2,298 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral positions in United States
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 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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, gender, gender expression, gender identity, genetic information, national origin, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke
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mechanics and analysis Experience with the following: Structural health monitoring (SHM) Finite element modeling (e.g., ABAQUS, SAP2000, ANSYS) Machine learning / AI (Python, TensorFlow, PyTorch) Demonstrated
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optimization or machine learning methods relevant to materials research. 4/2/2026
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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at the University of Richmond. The postdoctoral researcher will also have the opportunity to teach up to one course per semester in the Data Science and Statistics Program and to travel to international conferences
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Prof. Youngseok Kim (Ohio State University) – Quantum Computation & Quantum Algorithms Prof. Pilkyung Moon (NYU Shanghai) – Graphene, Twistronics, Novel Topological Materials Website of our team https
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a postdoctoral scholar in computational biology. The PI, Dr. Lixing Yang is an Associate Professor at the Ben May Department for Cancer Research and the Department of Human Genetics. To learn more
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential