2,773 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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post-doctoral research associate position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse
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members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National Laboratory . Equal
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Required Knowledge, Skills, and/or Abilities Demonstrated experience in computation/computer algorithms, as evidenced by relevant publications. Desirable Knowledge, Skills, and/or Abilities Proficiency in
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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Computer Science and Electrical and Computer Engineering departments, and the School of Medicine. The group emphasizes collaborative and multidisciplinary work and brings together expertise from machine learning
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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pressing challenges. The PIIRS Postdoctoral Fellows Program is integral to that mission. We will award two postdoctoral fellowships to our 2026-27 cohort. PIIRS seeks recent PhDs in the Social Sciences who
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develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a