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Field
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at the Large Hadron Collider (LHC). The successful candidate will contribute to a broad research program that includes physics analysis, detector performance studies, experiment operations, and upgrade
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
. Description: Under the guidance of a mentor, the participant will engage in a NASA-aligned research project advancing data-driven approaches to characterize wildfire risk and post-fire vegetation recovery
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big data. Among the key duties of this position are the following: Participate in lab meetings, research-in-progress seminars, data analysis, and presentations at conferences. Participate in the ACTIVE
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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. Assists with the preparation and cleaning of worksite. Analyzes research data and summarizes results. Writes and may contribute to research report, papers, articles, and publications. Mentoring May assist
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of real-world evidence using large real-world data sources, including data from the ongoing prospective cohort study (DREAM cohort). The successful candidate will have expertise in epidemiologic research
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in the analysis and interpretation of single-cell multi-omic data. This role will contribute to cutting-edge research by integrating statistical and computational approaches to address complex
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evolutionarily conserved structured RNAs and candidate mammalian riboswitches from large genomics and transcriptomics datasets. The position will involve close collaboration with experimental scientists who will
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, spatial statistics, machine learning approaches, large ecological datasets Previous experience with passive acoustic monitoring and/or eBird data Familiarity with ecology and/or ornithology Demonstrated
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
for large-scale ice-sheet models such as ISSM, and provide a pathway toward increasingly integrated model–observation frameworks, including data assimilation. References: E Rignot, S Jacobs, J Mouginot, B