86 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" uni jobs 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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candidates must submit to and successfully pass a post-offer drug screen. Skills and Knowledge: Ability to learn the construction industry and develop personal skills for dealing with the varied companies and
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. Ability to use independent judgment in completing assigned projects. Ability to analyze and solve complex problems. Ability to understand and operate computer software programs. Must have good verbal and
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Applicants:Position is eligible for hybrid work subject to University policy . Job Summary: The College IT Support Technician I provides service to faculty, staff, and students utilizing college computer systems
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keyboard skills (data entry, portable data collection devices, etc.). Ability to use various resources including computer systems/software applications. Ability to learn the mail center's software systems
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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