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intelligence (AI). The successful candidate will join Prof. Francesco Restuccia’s research team (website: https://mentis.info) in Boston, Massachusetts, and work on cutting-edge topics in resilient AI, including
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such as SEM and TEM to characterize oxide particle size and distribution. Collaborate on research papers that are led by PhD GRA who is also working on project. Required Education: PhD in Welding
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for large-scale and distributed systems. The role focuses on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 44 minutes ago
distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that would be involved in this project
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volumes in frozen cell sections, providing unprecedented maps of the distributions of small molecules within the cell. Determining the spatial distribution of small molecules within cells is crucial
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WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Assists with grant preparation and
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instrument will have many applications; notably, it will allow the spectroscopic characterization of nanoscale volumes in frozen cell sections, providing unprecedented maps of the distributions of small
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discrimination, the economics of labor supply and retirement, education, income distribution, wage and employment determination, labor turnover and job duration, and labor unions. Research Associates will work
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 hour ago
representation and speed of computation for GISS climate model, particularly the treatment of cloud inhomogeneity in GCM grid scale (~200 Km) and the improvement of K-distribution parameterization for gaseous