UTSW invites applications for a Postdoctoral Fellow in Bayesian Biostatistics. The fellow will contribute to both applied and methodological research involving Bayesian methods for multicenter clinical trials, with a particular focus on phase III studies in trauma, trauma resuscitation, and traumatic brain injury. 

This position is suited to a recent PhD graduate who is interested in developing a research program at the intersection of Bayesian methodology and collaborative clinical-trial research. The fellow will work closely with biostatisticians, clinical investigators, trial leadership, and multidisciplinary research teams involved in large, multicenter studies. 

Research activities 

The fellow’s work will include: 

• Conducting statistical analyses of multicenter clinical-trial data. 

• Developing statistical analysis plans, including specification of estimands, prior distributions, analysis populations, missing-data methods, interim analyses, and sensitivity analyses. 

• Contributing to the design, conduct, monitoring, and reporting of phase III clinical trials. 

• Developing and evaluating Bayesian methods relevant to multicenter trials. 

• Conducting simulation studies to assess type I error, power, bias, interval coverage, operating characteristics, and robustness to prior-data conflict. 

• Preparing manuscripts, abstracts, presentations, technical reports, and grant applications. 

• Collaborating with clinicians and investigators in trauma, trauma resuscitation, and traumatic brain injury research. 

Methodological projects may include, but are not limited to: 

• Bayesian borrowing of historical or external information. 

• Dynamic and robust borrowing methods. 

• Hierarchical models for multicenter studies. 

• Commensurate, mixture, power, and meta-analytic predictive priors. 

• Bayesian approaches to phase III confirmatory trials. 

• Bayesian interim monitoring and adaptive trial methods. 

• Modeling treatment-effect heterogeneity across centers or patient subgroups. 

• Methods for ordinal, longitudinal, survival, and competing-risk outcomes. 

• Sensitivity analyses for prior specification, missing data, and departures from modeling assumptions. 

The fellow will have opportunities to lead methodological and applied manuscripts, present findings at national scientific meetings, and participate in the development of grant proposals and future clinical-trial protocols. 

Required qualifications 

Applicants should have: 

• A PhD in biostatistics, statistics, or a closely related quantitative field, completed recently—typically within the past one to two years—or expected before the position start date. 

• Formal training in Bayesian statistical methods. 

• Strong programming skills in R. 

• Experience with statistical simulation and reproducible data analysis. 

• A strong foundation in statistical inference, regression modeling, and clinical-trial methodology. 

• The ability to communicate statistical concepts effectively to both quantitative and clinical collaborators. 

• Strong scientific writing and organizational skills. 

• An interest in conducting both applied and methodological research. 

Preferred qualifications 

Preferred experience includes one or more of the following: 

• Bayesian hierarchical modeling or Bayesian borrowing methods. 

• Clinical-trial design or analysis. 

• Development of statistical analysis plans. 

• Multicenter or cluster-structured data. 

• Stan, RStan, cmdstanr, JAGS, NIMBLE, or other Bayesian computing platforms. 

• Longitudinal, ordinal, time-to-event, or competing-risk methods. 

• Analysis of trauma, emergency medicine, critical care, or neurological outcomes. 

• Preparation of peer-reviewed manuscripts or collaborative grant proposals. 

Prior experience in trauma research is not required. Applicants with strong Bayesian training and an interest in clinical-trial applications are encouraged to apply.