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Field
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-Resistant Organism Repository and Surveillance Network (MRSN) is a unique entity that serves as the primary surveillance organization for antibiotic-resistant bacteria across the Military Health System (MHS
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within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a
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candidate will join Associate Professor Jean Wen’s research group, conducting independent, high-impact research at the intersection of AI/machine learning, computational biology, and RNA biology. The position
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managing and curating large datasets and with machine learning techniques preferred. Excellent oral and written communication skills and the ability to perform both self-directed and guided research
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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dataset, GroupLens Research. grouplens.org [8] Statlog German Credit Data, UCI Machine Learning Repository. archive.ics.uci.edu [9] ERASER Benchmark, ERASER Project. eraserbenchmark.com [10] e-SNLI Dataset
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory
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standards and data protection regulations. This includes managing sensitive data correctly and guaranteeing that machine learning applications are developed with ethical considerations in mind. Participate in
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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig