This full-time 4 week summer institute held in the Ann Arbor campus of the University of Michigan is targeted toward undergraduates who have an interest (or are susceptible to being interested) in the intersection of Big Data, Statistics, and Human Health. The institute is led by a distinguished group of faculty from the Department of Biostatistics at the University of Michigan School of Public Health (UMSPH) with additional outstanding faculty from Statistics and Electrical Engineering and Computer Science (EECS).
The field of big data science that intersects with public health and biomedicine is changing rapidly with datasets of enormous complexity and size being gathered in diverse areas including genomics, imaging, electronic health records, social media and environmental monitoring. The training of the next generation of quantitative scientists needs to change to meet the demands of the data. More training in data management, data storage, visualization, high dimensional statistics, optimization, causal methods, modeling sparse data and machine learning are needed to equip students to tackle these big data challenges. It is expected that the knowledge obtained from these massive heterogeneous data sources will inform prevention, screening, prognosis and treatment of human diseases and play a major role in biology, medicine and public health in the coming decade.
Each participant will be paid a stipend of up to $2500 to cover costs of travel, housing, and meals. There are no tuition costs associated with the program.
- Applicants must be undergraduates at an accredited school or university with an interest in scientific research
- Applicants are desired to have some background knowledge in computing/programming and introduction to the theory of probability, calculus and linear algebra, but we are flexible on prerequisites
Application opens February 1, 2015 for the Summer 2015 program. Applications are due by March 15, 2015.
For more information or to apply, please visit: http://bigdatasummerinst.sph.umich.edu/