REU Program

The Center for Research Computing (CRC) at the University of Notre Dame is an ideal setting for undergraduate students to become familiar with interdisciplinary computational research. Within the CRC's Research Experience for Undergraduates (REU) program, students spend ten weeks emersed within research groups working across a diverse range of computational problems.

CRC REU Programs

Computational Social Science (CSS) REU

Within the Computational Social Science (CSS) REU program, ten students select from a wide variety of computational social science projects at the University of Notre Dame and work collaboratively with expert mentors. Computational social science as an approach to analyzing the social world is growing rapidly. An increasing number of social interactions are taking place in the virtual world via 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 an 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 program develops multidisciplinary social scientists with the appropriate expertise to answer the computational social science data growth challenges and opportunities.

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Data Intensive Scientific Computing (DISC) REU

Students enrolled in the Data Intensive Scientific Computing (DISC) REU program learn how to use high performance computing and big data technologies to enable new discoveries in computer science, physics, and biology. Students work with the CRC 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 much more. To do this, the CRC harnesses 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.

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Featured Alumni


Abigail Boatwright

An Analysis of Intellectual Property Diffusion in Global Markets

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