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conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve
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conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve
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: Machine Learning for Greek Philology. The Logion project aims to develop machine learning methods to identify and correct cases of ‘textual corruption’, i.e. cases in which ancient and medieval scribes
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vision image stitching and alignment software based on classical computer vision and deep learning automated error detection and correction of EM image segmentations by artificial intelligence registration
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machine learning in the research group of Laure Resplandy. Duties will include ocean model code development and maintenance (MOM6, GitHub), model configuration/simulation development and running, model data
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, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), bioinformatics, molecular dynamics simulations, and related areas at the interface of computer/data science
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To develop computer modules for RF physics group. A proud U.S. Department of Energy National Laboratory managed by Princeton University, Princeton Plasma Physics Laboratory (PPPL) is a longstanding
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their fields of scholarship using techniques from machine learning and statistics. Applicants may also make research advances in the machine learning and statistical methods themselves, as necessary
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Description: Through The center for Statistics and Machine Learning at Princeton University, Princeton Language and Intelligence Initiative is now accepting applications for Research Scientist. This Initiative
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Professor level with a target starting date September 1, 2024. The search is across the broad areas of Optimization, Statistics, and Machine Learning and their applications to engineering fields. The ORFE