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The Princeton Institute for International and Regional Studies (PIIRS) at Princeton University is pleased to announce the call for applications to the PIIRS Postdoctoral Fellowship Program for
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
include advancing foliar trait retrieval algorithms, atmospheric correction over dense humid tropical canopies, machine learning and dimensionality reduction for handling big data, landscape evolution
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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Monday - Friday, 8 a.m. - 5 p.m. Summary A Postdoctoral Associate position is available in the Division of Vascular Surgery’s Vascular Intelligence for Translational AI & Learning (VITAL) Lab
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Informatics (HOBI) at the University of Florida (UF) is seeking a highly motivated Postdoctoral Researcher with a strong background in biomedical informatics, artificial intelligence, machine learning, or data
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Job Description Apply now Job Title: Postdoctoral Associate - Cell and Gene Therapy Division: Pediatrics Work Arrangement: Onsite only Location: Houston, TX Salary Range: $63,480 - $64,356 FLSA
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization