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professional to join the University’s Information Services research computing team. The Research Computing as a Service (RCaaS) Research Software Engineering (RSE) lead is responsible for the development and
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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applications for computer vision. Experience using C++ to develop and run software applications. Experience using GPU-accelerated ML and related frameworks. Experience with Docker or other containerized
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software delivered to sponsors outside of ARL:UT. Other related functions as assigned. Required Qualifications Bachelor’s degree in Computer Science, Computer Engineering, or other related discipline
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and computational resources associated with multiple research disciplines. Desirable: B1 Knowledge of scaling and optimising software to take advantage of GPU / HPC infrastructure. B2 Good
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Based within the School of Computing and Mathematical Sciences on the World Heritage site at the Old Royal Naval College, Greenwich, you will be part of the Centre for Safety, Resilience and
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, Git, Azure Data Studio, pandas, NumPy, and Scikit-learn. Experience with High-Performance Computing (HPC) platforms with advanced skills in SLURM-based multi-node, multi-GPU training, data parallelism
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artificial intelligence. You will work with a diverse group of faculty, postdocs, and students from multiple disciplines, including cognitive science, psychology, computer science, statistics and machine
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-of-the-art high-performance computing (HPC) infrastructure. In this position, you'll leverage your expertise to support and manage CSHL's AI-driven compute cluster powered by NVIDIA H100 GPUs, empowering
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the entire northern sky every day and processes over 6.4Tb/s of sky data 24/7 on a large on-site GPU cluster. CHIME is a multi-institutional collaboration with 100+ members. The Scientific Software Engineer