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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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community visit: https://greateriowacity.com/build/area-advantages/ The position will begin in Fall 2026, with flexibility in start date based on candidate availability. The initial appointment is for 1 year
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
-driven decision-making Experience leveraging analytics, predictive modeling, and technology to optimize recruitment The ability to build sustainable systems and processes that adapt to the evolving higher
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research program focused on advanced neuroimaging and computational modeling in collaboration with Pediatric Neurosurgery and the Adult Cerebrovascular Division. This faculty member will develop a
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or willingness to develop skills in analytical techniques such as GC–MS or related methods for quantifying seed-applied compounds Experience with statistical modeling, experimental design, and multivariate
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-applied compounds • Experience with statistical modeling, experimental design, and multivariate analysis of biological datasets using R, Python, SAS, or related platforms • Ability to integrate laboratory
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of CRM platforms (such as Slate), application processing software (LSAC Unite), reporting tools and dashboards, and familiarity with predictive modeling for yield forecasting and financial aid decisions
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of CRM platforms (such as Slate), application processing software (LSAC Unite), reporting tools and dashboards, and familiarity with predictive modeling for yield forecasting and financial aid decisions
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account, which may be accessed here: http://workday.cornell.edu/ Apply By All applications must be received online by 11:59 pm on 6/18/2026. Position closing dates may change based on Association needs
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experimental design, biometry, and statistical analysis of multi-environment trials, such as alpha-lattice and augmented designs, mixed-model and BLUP analyses, and genotype-by-environment interaction modeling