71 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at The University of Alabama
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: The College Experiential Learning Coordinator organizes and oversees experiential learning opportunities (co-curricular learning experiences, corporate-sponsored projects, service learning, select
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and thus are strongly encouraged to apply. Detailed Position Information The Department of Electrical and Computer Engineering (ECE: https://ece.eng.ua.edu/ ) and the College of Engineering (CoE: https
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are strongly encouraged to apply. Detailed Position Information The Department of Electrical and Computer Engineering (ECE: https://ece.eng.ua.edu/ ) and the College of Engineering (CoE: https://eng.ua.edu
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and thus are strongly encouraged to apply. Detailed Position Information The Department of Electrical and Computer Engineering (ECE: https://ece.eng.ua.edu/ ) and the College of Engineering (CoE: https
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. Detailed Position Information The Department of Electrical and Computer Engineering (ECE: https://ece.eng.ua.edu/) and the College of Engineering (CoE: https://eng.ua.edu/) at The University of Alabama (UA
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experience in at least three of the following: developing watershed model input datasets, geospatial analysis, applying large-scale hydrologic models, artificial intelligence and machine learning, computer
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of Alabama and beyond. The successful candidate will apply tools including (but not limited to) Data Acquisitions, Data Mining, Data Visualization, Machine Learning, Statistics, Optimization and Simulation in
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University and College policies. May teach compass course as needed. Additional Department Summary: Provides proactive, holistic academic advising, case management, and support for undecided freshmen in
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student. Ability to work at least 2 night shifts per week. Skills and Knowledge: Excellent verbal communication skills. Ability to learn new computer programs quickly. Ability to work independently and
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hydrodynamic modeling (e.g., SFINCS, DFLOW-FM, MIKE, ADCIRC), coastal hazard assessment, model coupling, or model calibration and validation. Experience in machine learning and statistical/probabilistic analysis