RTG Research Experience for Undergraduates

As a member of the RTG-REU, you will learn   

- learn mathematical ideas fundamental for data science;

- learn to use basic tools for data-intensive scientific computing;

- gain experience applying these tools to concrete problems of data-driven modeling and inference under the guidance of RTG faculty, postdocs, and graduate students;

- learn to communicate science effectively;

- learn about applying to graduate schools.                                            

Qualifications: We expect all REU students to have completed a standard calculus sequence (including vector calculus) and have had some exposure to linear algebra and differential equations at the time they start the REU. Some of our projects may benefit from additional background knowledge. Experience with some form of programming, e.g., Matlab or Python, is helpful but not required. (If you're interested but unsure whether you qualify, just ask!)

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APPLICATION. We are funded by a grant from the National Science Foundation (NSF).  The grant provides support for US citizens and permanent residents.  To apply, fill out the following application:

• Start your application here: Review begins March 1 and will continue until all positions are filled

Note that we do ask for 2 letters from all applicants.

Please email Prof. Kevin Lin (klin@math.arizona.edu) if you have any questions.  Letters of recommendation may be emailed to rtg-admin@math.arizona.edu.

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MORE DETAILS ON THE PROGRAM

The main Summer 2024 RTG-REU activity is the Data Driven Discovery Bootcamp.  This will start in mid June and run for ~2 weeks.  The program is hybrid, with the first week online and the second week in person in Tucson.  A very small number of slots are available for a full summer research program with RTG faculty.

For all students, full-time, 40 hour per week commitment is required for the duration of the program.  Eligible participants will receive a stipend (proportional to the duration of their participation) so they can focus on their summer research.

Topics for 2024 are

• Data assimilation for nonlinear chaotic dynamics (Prof. Kevin Lin and Dr. Shay Gilpin)

• Data driven modeling of biological systems (Prof. Laura Miller and Dr. Xiaolong Zhang)  

Depending on interest and pending budget and advisor availability, we may be able to arrange projects with other RTG faculty, postdocs, and graduate students. Let us know your areas of interest and/or whom you'd like to work with in your application, and we'll do our best to match you with a suitable advisor and project!