*Note: Due to COVID-19, the Post-Baccalaureate Internship Program will be not be taking place in 2021. The Summer Program in Biostatistics and Computational Biology will be held virtually in 2021, please click here for more information.
The 2-3 month Post-Baccalaureate Internship Program is open to students who have received a bachelor’s degree and who are interested in or planning to attend a graduate degree program in biostatistics. Past summer program participants are encouraged to apply!
June – August (approximate)
Two interns will be selected for a 2-3 month summer stay and will:
- Conduct biostatistical or epidemiologic research alongside a Harvard faculty mentor and graduate student mentor
- Participate in collaborative research projects through 1-2 rotations at academic and clinical centers at Harvard
- Attend regular seminars at Harvard Chan School on biostatistical topics
- Participate in our annual Pipelines Into Biostatistics symposium
- Receive directed mentoring and support for graduate school applications
Travel will be provided and interns will receive a salary from other funding sources. For more information, please contact: firstname.lastname@example.org
Alexis Garretson graduated from George Mason University in May of 2018, earning her Bachelor of Science in Biology with a concentration in Environmental and Conservation Biology and minors in Public Health, Economics, and Applied Global Conservation Studies. Her research interests include bioinformatics and complex-system modeling, particularly as it relates to ecological interactions and infectious disease spread. Alexis hopes to pursue a career in academia, where she can continue pursuing her research interests. In the fall, she plans to begin her masters in biology at Brigham Young University and she anticipates pursuing a Ph.D. in biostatistics or mathematical ecology.
Van Truong earned her Bachelor of Arts in Anthropology at the University of Florida in 2017 and completed an NIH research fellowship in Computational Epidemiology at Virginia Tech. In the Network Dynamics and Simulation Science Laboratory, Van worked extensively with local and federal data sets to develop a predictive model for the opioid epidemic by leveraging links from individual and population-level tendencies. Her current research interests include biostatistical applications in genomics and proteomics and the implications of representation in Big Data. She plans to pursue a doctorate degree in biostatistics or a complementary discipline.