899 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" positions at Pennsylvania State University
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., creating materials and delivering workshops and activities) Recruiting and training undergraduate research assistants The Human Research Technologist will also be allotted time for professional development
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will assist in developing large language model (LLM) applications for social science research and data analysis. Preferred qualifications include: Prior experience developing LLM applications (e.g
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Prepares reports, drafts manuscripts, and may present data at meetings and conferences Train users in equipment operation and research techniques, explain and demonstrate technology and equipment
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supports students to design plans that incorporate academic, career, and personal goals while meeting the standards of the undergraduate degree and providing a framework upon which students can develop
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the University’s mission. Positions in this job profile require a strong understanding of accounting principles, financial modeling, and business operations. Prepare and manage organizational budgets, including
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application of policies and procedures. The supervisor will work with management to develop and implement eTesting and Scanning procedures. The supervisor will create and maintain the eTesting request process
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The LionPATH Development and Maintenance Organization (LDMO), a unit of Penn State Information Technology, is looking for a highly motivated, knowledgeable, and proactive individual to fulfill the role
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of the University, which include all industrial control systems. Key Responsibilities: Developing control systems and strategies for industrial applications. Performing system and network calculations to ensure
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for experiments Collect, process, and analyze behavioral, fMRI/fNIRS, and EEG data Track project goals and budgets; purchase necessary study supplies Oversee, train, and assign tasks to student and volunteer
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: Collaborate with NCEMS Working Groups to design, develop, and evaluate machine learning approaches for integrating, analyzing, and visualizing molecular and cellular biology data across the central dogma and