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The University of Arizona's Research Training Group (RTG) in Data Driven Discovery supports integrated research and training in data driven modeling techniques and applications, including computational neuroscience, fluid turbulence, medical imaging, and more. Our Research Experience for Undergraduates (REU) program provides opportunities to learn and apply foundational mathematical and computing skills.
Application. We have two sources of funding:
UA's Undergraduate Research Opportunities Consortium (UROC) supports students from groups traditionally underrepresented in graduate studies in STEM; and
the National Science Foundation (NSF) provides support for US citizens and permanent residents.
Unfortunately, we can only support students who are eligible for at least one of the two funding sources above. The two options differ mainly in funding source; all RTG research and training activities are open to both groups (UROC students may have additional activities), and both sources of funding are open to non-UA students.
UROC application (deadline 2/1/22): apply to the Summer Research Instiute and state that you are interested in working with the Data Driven Discovery REU
NSF application (deadline 2/28/22)
Note that while UROC does not require letters of recommendation, we do ask for 2 letters from all applicants for NSF funding. If you apply to UROC, you will also be considered for our NSF funding provided you arrange for 2 letters to be sent to us (not UROC!) at the same time.
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.
As a member of the RTG-REU, you will
work with RTG faculty, postdocs, and graduate students on data driven modeling and applications;
learn mathematical ideas fundamental for data science;
learn to use basic tools for data-intensive scientific computing;
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!)
For Summer 22:
The Summer 2022 RTG-REU program will start in early to mid June, and end in early August. (We are well aware that some of you may have exams in early June, and will be happy to work around your schedule as needed.)
Full-time, 40 hour per week commitment required.
Modality: for Summer 2022, the REU will be remote by default, with in-person component for local participants (i.e., those who will already be in Tucson) at their mentor's discretion. Group activities will be remote (possibly hybrid for local participants as conditions allow).
Eligible participants will receive an estimated stipend of $5,000.00 (to be confirmed) for the summer.
Potential projects include
Automated segmentation of spine X-rays for scoliosis detection (Prof. Marek Rychlik)
Stochastic Models of Thermostatically Controlled Multi-Unit Buildings (Prof. M. Chertkov)
Reconstruction of vector fields from weighted and unweighted vectorial Radon transforms (Prof. Leonid Kunyansky)
Machine learning and medical imaging (Prof. Ali Bilgin)
Optimal planning for self-driving cars (Dr. Christian Parkinson)
Neural data analysis and network dynamics (Prof. Kevin Lin)
Using 3D morphological data in multiphysics simulations (Prof. Laura Miller)
Circadian rhythms and wearable data (Prof. David Glickenstein, Prof. Kevin Lin, and Dr. Avinash Karamchandani)
Depending on interest and availability, we can also 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!
Diversity commitment: we encourage applications from traditionally under-represented groups. The University of Arizona is a Hispanic Serving Institution and an American Indian and Alaska Native-Serving Institution.
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