103 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at University of Washington
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modeling team, the UW Salish Sea Modeling Center, NOAA Northwest Fisheries Science Center, PNNL, and CSIRO Australia. The postdoc will also interface with the Future Scenarios project at the Puget Sound
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. The successful candidate will be a member of a highly interdisciplinary team including oncologists, biologists, engineers, and imaging scientists. The candidate will develop computational models of human disease
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Position Summary This position will focus on integrating high-resolution field monitoring, remote sensing, and statistical and numerical modeling approaches to improve predictive flood hazard
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disease models, human patient samples, 3D bone marrow organoid models, single-cell RNA-Sequencing, and general molecular and cellular biology techniques. The successful candidate should have a good
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comfortable with handling experimental and transgenic mouse models. The Lim Lab fosters a culture of respect, honesty, and hard work and is committed to translating preclinical findings into clinical trials
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the University of Washington Labor Relations website https://hr.uw.edu/labor/academic-and-student-unions/uaw-postdocs/uaw-postdoc-contract We are seeking a creative, innovative, and collaborative individual
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: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life
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models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life on planetary environments
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measurement. Additional duties involve microbial population analysis (16sRNA), chemistry analysis (N, P, metals), and statistical modeling. The role also entails lab management, including cleaning and safety
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: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life