795 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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University of Savoie Mont Blanc (USMB) that brings together expertise in machine learning and information fusion, as well as networks and systems. It develops methods for processing and managing data in
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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to collaborate and learn from experts researching, developing, and testing emerging technologies in marine energy and/or blue economy. You will conduct research at both your academic institution and at an external
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. For more information about AMBER, visit: https
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
Engineering stresses the application of science and engineering, mathematical analysis, and computer techniques to biomedical problems. The research and entrepreneurship of the faculty, students, and staff aim
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Dallas employees have access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https
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at the Lewis-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some