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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, or a related field. Preferred Qualifications, Competencies, and Experience Coding and statistical analysis experience is preferred. Special Physical/Mental Requirements Special Instructions
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. ● Experience with human subject research. ● Facility with statistical analyses such as structural equation modeling, multilevel modeling, and longitudinal analysis ● Demonstrated ability to successfully manage a
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Access (OEA) at (631) 632-6280 or visit OEA . In accordance with the Title II Crime Awareness and Security Act a copy of our crime statistics can be viewed here . Visit our WHY WORK HERE page
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position can be filled
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to these protections at http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf The Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act, or Clery Act, mandates that all Title IV
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Statistics Act, or Clery Act, mandates that all Title IV institutions, without exception, prepare, publish and distribute an Annual Security Report. This report consists of two basic parts: disclosure
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communication and willingness to have a societal impact; an empirical research focus and knowledge of quantitative content analysis and computational methods; proven proficiency in statistical software such as
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non-social paradigms for pre specified research hypotheses. Conducting model simulations, fitting, and recovery, as well as statistical inferences on model outputs, for pre specified research hypotheses
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow