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process. Our lab has been conducting large scale web-based experiments using the masked priming paradigm to measure with high precision how different sources of information are taken into account in
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Description The Center for Interdisciplinary Data Science and Artificial Intelligence (CIDSAI) at NYU Abu Dhabi seeks to recruit a highly motivated researcher to work on topics in the theoretical
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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at the intersection of Genomics, Personalized Medicine, Epidemiology, and Artificial Intelligence (AI). A key initiative within the school is the Human Phenotype Project—a groundbreaking, large-scale longitudinal
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at the intersection of Genomics, Personalized Medicine, Epidemiology, and Artificial Intelligence (AI). A key initiative within the school is the Human Phenotype Project—a groundbreaking, large-scale longitudinal
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Geotechnical Engineering, Civil Engineering, or a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian
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of large-scale survey data, which are combined with administrative and experimental datasets to answer high-impact policy and academic questions. Applicants must have a Bachelor's degree in Computer
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tackle a broad spectrum of topics, including pandemic modeling and forecasting, pathogen genomics, epidemiological big-data analytics, global health informatics, and vaccine development strategies. Drawing
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Description Associate Professor - Computer and Information Engineering Job Purpose: The responsibilities of faculty members shall be an appropriate combination of the following: a) Dissemination of
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focuses on the rigorous statistical and probabilistic foundations of machine learning and data science. We emphasize computational methods for large-scale data and scalable inference techniques. Our current