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areas: -developmental biology -experimental and/or theoretical biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant
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proposals. Responsibilities Develop, implement, and evaluate new statistical and machine learning methods aligned with the two themes above. Lead and co-author manuscripts in statistical, machine learning
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) and genetics data which are measured by longitudinally and cross-sectionally. • Developing and applying machine learning and AI approaches to identify interactive topological relationships
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 11 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs/21923150/2025-postdoctoral-research-associate-ai-machine-learning-for-analytical-and-forensic
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 11 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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, 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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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning