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Humanities Scholars Program Postdoctoral Associates Call for Applications: Humanities Scholars Program Postdoctoral Associates Open to Cornell PhD Candidates and Recent Cornell PhDs Eligible
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/02/03 11:59PM ** (posted 2025/12/11, listed until 2026/02/03) Description: Apply Description Call for Applications: Humanities Scholars Program Postdoctoral Associates Open to Cornell PhD Candidates
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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including
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approaches for using machine learning to analyze X-ray data, particularly Resonant Inelastic X-ray Scattering (RIXS). The position will collaborate with experts in RIXS experiments (Mark Dean), computational
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qualifications PhD in Microbiology, Computational Biology, Genomics, Systems Biology, Statistics, Machine Learning or related discipline Publication record in Microbiology, Metagenomics, Metabolic/Statistical
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 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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trials to multi-omics explorations, imaging, biomarker development, stable-isotope tracers, and large-scale data set s and machine learning. The lab is now recruiting for a postdoctoral researcher, who
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of educational data science, AI in education, and the learning sciences, with additional advisory support from faculty and researchers across learning sciences, computer science, machine learning, and education
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning