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Field
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simulation tasks. Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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and inference for distributed AI agents, and how the realities of networked operation shape the design of adaptive, resilient intelligence. Finally, the research will address how groups of embodied
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 6 days ago
distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that would be involved in this project
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
permeability of fluid flow through hydrate-bearing sediments, • High resolution visualizations of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | 19 minutes ago
on geomechanical stress-strain measurements, • Water conductivity and relative permeability of fluid flow through hydrate-bearing sediments, • High resolution visualizations of hydrate distributions and fluid
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communications (ISAC) in distributed multiple-input multiple output (D-MIMO) systems for resilient and efficient intelligent transport systems (ITS) and 6G-integrated non-terrestrial networks (6G-NTN)! Chalmers
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models; Learning with limited supervision; Generalisation beyond pretraining distributions The precise research agenda will be developed together with the successful candidate and may evolve throughout
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-mentor relationship Prompt disclosure to the mentor regarding the possession and desire to distribute materials, reagents, software, and copyrightable and potentially patentable discoveries derived from
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across tasks; Structured and compositional learning; Vision-language and multimodal models; Learning with limited supervision; Generalisation beyond pretraining distributions The precise research agenda