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the statistical analysis of data. They will be supported by a multidisciplinary internationally renowned team with diverse expertise including in health data science, epidemiology, risk prediction, AI and clinical
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& Post-doctoral Fellow Post-doctoral Fellow in the Department of Statistics and Actuarial Science, School of Computing and Data Science (Ref.: 533742) Applications are invited for appointment as Post
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of Statistics and Actuarial Science, School of Computing and Data Science (Ref.: 533742) Applications are invited for appointment as Post-doctoral Fellow in the Department of Statistics and Actuarial Science
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probabilistic and physically informed approaches for seismic hazard assessment. The successful candidate will contribute to the next generation of seismicity and hazard models that integrate statistical and
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from all backgrounds to join our community. The Department of Information and Communications Engineering is now inviting applications for a Postdoctoral or Doctoral Researcher in statistical signal
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generation of seismicity and hazard models that integrate statistical and physics-based representations of earthquake occurrence. These models will account for spatio-temporal variability in seismicity rates
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Doctoral Researcher in statistical signal processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from
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hold, or be close to completion of, a relevant PhD/DPhil in one of the following subjects: computational genomics, genetic or molecular epidemiology, medical statistics or statistical genetics. You must
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, you will collaborate with both clinical and preclinical researchers as well as experts from other research fields. You will have a central role in the project and work independently with: Statistical
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
involves processing and harmonizing high-resolution NASA EO data. Subsequently, we will architect and train an ensemble of deep learning and statistical models capable of identifying key wildfire drivers and