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principles and analytic methods relevant in health services research Advanced knowledge of statistical computing and/or Bayesian inference Advanced programming skills in a common statistical software package
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Tenure-Track Biostatistics Faculty - (25002815) Description EPIDEMIOLOGY AND BIOSTATISTICS Tenure-Track Biostatistics Faculty We invite applications for tenure-track faculty in biostatistics to join
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). -Interest in Bayesian inference. - Knowledge of non-Gaussian models (heavy-tailed, impulsive) is an asset. Additional Information Work Location(s) Number of offers available1Company/InstituteUniversité
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
of Biostatistics. Specifically, the position works on and provides oversight to several federal and industry research and training grants in the areas of casual inference, Bayesian methods, robust methods, frailty
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
of Biostatistics. Specifically, the position works on and provides oversight to several federal and industry research and training grants in the areas of casual inference, Bayesian methods, robust methods, frailty
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. The ideal candidate will enhance our biostatistical core and complement or deepen our current department strengths, including, but not limited to: Bayesian methods, big data, causal inference, clinical trials
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. The ideal candidate will enhance our biostatistical core and complement or deepen our current department strengths, including, but not limited to: Bayesian methods, big data, causal inference, clinical trials
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or deepen our current department strengths, including, but not limited to: Bayesian methods, big data, causal inference, clinical trials, machine learning, mobile health data, real world evidence, survival
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or deepen our current department strengths, including, but not limited to: Bayesian methods, big data, causal inference, clinical trials, machine learning, mobile health data, real world evidence, survival
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or deepen our current department strengths, including, but not limited to: Bayesian methods, big data, causal inference, clinical trials, machine learning, mobile health data, real world evidence, survival