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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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About the Role We invite applications for a Postdoctoral Research Associate to contribute to the “Big Data for Cardio-Oncology” programme funded by the Wellcome Trust. The research leverages
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project. The project is part of a large collaborative research effort involving Imperial College London, University of Bristol and three other groups at Cambridge. More information about the overarching
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models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps. The project emphasizes spectroscopic galaxy surveys
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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with researchers both at Stanford and the U.S. Census Bureau. The position is open to recent graduates of PhD programs in economics, statistics, sociology or related data science fields, preferably with
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underserved populations. Research skills and experiences will include utilizing mixed methods research, community engagement, qualitative, quantitative, and big data collection and analysis. This position
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to conferences For more information concerning this position, please contact Prof. Bertinelli, email: Your profile We are looking for a candidate with a PhD in economics, preferably with a specialization in
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questions related to infrastructure and development, and a thorough knowledge of applied econometrics The candidate should show some acquaintance in managing large datasets and non-traditional data, e.g. GIS
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scientists—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative datasets to support policy