Research Experience for Undergraduates
Analysis & Design of Complex Biological Systems using Data Science
May 31 – August 9, 2017
Students enrolled in Tufts University's REU program will learn and develop data science approaches to analyze and design complex biological systems. In keeping with this interdisciplinary theme, faculty mentors are drawn from multiple departments across life sciences and engineering, including Tufts University Departments of Chemical and Biological Engineering, Microbiology, Nutrition, Electrical and Computer Engineering, and Computer Science. The research projects deal with the collection, analysis, and modeling of biological datasets to understand or design a system of interest, ranging from microbial communities to bioreactors. The research activities are supported through workshops providing a hands-on introduction to modern data analysis, modeling, and visualization tools. Students will be provided training in responsible conduct of research and ethics through seminars and group discussions led by faculty mentors. Students will learn how research is conducted, and many will present the results of their work at scientific conferences. The students will learn about different STEM learning styles of K-12 students, and be presented opportunities to engage in K-12 outreach.
- Host-microbe interactions in health and disease
- Stem cell biomanufacturing
- Computational design of biosynthesis pathways for cell-based and cell-free production of chemicals
- Machine-learning for image processing
- Interactive visualization of data in repositories
- Data visualization
- Image processing
- Statistical design of experiments
- Computational modeling
How to Apply
The online applications will be available beginning in the 2017 spring semester. Students must be U.S. citizens or permanent residents who are enrolled in an accredited institution. Candidates should have a strong academic record. We especially encourage applications from women and minorities, as well as students from community colleges and other institutions that do not traditionally offer research opportunities.