611 postdoc-parallel-computing positions at Pennsylvania State University in United States
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tutorial program policies/procedures. Attending initial and ongoing tutorial program trainings. Assessing assigned tutee(s) needs and tailoring tutorial support by providing supplemental course instructional
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and a brief letter of interest via email to: Jennifer Valcin, Ph.D. Statistician Data Learning Center Research Informatics and Publishing Penn State University Libraries jpv5319@psu.edu BACKGROUND
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), plans and implements large scale campus programs where Student Affairs plays a key role, recruits and oversees orientation leaders and the Welcome Week/Weekend program, organizes student leadership
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for the leadership, administration, and management of the Penn State Schuylkill Cooperative Education Program. This position works closely with other departments in the Career Development Center, university-wide
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critical to maintaining secure and compliant computing environments and plays a key part in supporting student success through the management of Engineering instructional computing labs—both physical and
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preparation, and team travel. The Head Coach will develop and implement a comprehensive recruiting and retention program as well as perform organizational tasks as assigned by the Director of Athletics
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travel. The Head Coach will develop and implement a comprehensive recruiting and retention program as well as perform organizational tasks as assigned by the Director of Athletics. The Head Coach will also
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education technology. The RA will have the flexibility to work on-site or remotely as needed and will gain valuable experience on an interdisciplinary project that bridges computer science and learning
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply here, apply internally through Workday. CURRENT PENN STATE STUDENT (not employed previously at the...
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, methodologies, and submission timelines to support transparency and repeatability Required Qualifications: Degree in data science, statistics, education, public policy, computer science, or a related field