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Field
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proficient in working with large data-sets (observational or numerical), machine learning, and running/analyzing numerical simulations. The initial appointment will be for two years at Rutgers University
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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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/or networked microgrids. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr. Peng Zhang in the Department of Electrical and Computer Engineering . The
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access
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assembly and annotation Experience working on computer clusters and handling large datasets Laboratory skills including DNA/RNA extraction and library preparation Demonstrated advanced bioinformatics skills
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of Engineering as well as the new Virginia Tech Institute for Advanced Computing (IAC) located in the Greater Washington, D.C. area. The position involves conducting research in signal processing, machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
the group of Dr. Tengfei Li at the University of North Carolina at Chapel Hill. The successful candidate will develop and apply advanced statistical and machine learning methods for infant cognitive