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Field
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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literature. Foundational Algorithms for AGI AGI will not emerge from scaling existing models alone; it requires a new algorithmic foundation for learning, reasoning, and adaptation. This research area is
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the horse racing and equestrian industries. • Track social platform updates and algorithm shifts to optimize content performance. • Manage digital assets and relationships with in-kind sponsors and brand
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machine learning algorithms for application to sonar and underwater acoustics, as well as the accompanying data analysis to effectively characterize their performance in the Advanced Technology Laboratory
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postdoctoral researcher, your responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling
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with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent
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vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been funded by numerous agencies, including the National
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms
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control systems, especially EPICS. Familiarity with synchrotron light science (e.g., ALS) preferred. Experienced in RF technology, magnetics, distributed controls, and algorithm design. Strong academic
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or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. • An excellent