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impact on business, especially those in the transition from the era of data parsimony to the new one of “big data.” OM applies topics and tools from management science, operations research, and other areas
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for large-scale data analysis, complex simulations, and the development of next-generation artificial intelligence and machine learning models. The responsibilities will include: • Developing and teaching
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Summary: The Engineering Researcher I contributes to the planning and design of engineering research and creative projects. Performs supporting research and creative activities such as data analysis
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. Understanding of scientific computing principles. Experience with data discovery, metadata documentation, data processing, geospatial analysis, and scientific research. Experience working with large satellite
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first-author papers in reputable international journals. Experience with numerical modeling and/or data analytics with big data. Expert knowledge of hydrology. Background Investigation Statement: Prior
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that all website content is up to date and accessible. The coordinator serves as the student liaison for all large-scale programs hosted by The Office for Undergraduate Research including: the Undergraduate
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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. Detailed Position Information The Department of Information Systems, Statistics, and Management Science at the Culverhouse College of Business, University of Alabama, invites applications for a tenure-track
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applications for multiple tenure-track faculty positions at all ranks for candidates with research interests across all domains relevant to computer science. Candidates with research in Quantum Information
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applications for multiple tenure-track faculty positions at all ranks for candidates with research interests across all domains relevant to computer science. Candidates with research in Quantum Information