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Field
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research in machine learning (ML) for applications in High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time
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of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of research interests
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spectrum of laboratory equipment and computational analysis, including microbial amplicon analysis. Using data to create algorithms, databases, and decision support tools including calculators and case
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algorithms with safety guarantees for connected autonomous vehicles/trucks, robotic and vehicle-grid integration systems, incorporating robust control methods and uncertainty quantification. Implement and
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emission of a hydrogen plasma. Extend the quantum computing algorithm to a time-dependent system. Formulate the quantum scattering problem of electron impact ionization and excitation in a hydrogen and
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programming, algorithm development and deep learning model implementation, and practical experience in drone and boat-based surveys are preferred. Background Investigation Statement: Prior to hiring, the final
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Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall, the position will offer
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include but are not limited to: · Computational / algorithmic genomics · Algorithms and data structures for statistical inference over biological data · High/super
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The College of Engineering and Computer Science at Texas A&M University–Corpus Christi (TAMU-CC) invites applications for a Postdoctoral Research Associate to advance the state of the art in safe, efficient
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experimental facilities. You will be responsible for developing energy-efficient, physics-aware algorithms designed for distributed learning across both high-performance and edge computing environments. You will