208 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at Broward College
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semester hours in Political Science. • Ph.D. preferred. Minimum Experience/Training: • Prior college teaching experience is preferred. • The successful candidate must have a high level of computer literacy
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hours in History is required. • PhD preferred. Minimum Experience/Training: • Prior college teaching experience is preferred. • The successful candidate must have a high level of computer literacy and a
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graduate credit hours in Mass Communication, Strategic Communication, or New Media Communication. Minimum Experience/Training: Experience in evidence-based teaching, active learning, problem based learning
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” section of the application** Please refer to the link with the instructions on how to submit an application with multiple documents. https://www.broward.edu/jobs/_docs
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candidate must have a high level of computer literacy and a commitment to teaching. The successful candidate must be willing and able to teach in both the traditional face-to-face and blended (hybrid) format
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Nuclear Medicine Technology AND Certification and registration in Nuclear Medicine Technology (NMTCB or ARRT) AND Experience to teach assigned courses Minimum Experience: Prior college teaching experience
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of fostering student success, academic achievement, and persistence; (3) technological competence; and (4) the ability to use skills and strategies that engage students in ways that facilitate learning and
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persistence; (3) technological competence; and (4) the ability to use skills and strategies that engage students in ways that facilitate learning and prepare students for productive lives. Employ teaching
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evaluation, orientation, assessment of learning, facilitating student engagement in academic and career planning activities, student success skills, college policies and procedures, and student co- and extra
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underprepared students achieve academic success. The successful candidate will be expected to learn to use and maintain the use of computer assisted referral software in identifying students at academic risk and