The Biostatistics emphasis in this interdisciplinary program is distinguished by its rigorous training and practical collaboration. In this training program, students will develop essential expertise in theory and methods in biostatistics. Students will have opportunities to not only work with Biostatistics faculty in development of statistical theory and methods, but also collaborate with health systems researchers, translational epidemiologists, and clinical and basic science investigators across the University of Utah and around the globe. We aim to train the next generation of biostatisticians with skills needed to analyze complex biomedical data in the Big Data era, and academic leaders who are committed to improving patient and population-oriented care.
The curriculum of each student will be tailored to his or her background and objectives. In addition to core statistical training in probability, statistical inference, epidemiology, statistical programming, regression modeling, survival analysis, and categorical data analysis, the PhD program particularly emphasizes the development of expertise in study design, machine learning, analysis of big data, modern causal inference, and methods for analysis of multi-level data. Students are encouraged to pursue elective courses in related areas of application including bioinformatics, health economics, public health, and computer science.
Within the required coursework, students have the opportunity to develop a highly individualized plan of study with their faculty advisor. Students may orient their thesis to either novel applications of statistical methods or to the development of new methods, while publishing their research in academic journals.
Clinical & Translational Epidemiology
Clinical and translational epidemiologists work with lab scientists to develop optimal patient treatments based on cellular and molecular research findings.
The clinical & translational epidemiology track of our innovative 4-year curriculum reflects the translational process from cells to symptoms. A strong foundation of epidemiology complemented by coursework in biostatistics and biomedical informatics will prepare graduates with a unique blend of skills positioning them for success in transforming health care delivery.
Health Systems Research
PhDs in Population Health Sciences foster data-driven health care delivery while working in academic, government, policy, research, and health system settings.
The 4-year curriculum mirrors the novel interdisciplinary nature of population health sciences.
The PhD program complements and interfaces with existing graduate programs in public health, biomedical informatics, medicine, pharmacotherapy, mathematics, economics, political science, computing, nursing, statistics, and more.