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Field
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software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
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Bilingual in English and Spanish and/or Haitian Creole preferred Experience working with big data, machine learning preferred Department Specific Functions The CRANE Lab, within the University of Miami Miller
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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development, and publication in peer-reviewed venues. Strong background in machine learning, with research experience in deep learning, foundation models, or related areas. Solid programming ability in Python
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processes and particle acceleration in geospace. Research activities will integrate observational data analysis, theoretical modeling, and numerical simulations to advance our understanding of magnetospheric
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support machine learning applications for analyzing electron microscopy images of nanoalloys. Model interactions between nanoalloys and carbon substrates to reflect experimental conditions, incorporating
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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with strong expertise in machine learning for cyber-physical systems and a solid understanding of electric power distribution systems, and microgrid operations. The selected candidate will develop and
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Postdoctoral Researcher with a strong computer science background and demonstrated expertise in deep learning and generative model development to lead the AI component of this initiative. Responsibilities and
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Palmetto College campuses in Salkehatchie, Union, Lancaster and Sumter enable students to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our