Master of Science

 

Get the Skills to Look at Health in a Whole New Way

The Master of Science in Population Health Sciences prepares students to integrate knowledge, theory, and tools from multiple disciplines to find solutions that improve health.

Students will get a solid grounding in population health with a focus on data-driven inquiry including SAS and R programming and predictive modeling. By mastering 30 core competencies across seven domains, students will have the skills to employ rigorous scientific and analytic methods in a range of healthcare environments.

Learning takes place in both the classroom and real-world settings to ready them for careers in the public or private sectors.

Class sizes are small – a 1:2 faculty-to-student ratio – allowing students to form strong connections with peers and instructors. Students also have access to courses and researchers across Duke University and in the Duke University Health System leveraging world-renowned research that is only happening at Duke.


"Dr. Leah Zullig is a fabulous teacher, and was an absolute joy. She carefully took time to answer our questions, and go over topics in depth. She was flexible with classes, and moved around subject matter as necessary to spend time on topics we had questions about and more interest in.” 

- 2019 Matriculant


In Class with Assistant Professor Emily O'Brien, PhD

About Dr. O'Brien

Education: PhD, University of North Carolina at Chapel Hill, Gillings School of Global Public Health
Research Focus: Comparative effectiveness, patient-centered outcomes, and pragmatic health services research in cardiovascular and pulmonary disease
Teaching: PHS 701 Applied Analytic Methods for Population Health Sciences I (Syllabus):  

I want my class to be as interactive as possible. More engagement makes it easier to explain the concepts and helps students process the information. Upon completing my class, students should be able to think like an analyst—to translate a research question and data source into an answer using statistical methods. The tools they learn will help them understand the limits and strengths of data should they choose to become an analyst, a project manager who just needs to understand the lexicon, or an implementation scientist who uses data to bring innovation into practice.

Students will be working with data in some capacity in any job they land post-grad school. I want them to be comfortable with levels of uncertainty when they wade through the messiness of real-world information.