Rice University's Department of Statistics is dedicated to the advancement of the scientific discipline of statistics, the innovative application of statistics to meet modern scientific, engineering and societal challenges, the expert education of students in statistics and other disciplines, and statistical leadership in the local, national and international communities.
Applications are currently being accepted to fill one full-time, 12-month postdoctoral fellow position at the Department of Statistics in the School of Engineering. The postdoctoral fellow will be mentored by Professor Daniel Kowal.
Research will focus on modern challenges in Bayesian inference, prediction, and decision-making. Scientific measurement systems produce data at greater volume, velocity, and variety than ever before. In such settings, Bayesian models provide a valuable tool for inference and prediction: they aggregate multiple data sources, model a variety of dependence structures concurrently, and provide posterior uncertainty quantification. However, Bayesian models are often highly complex and computationally intensive, with posterior distributions that are difficult to interpret and cumbersome for rapid prediction and decision-making.
The goal of this research is to construct, compute, and evaluate scalable and interpretable approximations to complex Bayesian models.
We are seeking candidates who have demonstrated ability to lead and/or work collaboratively in teams comprised of individuals of diverse backgrounds, skills, and perspectives. Consistent with the National Research Council's report, Convergence: Facilitating Transdisciplinary Integration of Life Sciences, Physical Sciences, Engineering, and Beyond, we are seeking candidates who have demonstrated ability to work in research groups that
Internal Number: 24204
About Rice University
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