482 postdoc-parallel-computing positions at University of Pennsylvania in United States
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animal handling and sample and data collection. Job Responsibilities Conduct experiments and enter findings into computer. Processing samples. Preparation and shipping. Organize data and compile
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, interpersonal, and communication skills. Knowledge of IRB and neuroimaging analysis is a plus. Working Conditions Office, Library, Computer Room; Requires extensive safety Physical Effort Typically sitting at a
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of the Softball program, specifically as it relates to skill development and strategies and the recruitment of qualified student-athletes. Pitching coach experience welcomed. This includes but is not limited
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Responsibilities Plan and execute a comprehensive, accessible, and culturally competent sexual health, gynecology and gender-affirming care program including program utilization, outcomes, and satisfaction
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responsibilities include the development and oversight of a program foscused on prospect development, data analysis. proactive prospect identification, and strategic prospect portfolio reviews for a team of
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. Serve as Remote Campus backup to DS Admin coordinator as liaison with Perelman School of Medicine Information Services LSP on all Distribution Services computing issues. Must be physically able
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audiences to support key and impactful reporting. Collaborate with academic program and departments to help support the development of clear stewardship materials that reflect unique donor expectations in
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maintaining the university’s ADIT report to ensure accurate transfer of admissions and enrollment data to Penn’s data warehouse, as well as producing ad-hoc analyses for senior leadership, program staff, and
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reporting of gifts. Produce acknowledgements to donors for Penn Medicine. Produce Notice-of-Contribution correspondence generated by donations made to the Development program. Handle the responsibilities
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, experimental psychology, and computer science preferred). Data management, cleaning, and analysis skills (understanding data structures and types, cleaning, wrangling/reshaping, merging, working with missing