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Offer Description Mission: Collaborate in the development of strategies for predicting and monitoring railway-induced vibrations. Functions to be developed: Develop prediction models for vibrations
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network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 month ago
system. Climate models are important tools for improving our understanding and prediction of atmosphere, ocean, and climate behavior. We seek candidates with an interest in advancement of radiative
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impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient
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network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
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Optimization (AI/ML) Developing AI/ML models to predict drillability issues based on mechanical rock properties Real-time parameter optimization (WOB, RPM, flow rate, etc.) using machine learning techniques
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fundamental and applied challenges in how unsteady flows generate sound and how that sound can be predicted or reduced. For more information please visit - https://www.unsw.edu.au/research/flownoise Skills
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neuroscience • Psychological and brain sciences • Medical • Biomedical • Nanofluidics and microfluidics • Biomimetics and biofilms • Social media analysis and predictive modeling • Molecular, cellular
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of Molecular Medicine and Therapeutics at The Ohio State University College of Medicine. Lab website: http://u.osu.edu/mathur Our goal is to use the lens of metabolism to better understand and predict cancer