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Return to Biostatistics

Susceptibility to many complex diseases can be governed by the interactions between modifier genes and environmental factors. In the post-genomic era we are beginning to comprehend and compile the breadth of genetic variation within the human population. Refined use of this information requires the development of advanced methods of biostatistical analyses. In addition, to make significant progress in disease prevention, a hallmark of public health, there is a pressing need to translate advances in basic science into programs and policies focused on preventing common and costly chronic diseases. Only by integrating emerging scientific information into the design of clinical and public health interventions can we fully extract the value of these advances for public health.

To meet these challenges, this training program provides training of the highest quality in biostatistical theory and methods as well as in molecular biology, computational biology, genomics, and statistical genetics. The pre-doctoral trainees will learn to be true collaborative partners with molecular biologists and biologically-trained computational biologists and to pursue methodological research that is motivated by, and helps to solve, real analytic issues that arise in laboratory, clinical, and population studies. This training program also encourages the development of interdisciplinary research, especially in genetics and the various "omics" arising from new methodologies for characterizing biological activity, at Harvard and externally in the broader statistical and biomedical communities.

Stipend and tuition support for this training program is funded through a National Institutes of Health grant (T32 GM74897).