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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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opportunities for methodological and/or software development, as well as the integration of machine learning into the project, depending on the candidate’s interests. This position is one of three Postdoctoral
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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
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. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/22002423/postdoctoral-associate-x28-movshon-lab-x29 Return to Search Results
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Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 12 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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Carnegie Mellon University, Institute for Computer-Aided Reasoning in Mathematics Position ID: 3637-PF [#27988] Position Title: Position Type: Postdoctoral Position Location: Pittsburgh
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 12 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoctoral researchers