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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
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responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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electrical stresses. Specific goals include: - Development of a hybrid model combining degradation indicators and AI-based algorithms. - Integration of the model into an online monitoring framework
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 25 days ago
climate system and the effect of ice-atmosphere feedbacks (e.g., ice albedo feedback and cloud feedback) on sea ice evolution. Developing radiative transfer algorithms to improve both the physical
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develop research projects for the Internet of Things for Precision Agriculture (IoT4AG) research grant Develop novel semantic mapping algorithms in the field of agricultural and forestry robotics to promote
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situation in which a customer or colleague was upset and the steps you took to resolve the issue to a reasonable conclusion. Describe your key impressions of the CVC presentation found here: http
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via bitbucket). Backup code on bitbucket and oversee the revision of the code to integrate with other algorithms. Algorithm development initially will involve solving problems such as: (1) base calling
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design
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multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid approaches for next-generation fluid simulations. Who we