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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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/Administrative Internal Number: 6791073 Postdoctoral Research Associate About the Opportunity The Postdoctoral Research Associate advances research in mathematical modeling, optimization, and stochastic analysis
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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Monitoring Drift Chambers (MDT), and in the Event Filter track trigger (EFTracking). The group applies novel Machine Learning tools and techniques to both analyses and trigger upgrades, and leverages FPGA and
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disciplinary boundaries, notably the Co-Design Center for Quantum Advantage (C2QA) at BNL. The postdoctoral researcher is expected to conduct original research, disseminate results by writing manuscripts and
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his collaborators, Yan Li in the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project is to develop
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours 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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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 4 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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activities as part of your postdoctoral training. You do not need to be an expert in both infection biology and insect physiology from the beginning — but you must be willing and able to learn quickly within a
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should