Doctor of Philosophy (Ph.D.) in Statistical Science

Statistical Science at Duke is the world's leading graduate research and educational environment for Bayesian statistics, emphasizing the major themes of 21st century statistical science: foundational concepts of statistics, theory and methods of complex stochastic modeling, interdisciplinary applications of statistics, computational statistics, big data analytics, and machine learning. Life as a PhD student in Statistical Science at Duke involves immersion in a broad range of research experiences and emphasizes conceptual innovation, as well as building a deep and broad foundation in theory and methods. Working with world leaders in research, PhD students customize their studies to define "individualized PhD programs." We stress the flexibility to tailor course selection, independent study, research experiences, and internships and so forth to help each student define a core base of expertise and move at her/his own pace towards PhD research. Coupled with our core emphases in modeling, computation and the methodologies of modern statistical science is a huge range of interdisciplinary areas via relationships with many other disciplines (biomedical sciences, environmental sciences, genomics, computer science, engineering, finance, social sciences, and others). These rich opportunities for students in interdisciplinary statistical research are complemented by our collaborations with the National Institute of Statistical Sciences (NISS) and the Statistical and Applied Mathematical Sciences Institute (SAMSI), and internships at companies such as Google, Yahoo, AT&T, IBM, RAND, Microsoft, multiple financial and biomedical companies, among others. Life as a graduate student in Statistical Science at Duke is fun and challenging; perhaps most challenging is the need to select a few specific areas of thesis research from the delightfully rich array of opportunities available to modern statistical scientists. We maintain a complete catalogue of all past PhD theses (by name and/or year). These are viewable and downloadable as a resource for potential PhD applicants, current students and interested researchers worldwide. Each also indicates the current professional affiliation and activities of the PhD alum to provide some details of professional tracks post-graduation.