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Field
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). The successful candidate will contribute to the modeling, simulation, and co-design of next-generation Quantum-HPC (QHPC) architectures, with particular emphasis on integration of quantum and HPC distributed
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developing algorithms for robot navigation, path and trajectory planning, resource allocation, coordination, or distributed decision-making. Knowledge of wireless communication systems, communication-aware
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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to influence community-wide best practices for data handling at large-scale research facilities. Activities include benchmarking and validating compression algorithms, developing software tools and workflows
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) until 31 March 2027 (with the possibility of an extension). The appointed candidate will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimisation
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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to architectures, algorithms, and applications. Titled "Exploring Atomic Ensemble Qubits for Distributed Quantum Computing," this LBNL-funded initiative brings together experts from the ESnet, NERSC, and AMCR
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study at the forefront of chronic pain epidemiology, helping to validate an algorithm for identifying neuropathic pain using linked healthcare data. Your work will generate evidence on prescribing
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: developing precise parton shower algorithms and studying their consequences in jet physics. - Develop a parton shower algorithm that is precise to the next-to-single log for ee collisions. - Extend
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postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and