111 parallel-computing-numerical-methods-"Multiple" Postdoctoral positions at Princeton University
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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior research scientist
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://pritykinlab.princeton.edu) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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expected to contribute to projects that aim to model the drivers and impacts of energy transitions across multiple scales. Specifically, the researcher will join a team of energy modelers at the Andlinger
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of diffusion and carbonation, early-stage rheological characteristics, life cycle analysis, and design and additive manufacturing of architected materials. Previous experience in experimental, numerical, and
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quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation
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assessment, and geospatial modeling methods and tools. Applicants should have strong, demonstrated research ability, and excellent English written and spoken communication skills. Preference will be given
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. The candidate's work may use empirical or theoretical methods to address important policy questions. The position offers an outstanding opportunity for independent research, as well as opportunities
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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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for the Postdoctoral Research Associate role . DDSS supports technical and methodological innovation in quantitative and computational social science, addressing a diverse array of new data and analytic challenges