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who are empowered to halt the climate crisis and create an environmentally sound future for generations to come. To learn more about SEAS and our values, please visit our website at https
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
diverse social, cultural, recreation and professional opportunities that span the campus and community. Please see the following links https://www.pml.unc.edu/ and https://www.pml.unc.edu/openings Primary
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Carolina at Chapel Hill More Jobs from This Employer https://main.hercjobs.org/jobs/22061395/postdoctoral-research-associate-corporate-climate-action-and-social-tipping-points Return to Search Results
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qualitative methods (interviewing, observing, coding Demonstrated skill with organization and program/project management and oversight Department Unit/Website: School of Education website: https
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their relevance to tutoring data infrastructure and student outcomes. Please articulate your expected alignment with the research themes and goals of the NTO. To apply: https://academicjobsonline.org/ajo/jobs
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experience. This is an exempt-level, benefited position. Learn more about UVA Benefits - http://hr.virginia.edu/benefits . To learn more about UVA and in the Charlottesville area, visit UVA Life and Embark
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letter and research statement should highlight the candidate’s most significant work related to the mission of the National Tutoring Observatory (NTO), https://nationaltutoringobservatory.org/ . We also
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responsibilities but will have the opportunity to interact with and mentor graduate and undergraduate students. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/31747
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. Develop and document analytical tools and quantitative metrics for comparing real and synthetic PNT data. Construct network-based representations of time series data to analyze structural and temporal
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving