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Postdoctoral Research Associate, Chemical & Environmental Engineering Posting Number req24856 Department Chemical & Environmental Engr Department Website Link https://chee.engineering.arizona.edu/ Location Main
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continued U.S. Department of Energy funding for our group. Department: http://www.physics.ucsb.edu/ School: https://www.ucsb.edu/ Qualifications Basic qualifications (required at time of application
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opportunity to work with the founding directors of the MADRES cohort now at the new WashU School Public Health (in St. Louis, MO) and to be a part of the School of Public Health’s development and future
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discovery from large scale amplicon sequencing data, development of qPCR primers for specific predator, pathogen, or other organismal groups, and large-scale microcosm experiments for predation of pathogens
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research with a strong emphasis on digital health, particularly the innovative application of wearable sensor data analysis and mobile health (mHealth) application development. The goal of this research is
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will perform research with a strong emphasis on digital health, particularly the innovative application of wearable sensor data analysis and mobile health (mHealth) application development. The goal
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., human, organizational, infrastructure) to conduct research and support workforce development efforts on their campuses. This collaborative research project will use mixed methods to investigate
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and
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contributes to ARAC’s scientific portfolio through independent data analysis, development of computational workflows, integration of genomic and epidemiologic datasets, and coordination of research activities
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems