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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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infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi-node GPU training and inference pipelines for foundational models. You'll also
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and collaborative team of computational scientists, software and AI engineers, and neuroscientists, you’ll have access to high-performance workstations, CPU/GPU clusters, and experimental systems
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-term project. We are looking for a software engineer to develop new features and extend the capabilities of a real-time neural data processing and decoding platform. This includes optimizing GPU
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roles or positions in industry. A supportive and collaborative team committed to fostering your growth as a researcher. What You’ll Do Process calcium imaging data using GPU-based software packages
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, and interacting with pilots and passengers. Operates and becomes familiar with ground support equipment, such as the aircraft tug, ground power unit (GPU), lavatory service cart, de-icing cart, forklift
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well as experience working with large biological datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive
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orchestration, and high-throughput data processing, as well as experience working with large biological datasets in GPU-based computing environments. What we provide: A competitive compensation package, with
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resources, including the Texas Advanced Computing Center (TACC) , and multiple HPCs on campus , including some GPU-heavy clusters. University of Texas at Arlington Research Institute (UTARI) Center
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for candidates with experience in ML model deployment, workflow orchestration, and high-throughput data processing, as well as experience working with large biological datasets in scalable GPU-based computing