37 data-science "https:" "https:" "https:" research jobs at Pennsylvania State University
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Technology, Human-Computer Interaction, or a closely related field Demonstrated experience conducting empirical research in educational or community settings Strong writing, collaboration, and project
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, wiring, and troubleshooting Programming and data analysis (Python, MATLAB, or similar) Concrete structures, construction, or field testing Engineering drawings and technical documentation Learning
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Qualifications: Experience analyzing oral microbiome datasets (16S, shotgun metagenomics, or metatranscriptomics). Advanced programming and data science skills in R, Python, or other relevant languages
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) Slavkovic. Potential research projects include (but are not limited to) work on various statistical aspects of data privacy methodology, including validity of inference, measurement error, nonparametric
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- Requirements include a Ph.D. in Electrical and Computer Engineering, Computer Science or other relevant fields by the start date. Prior background in machine learning, digital twins and electronic design
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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, and New York City. Please see https://www.statecollegepa.us/ for more information. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s
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. For more information about CGNE, please visit https://www.nursing.psu.edu/cgne/. At this website, you will find information about our vision, mission, and faculty, as well as links to our annual report
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SPECIFICS Penn State's interdisciplinary Center for Theory of Emergent Quantum Matter (C-TEQ), within the Institute for Computational and Data Sciences (ICDS) Quantum Hub, invites applications for several "C
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dwarfs and/or the high-precision RV survey of solar-type stars being conducted with the NEID instrument on the WIYN 3.5m telescope; (2) improving technology, algorithms, and data analysis to mitigate