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Field
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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advancement. The ideal candidate will have a PhD in computer science or related field utilizing computer science methods, strong expertise in medical image processing, registration and analysis and a long-term
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defending the cultural value of knowledge for its own sake. You will also possess computational expertise in data mining and / or analysis, ideally including language processing, and be able to work with an
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the context of rapidly evolving anthropogenic aerosol emissions. Responsibilities Conduct scientific analysis to establish and explain the response of multivariate hydroclimate extremes to near-term evolution
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collected from naturally infected animals. Most of the effort will be spent on cell cultures, molecular tests, animal studies, and associated data collection and analysis. Start date is negotiable. The
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, development, and execution of computer simulations of system related to different replication stages of the HIV virus. Preference will be given to applications with expertise in 1) protein dynamics; 2
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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data collection and scenario design. Techno-Economic & Environmental Analysis Compare material intralogistics handling alternatives (IPCC, trolley assist, battery trucks, etc.) via life-cycle cost and
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Spaces Sciences at the University of Washington seeks a Postdoctoral Scholar to work on numerical simulations and data analysis to inform the search for life on exoplanets. The position will be supervised