82 machine-learning-"https:"-"https:"-"https:" positions at The University of Alabama
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Pay Grade/Pay Range: Minimum: $44,200 - Midpoint: $55,300 (Salaried E6) Department/Organization: 870601 - Veterans/Military Affairs Normal Work Schedule: Monday - Friday 8:00am to 5:00pm; some
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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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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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languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or machine learning applications. Acquisition, processing, and analysis of remote sensing imagery
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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Department Minimum Qualifications: Current CPR certification. Experience with an electronic health record system in a previous learning or employed role. Final candidates must submit to and successfully pass a
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Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job
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techniques. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Background Investigation