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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 (EVE CUDA) Next Job Apply for Job Job ID 81379 Location Sacramento Full
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level languages such as Matlab/Simulink, Python or similar 3. Demonstrated, successful experience (academic or professional) with parallel programming using languages such as OpenCL and/or CUDA 4
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potential use of Rust, CUDA, C/C++, Bash/Zsh, and Haskell while collaborating closely with students, professionals, and external partners. The role offers significant opportunities to contribute to system
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Language Model (LLM) GPU cluster to ensure stable and reliable operation of training tasks; (b) handle GPU node failures, IB network anomalies, CUDA/NCCL errors and Kubernetes scheduling failures, perform
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CUDA and scientific data libraries (e.g., Zarr) Workload: Approximately 15 hours per week on average during the semester, with the possibility of increased working hours (up to 40 hours/week) during
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the codebase by triaging and resolving GitHub issues, reviewing contributions, and addressing bugs that arise as the platform is used in active research settings. The platform is built in C++ with CUDA-based
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++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA, OpenCL, or equivalent). Familiarity with
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, scheduling policies and container runtime environment setup (Docker/Containerd); (c) build the software stack for the NVIDIA cluster, including CUDA, NVIDIA drivers, Fabric Manager, PyTorch Distributed and
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, resource requests, and environment management. Desired Requirements: 1. Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein integration. 2. GPU experience: PyTorch/CUDA for segmentation/model
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Proven experience with multiple parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA (Compute Unified Device Architecture) Experience in a batch HPC environment with a