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at Duke University (www.venturellilab.org) is seeking highly motivated researchers or postdoctoral researchers with expertise in machine learning, deep learning, and/or nonlinear dynamical systems to join
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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Praha 120 00, Czechia [map ] Subject Areas: Statistics, data analysis, information theory, machine learning, deep learning, and data science Appl Deadline: 2026/04/16 04:59 AM (posted 2026/01/23 05:00 AM
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scoping to deployment and monitoring of production-grade models—with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 1 day ago
. Description: This project aims to develop a next-generation wildfire risk assessment platform that tightly integrates Earth Observation (EO) data, deep learning, and dynamic fire behavior modeling
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the Job related to staff position within a Research Infrastructure? No Offer Description Description The Deep Learning laboratory in the Division of Science, New York University Abu Dhabi, seeks
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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Engineering in the 2025 QS World University Rankings by Subjects. The EEE Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for cardiac ultrasound imaging