The Center for Research Computing (CRC) at the University of Notre Dame is an ideal setting for the REU student to become familiar with interdisciplinary computational research. CRC provides access to research groups working across a diverse range of computational problems.


REU Programs 2018

Data Intensive Scientific Computing-DISC REU

Students in the DISC REU program will learn how to use high performance computing and big data technologies to enable new discoveries in computer science, physics, and biology. We work on grand challenge problems, like discovering new galaxies in digital imagery, discovering new fundamental particles, using gene sequencing to understand disease, predicting the effect of new drugs using computational modeling, and many more. To do this, we harness large scale computing clusters and big data systems composed of hundreds or thousands of machines, all working together in concert. To make advances in these areas, our goal is to train the next generation of scholars to be adept in both scientific domains and advanced computing techniques.


Computational Social Science REU

This Computational Social Science REU program is a ten week program where ten students will work collaboratively with expert mentors and select from a wide variety of computational social science projects at the University of Notre Dame. Computational social science as an approach to analyzing the social world is has been growing rapidly. An increasing number of social interactions are taking place in the virtual world, using social media, mobile phones, and other electronic means. The digital traces of such interactions and the greater availability and detail of CSS data sets (e.g. surveys, census data, historical records) yield and exponential growth in data available for analysis. New cyberinfrastructure tools and methodologies for data analytics are needed to capitalize on this resource and enhance American economic competitiveness. This REU training environment will develop multidisciplinary social scientists with the appropriate expertise to answer the computational social science data growth challenges and opportunities.