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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Proposed Start Date Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching, research and public service, the University
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of the following: (i) cross-national survey methodology, (ii) web surveys, and/or (iii) non-probability sampling methods Broad research interests related to family, social stratification, and comparative research
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employment. Individuals with expertise in relevant modeling methods are encouraged to apply, including but not limited to integrated assessment modeling, energy systems modeling, supply chain modeling, etc
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projects. Duties may include, but are not limited to: organize and implement research plans develop methods or research that incorporate highly specialized training in a specific specialty conduct tests
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://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf ]. A reasonable estimate for this position is $69,073- $82,836. Application Window Open date: October 31, 2025 Next
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non
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for the salary range for this position. A reasonable estimate for this position is $69,073 - $82,836. Percent time: 100% Anticipated start: January 1, 2026 Position duration: 2 year position Application
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field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
. At the microscale, grain interactions—governed by nonsmooth phenomena, e.g. contacts, friction—drive the bulk dynamics at the macroscale, which challenge current modelling frameworks. Modern experimental methods
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in