Starting in May 2006, the Department of Statistics at North Carolina University (NCSU) and the Duke Clinical Research Institute (DCRI) at Duke University are jointly administering an integrated program for predoctoral training in biostatistics to prepare trainees for careers in medical research, with a focus on cardiovascular disease (CVD) research. The goal of the program is to prepare graduate students studying for a Ph.D. in Statistics at NCSU to excel as both biostatistical methodologists and biostatistical collaborators, preparing them to conduct state-of-the-art biostatistical research relevant to important problems in CVD and other medical research. Trainees receive training in foundations of and new developments in biostatistical theory and methodology and work with leading researchers on cutting-edge issues in CVD science to which they apply their statistical training.
The training program is funded by the National Heart, Lung, and Blood Institute and includes a stipend and tuition and fees. Please see below and the links to to the left for more details!

The training involves formal coursework at NCSU on statistical theory,
including probability, inference, linear and other statistical models,
measure theory and advanced probability, and advanced statistical
inference, and statistical methods, including clinical trials
design/analysis, longitudinal data analysis, survival analysis,
epidemiology, and cutting-edge special topics, such as causal
inference; and at DCRI in fundamental aspects of CVD science and in
research responsibility and ethics. There is also extensive formal
and experiential training in communication and leadership skills at
both institutions. Trainees are introduced to DCRI CVD research
gradually and will evolve over their tenures to holding full
collaborative apprenticeships in which they are fully integrated as
functioning members of DCRI project teams. The apprenticeships will
provide trainees with extensive working knowledge of CVD science, the
opportunity to develop collaborative skills, and the recognition of
how new biostatistical methods development follows from challenges
encountered in the collaborative context. This last point will be
emphasized through mechanisms under which statistical methodological
challenges arising in trainees' apprenticeships will lead to doctoral
dissertation research in biostatistics.
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