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exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website . Required Qualifications: Completed PhD in biomedical engineering, electrical engineering
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develop signal processing algorithms to characterize structural health in microreactors and other advanced nuclear reactor technologies. Metrics for success will include scientific output, disseminating
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
@jpl.nasa.gov (818) 793-4606 Questions about this opportunity? Please email npp@orau.org Qualifications The selected candidate must have a PhD degree in aerospace engineering, or related field; must have
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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project is to develop scalable and privacy-preserving Bayesian computational algorithms. The position is intended for two to three years, with an initial one-year appointment renewable contingent upon
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
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Requisition Id 15253 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune