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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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implementing novel and innovative tools, technologies and approaches to fundamental problems in systems and circuit-level neuroscience. For more information about the lab check out: https
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https
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information about the lab check out: https://www.moorelabstanford.com/ . About the role: The role will be in-person with hybrid flexibility and is a perfect opportunity for someone looking for a 1-year, fixed
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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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: Project Scientist Salary range: The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following table for the current salary scale for this position: https
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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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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
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, proteins, chemical structures, geospatial, oceanographic, or heath record data. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Familiarity with RESTful web