, holding office hours, responding to emails, and
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 17 hours ago
% vacation pay Minimum qualifications: Familiarity with scalable technologies such as Apache Spark, Amazon Lambda, Cassandra, MongoDB, Redis, CUDA, Parallel Algorithms, Docker, Kubernetes, Squid. Familiarity
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with job schedulers, e.g. SLURM, PBS, SGE, etc. ● Experience working at an academic institution ● Experience with parallel codes and libraries (e.g. MPI, OpenMP, Cuda) ● Experience with research and/or
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rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to
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Programming: Python, CUDA, Git
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efficiency for serving massive models. Research and implement cutting-edge optimization strategies at the kernel level (e.g., FlashAttention, custom CUDA/ROCm kernels). Build robust data pipelines
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, CUDA) and good understanding of hardware used in large scale HPC clusters such as hybrid CPU+GPU systems, memory hierarchies and file systems; experience with job schedulers (e.g., Slurm, FLUX) and