REU Site: Multi-Scale Systems Bioengineering and Biomedical Data Sciences

About This Grant

This three-year REU Site: Multi-Scale Systems Bioengineering and Biomedical Data Sciences focuses on combining experimentation with computational analyses to discover the mechanisms of disease and identify new treatments and cures. The number of Americans with cardiovascular disease, obesity, diabetes, and cancer is increasing because these diseases are complex and affect each person differently based on their genetics, lifestyle, environment, and access to healthcare. Identifying effective therapies requires a workforce of biomedical researchers able to deploy state-of-the-art experimental protocols in wet-lab environments and analyze the resulting data sets using sophisticated algorithms and computational models. Ten undergraduates each summer will be recruited to participate in state-of-the-art systems bioengineering and data science research. REU students will engage in research projects about new biological mechanisms of disease and novel therapies. By equipping students with the skills for conducting and combining wet-lab research with computational analyses, this REU Site will generate alumni who are prepared for further graduate education and/or successful careers in biomedical industries. The goal of this REU Site is to recruit and educate young scientists from a variety of STEM backgrounds, and provide them with the skills, confidence, and mentorship necessary for successful careers in systems bioengineering and biomedical data science. Participants will engage in hands-on collaborative and immersive experimentation and computational analyses, working closely with their faculty and graduate student mentors. Professional development sessions include career advising, training in research ethics and scientific communication, and ongoing mentorship after completion of the summer program. Advances in the biomedical sciences and medicine will increasingly depend upon the application of rigorous and quantitative engineering-based approaches to characterize and interrogate biological systems and the resulting “big data” and a workforce that can successfully address these challenges. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.