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Field
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- Reinforcement Learning Algorithms COURSE SCHEDULE: April 1, 2026 - April 28, 2026 Number of available GSI positions: 1 position at .25 fraction, pending enrollment Number of positions reserved for PhD Students as
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Liu at UA Department of Geography and the Environment. The postdoctoral scholar will lead sediment remote sensing algorithm and foundation model development and implementation, remote sensing and field
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 2 hours ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall, the position will offer
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interests, including both scientific topics and algorithm/software development; Potential synergies with ongoing research at the University of Michigan with at least 2 professors on campus applying
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emission of a hydrogen plasma. Extend the quantum computing algorithm to a time-dependent system. Formulate the quantum scattering problem of electron impact ionization and excitation in a hydrogen and
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approach development for rescaling the temporal and spatial resolution of satellite images to be used in prediction algorithm and software development Develop Research Report, Conference Presentations
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cohorts and data generation resources through highly collaborative clinical faculty. Ideal candidates will have expertise in computational modeling, machine learning, or algorithm development, with
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research on AI/ML methods for accelerating integrated circuit (IC) design. * Participate in the deployment and testing of AI/ML-driven IC design algorithms to both open-source and industry-standard CAD tools