Deadline: February 20, 2017

Data+ is a 10-week summer research experience that welcomes Duke undergraduates interested in exploring new data-driven approaches to interdisciplinary challenges. Students join small project teams, working alongside other teams in a communal environment. They learn how to marshal, analyze, and visualize data, while gaining broad exposure to the modern world of data science. Data+ is part of the Bass Connections in Information, Society & Culture theme.

Participants will receive a $5,000 stipend, out of which they must arrange their own housing and travel. Funding and infrastructure support are provided by a wide range of departments, schools, and initiatives from across Duke University, as well as by outside industry and community partners. Participants may not accept employment or take classes during the program.

For some projects, human subjects research training may be required and will be provided in advance. With each project, we have attempted to list potential majors and/or interests that might be best suited for the project, but these should not be seen as requirements in any way. Quantitative STEM majors like mathematics, computer science, statistics, and electrical engineering are relevant to all.

For the Application, Please Submit:

  • Cover letter
  • Curriculum vitae
  • Transcript
  • Contact information for two references (note no letters are desired)
  • One paragraph (per project chosen) about how you can contribute to the project
  • And anything else requested in the program description

Browse the current projects, choose three you’re interested in, and send in your application. The program runs from May 22 until July 28, 2017. The application deadline is Feb. 20, 2017, but we will evaluate applications on a rolling basis. The first round of offers will go out January 25 and the second will go out February 25. For any questions, contact Paul Bendich.

Projects for Summer 2017

Data Viz for Long-term Ecological Research and Curricula

Electricity Access in Developing Countries from Aerial Imagery

Mapping the Ocean Floor

Open Data for Tobacco Retailer Mapping

Open Source Spatial Visualization for Public Health Intelligence

Marriage and Statistics through Space and Time

Visualizing Suffering: Tracking Photojournalism and the Syrian Refugee Crisis

Nutrition Dependent Growth in the Laboratory Rat

Quantifying Rare Diseases in Duke Health System

Quantifying Phenotypic Evolution during Tumor Growth

Validating a Topic Model that Predicts Pancreatic Cancer from Latent Structures in the Electronic Medical Record

Visualizing Real Time Data from Mobile Health Technologies

Ghost Bikes

Building a Duke SLED (Duke Surgery Longitudinal Education Database)

Comparing the Exploration of Academic Majors at Duke

Quantified Feminism and the Bechdel Test

Controlled Substance Monitoring Visualization

Classification of Vascular Anomalies