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Field
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of neuroimaging data to predict subjective experiences and individual differences, as well as cognitive modeling of decision-making in both lab and realworld settings. Successful candidates will be supported in
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in the Unit, including i) using AI to strengthen epidemic preparedness, ii) the development of models evaluating how the combination of different surveillance systems (e.g. syndromic and virologic
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in different brain models (tree shrew, macaque, human neurotypical, schizophrenia patients) and levels of analyses (local- and large-scale circuits). This is a unique opportunity to learn about team
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scholars and researchers from around the world are tackling global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham
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Hub. Accountabilities Cleaning, manipulating, and analysing longitudinal quantitative data from various datasets, including survey, accelerometer and GPS, and EMA data from different project sites
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under different climatic and social contexts to provide decision-making tools for sustainable urban planning. Main Tasks and Responsibilities: Develop a predictive model integrating the direct and
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-related issues. Demonstrated training or experience with using econometric methods (e.g., differences-in-difference, regression discontinuity, instrumental variables, fixed effects for panel data, matching
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duties will be the following: Manipulate and culture different types of primary and stem cells (including induced pluripotent stem cells) and tissue constructs, particularly at the genetic level, and
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, including music generation, production, and analysis. The candidate will join a highly dynamic team of researchers that spans across different departments at Duke University and other research universities
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care have been part of the journey to place this technology on the market. Different grants have been awarded to the project, including the prestigious Biomedical Catalyst from Innovate UK. The later is