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affiliated with Columbia University. Duties and Responsibilities: Construct air pollution and meteorological data prediction models using machine-learning based methods Conduct epidemiologic analyses studying
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collapse — working with Earth observation data and CMIP6 climate model output to develop and test statistical and machine-learning approaches for detecting precursors of abrupt change in these systems
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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projects spanning data visualization, human-computer interaction, and human-centered AI. Coordinate scientific project activities, including planning, reporting, and coordination across collaborating
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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strong background in relevant areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by