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Field
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models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing new models of brain circuits and function; and learning software engineering
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and a new GPU cluster. Opportunities for professional growth and career advancement. Collaborative and inclusive work environment that fosters creativity and innovation. Application of Domain Expertise
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suite of software, and its deployment on the university HPC & GPU based system. The position is primarily research and enterprise, but there would be a contribution of up to 20% to teaching, including
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patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling for ML / LLM algorithms working over free-text clinical
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with high-performance computing capabilities (including approximately 4,000 Nvidia RTX 4000 Ada GPUs and over 30,000 CPU cores) hosted at the project data center in Nevada where the telescope is located
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management application GPU & specialized hardware for Artificial Intelligence and Deep Learning Server-class hardware and remote management The HPC administrators are responsible for working closely with
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, computational algebra, logic and programming languages. The department is housed in the newly constructed Science & Innovation Center which boasts Data Center with High Performance GPU Cluster and state
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of research computing at LSE. Your expertise will be key in future-proofing our research hardware environment, ensuring high availability, scalability and security across HPC clusters; GPU acceleration, high
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in chemistry, physics, or related field. At least 2 years of experience developing quantum Monte Carlo algorithms. Strong problem-solving and analytical skills. Python programming experience. GPU
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systems and GPU-accelerated processing. Proficient in computing languages for software/hardware integration, data analysis, networking; specifically, Python and C/C++. Proficient with Linux computer systems