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Nutrition at Steinhardt is seeking a Postdoctoral Associate to support Dr. Andrea Glenn's research program in nutrition and cardiometabolic health. This position will provide comprehensive involvement in two
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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, Environmental Science, Remote Sensing, or related field Experience in atmospheric modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record Where to apply
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, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models. The postdoctoral researcher will be responsible for: Developing a
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well as how students from backgrounds traditionally considered "outside" the academy experience and engage in STEM learning and career training. The postdoctoral associate will contribute to existing projects
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/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to locomotion and manipulation; path
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“Quantifying Efficacy and risks of solar radiation management (SRM) approaches using natural analogues”. The project will use novel machine learning-based methods to determine the climate response to a range of
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Learning Sciences, Computer Science, Human-Computer Interaction, Informatics, Educational Measurement and Statistics, Educational Psychology, or a related field. Required Qualifications: Relevant experience
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machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes thus