The University of Colorado Anschutz Medical Campus is seeking a postdoctoral fellow in causal inference, supervised by Professor Debashis Ghosh (Department of Biostatistics and Informatics, Grohne-Stepp Endowed Chair) and Dr. Sridharan Raghavan (General Internal Medicine, School of Medicine). The position is funded by an NIH R01 grant from NIDDK and focuses on comparative treatment effects and risk prediction models across diverse populations. The research will involve advanced methods in causal inference, biostatistics, and data science, with applications in medical statistics and cancer research. The postdoctoral fellow will have opportunities to collaborate with the FIORD (Forum on the Integration of Observational and Randomized Data) Initiative and the Center for Targeted Machine Learning and Causal Inference (CTML) at UC-Berkeley. The role is designed to support the fellow's long-term career goals and may include mentoring junior trainees, managing working groups, and participating in classroom teaching as opportunities arise. Applicants should have a PhD in biostatistics, statistics, epidemiology, or a related quantitative field. Experience with causal inference, risk prediction, or comparative effectiveness research is highly desirable. Strong programming skills and a collaborative approach to research are preferred. The position is fully funded, with salary and benefits provided according to NIH postdoctoral stipend levels. Sample publications from the group include research on transportability analysis, risk prediction, and comparative effectiveness in medical settings. The research environment is highly interdisciplinary, with strong connections to public health, medical science, and advanced statistical methods. To apply, visit the University of Colorado job portal using the provided link. Prepare your CV and cover letter, and highlight your experience in causal inference and biostatistics. For more information, you may contact the supervisors or review the group’s recent publications.