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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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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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collaborator Dr. Cynthia Gerlein-Safdi (Civil and Environmental Engineering, Berkeley) and assistance from at least one PhD student. In person work is required, but a hybrid working arrangement may be considered
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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 | 28 minutes 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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, 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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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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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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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