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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 8 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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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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Internal Number: 528197 Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5
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. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Surface Structures The Data-driven Atomistic Simulation (DAS) group, led by
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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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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
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Bachelor's degree and relevant work experience. Experience Excellent organizational skills and attention to detail. Must have experience or be extremely motivated and eager to learn neuroimaging processing
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Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning