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and GPUs) or cloud. Proficiency with high performance computing and system architecture. Advanced skills and experience associated multiple of the following: artificial intelligence; method and machine
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Description Primary Duties & Responsibilities: Lead the optimization of large-scale LLMs and deep learning architectures for biomedical research. Design and deploy high-performance AI systems using GPUs and
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the optimization of large-scale LLMs and deep learning architectures for biomedical research. Design and deploy high-performance AI systems using GPUs and hardware accelerators. Interact and collaborate
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free text of both biomedical literature and electronic patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling
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(CPU/GPU), numerical modeling/Monte Carlo simulations are an asset Visualisation skills are an asset Careful way of working, checking of results Candidates can have an M.Sc. degree in STEM, or a Ph.D
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
, or intrinsically disordered proteins. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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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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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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managing and administering an NVIDIA DGX SuperPod instrument. You and another HPC administrator will partner closely with a team of data scientists from Stanford Data Science to ensure that the GPU cluster