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into their models; or 2.Computational social scientists with experience in empirical research and/or theoretical modeling, who are motivated to incorporate their methods into energy modeling. All applicants must
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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% – Research Lead development of computational models of judgment and decision making, including evidence accumulation models, social drift-diffusion models, and hybrid models integrating computer-vision–derived
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to transform the way environmental and social data are integrated into fisheries management by combining advanced ocean forecasting, species-specific modeling, and social science to develop adaptive strategies
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Description: Apply Position Description Postdoctoral Research Associate in Transportation Systems Modeling & Urban Mobility Analytics Cornell University’s Center for Transportation, Environment, and Community
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Job Id: 11788 Limited to 3 years | Full-time with 38.5 hours/week | Salary according to TV-L E13 | Clinical Epidemiology Unit at the Institute for Epidemiology and Social Medicine We are UKM. We
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on the development of mathematical and computational models of biological systems. This position is supported by an NIH Virtual Consortium for Translational/Transdisciplinary Environmental Research (ViCTER) grant, “In
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modelling in transdisciplinary processes in order to examine ecological and socio-spatial change, existing biodiversity governance regimes and develop multispecies ethnographies to better understand
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into the research team, engage socially with other members, share ideas, and mentor junior researchers or students. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7006-JOHSCH-009/Default.aspx
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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research