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-node GPU training and inference pipelines for foundational models. You'll also develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing
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develop new features and extend the capabilities of a real-time neural data processing and decoding platform. This includes optimizing GPU-accelerated signal processing pipelines, improving system
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., Bayesian, hierarchical, time-series), experience with sensor-based data (such as eye tracking, EEG, and heart rate), and proficiency in computational workflows, including distributed and GPU-based systems
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them. Research Computing & AI Enablement - Work with the Architecture team to build scalable HPC and GPU-enabled environments on IaaS cloud sites along with other specialized hosted solutions. Work
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of the art equipment within DNA and RNA sequencing, laboratory automation, CPU and GPU compute resources, proteomics, metabolomics, and advanced microscopy. This position offers an excellent opportunity
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programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal research compliance and security requirements Background in AI/ML computing
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tuned for thermal transport and fire dynamics. FDS has been scaled up to 10,000 cores on Titan. The aim of this project is to improve code performance for serial, OpenMP, MPI, and potentially GPU
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the next generation of AI leaders, mentor students on groundbreaking research projects with access to state-of-the-art GPU hardware, forge partnerships with industry and academia, and contribute to AI
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Information Benefits Trabajo en IA generativa de vanguardia aplicada al habla / Work on cutting-edge generative AI for speech Acceso a servidores GPU y recursos de cómputo / Access to GPU servers and computing
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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