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Research Experience for Undergraduates

Data Science

Research Experience for Undergraduates in Data Science 

Rice University is now accepting applications for a 10-week summer undergraduate research program in the general area of Data Science, generously funded by a gift from Google, LLC.

Background

Research Experience for Undergraduates (REU) participants will be assigned to a Rice faculty mentor and will work closely with a Rice PhD student to perform cutting-edge research in Data Science. This could include designing and implementing new machine learning algorithms, applying machine learning algorithms to solve specific problems, or developing methods to manage huge data sets.  

What Is Data Science?

Data science is the science of extracting actionable knowledge from large and complex data repositories, where “complex” may refer to the modality of the data (images, time series, text, as well as traditional tabular data) or other facets of the data in question (data can be complex because they are geographically distributed, or characterized by the ubiquity of missing or inaccurate values). It has quickly become a critical enabling capability in many different fields: science, healthcare, energy, manufacturing, finance, and many others. Data can be used to train algorithms that are more accurate than experienced doctors in recognizing early-state tumors. It can also be used to predict when it is time to do preventative maintenance on a multi-million dollar machine, before a catastrophic failure. Data can be used to detect fraudulent activity in credit card transactions. Furthermore, it is becoming a core enabler for detecting and preventing cyberattacks. Data science is an interdisciplinary field of study, encompassing sub-areas of computer science, statistics, electrical engineering, and applied mathematics.

Eligibility

  • Majors in computer science, statistics, applied mathematics, electrical engineering, or applied/pure mathematics 
  • Some knowledge of computer programming in a language such as Python or Java is required
  • International students must be enrolled at a US university
  • Students must have the ability to come to the Rice campus in the event that Summer 2021 research occurs in-person
  • Applicants must be available during full-time business hours and possibly occasional weekends if required by the mentor

Will the COVID-19 pandemic affect the program? 

It is difficult to say at this time. The program may be virtual, in which case participants will participate remotely.  However, we are still hoping to host students this summer at Rice. In case the program will take place in person, participants from outside of Houston will be given $400 to offset the cost of relocating to Houston. Such participants will then either be housed on campus or will be given an additional stipend to offset the cost of housing.

Why come to Rice? 

Boasting a 300-acre tree-lined campus in Houston, Rice University is ranked among the nation’s top 20 universities by U.S. News & World Report. Rice has a 6-to-1 undergraduate student-to-faculty ratio. Rice students and faculty discover, create and innovate, rising to challenges and solving real-world problems that make a measurable global impact.

Stipends

  • $6000 and accommodation on campus (if circumstances allow)
  • $400 travel expenses (if traveling from outside of Houston)

Key Dates

  • Application Deadline: April 15, 2021
  • Start Date: May 24, 2021
  • End Date: July 30, 2021

Questions? 

For questions, please contact Beth.Rivera@rice.edu

How to Apply

Students can apply to the REU Data Science Program at reuapply.rice.edu.

Recommendations from professors and/or mentors who can vouch for the applicant's intellectual strength and personality are required.

In your application materials, please outline:

  • Research interests: Clearly describe your interests and motivations in data science research and any specific areas in which you are most interested 
  • Readiness: State what you would like to gain from the program
  • Contribution: Describe the unique perspectives you bring to data science research and how you would contribute to a diverse, equitable, inclusive and impactful community