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assistant professor commencing Fall 2025 to support the growth and development of our cybersecurity programs. We will consider candidates from any area of cybersecurity, with an earned PhD in Computer Science
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extramural competitive grants. These are non-tenure track research appointments housed within IWRRI with no formal teaching responsibilities. Position Overview Serves as an independent researcher, or a
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studies, science methods or literacy, educational foundations, or Indigenous theories of learning, and graduate classes in Indigenous research methods. The ideal candidate will establish a focused line of
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execution, deployment and post-launch support. This position will be instrumental in managing a pipeline of competing project ideas by applying a formal prioritization framework to help leadership make
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, peer-reviewed Extension bulletins, popular press articles, digital information products and other methods as appropriate. The educational programs will be accessible to students (including those enrolled
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: Planning and conducting research in accordance with stipulated protocols and quality and safety standards Performing complex scientific analyses Developing new methods and guidelines for procedures Directing
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at time of hire. Required Qualifications PhD in psychology or related discipline Have been awarded funding from National Institutes of Health Experience conducting externally funded research Experience
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. Preferred Qualifications PhD, DBA or other terminal degree in a business-related field. Experience developing a variety of teaching methods including face-to-face and online. Experience teaching in a variety
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, educational technology or closely related field Required Education Master’s degree Required Other Additional Preferred EDUCATION AND WORK EXPERIENCE: PhD and at least one year of experience working with faculty
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working on forage quality analysis using NIRS or wet chemistry methods Experience of using soil and water sensors and handling big data Experience with field research, experimental design, data collection