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Field
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have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding of neuroimaging data to predict subjective
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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on reliability, security, and resilience of electric power systems and microgrids and stability analysis and Scientific Machine Learning (SciML) for microgrid applications. The successful candidate will be
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Experience with Knowledge Graph machine learning including KG embeddings. Strong background in data integration, ETL pipeline design, and schema transformation. Familiarity with workflow managers, with a
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control