117 algorithm-development-"Multiple"-"Prof"-"UNIS" positions at Princeton University in United States
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necessary. Applicants who are interested in DA research and development should have a strong background in using DA systems (such as GSI or JEDI) and a strong understanding of the data sets and algorithms
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on social vulnerability to hazards. The researcher will have the opportunity to work on multiple projects, investigating (a) cumulative environmental impacts, (b) the use of census microdata for social
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scientists to join the NOAA Research Global-Nest Initiative. This multi-laboratory project aims to develop ultra-high resolution atmospheric prediction models for better prediction, understanding, and
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior research scientist to develop hybrid models for sea ice that combine coupled climate models and machine
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experimental research related to multiple ongoing projects, including optical diagnostic design and high-temperature ammonia oxidation chemistry with applications to green manufacturing and recycling of steel
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background in human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use
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: 272540364 Position: Postdoctoral Research Associate Description: The condensed matter spectroscopy group at Princeton University invites applications for multiple Postdoctoral Research or more senior
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. The successful candidate will be expected to assist with the commissioning of a new shock tube facility and will conduct fundamental experimental research related to multiple ongoing projects, including
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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of decarbonization and renewable energy expansion in the U.S. The researcher will work with a group of interdisciplinary scholars across multiple institutions that includes Elke Weber and Chris Greig at Princeton