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Description The Teamcore Group (https://teamcore.seas.harvard.edu) at the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University seeks postdoctoral fellows to work on AI
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 hour ago
missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations
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learning, uncovering the modes of learning available to linear and nonlinear systems, their expressiveness and capacity, and the physical imprints of learned tasks. The postdoctoral researcher will
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Posting Details Position Details Title Postdoctoral Fellow in Biostatistics and Health Data Science Specific Title Appointment Type Postdoctoral Fellow Department IUSM - Biostatistics Campus IU
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. The successful candidate will engage in innovative research addressing statistical methodology, machine learning, and/or learning techniques in complex biomedical and health-related challenges. We particularly
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We are seeking to appoint a Postdoctoral Research Scientist in Statistics to join Professor Xin Lu’s group, with an affiliation with OPIG. The Lu Group (https://www.ludwig.ox.ac.uk/research/xin-lu
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital