Skip to main content

REU in Data-enabled Science and Engineering

Research Experiences for Undergraduates (REU) opportunity in UW ChemE

Application deadline: February 14, 2020 | Program start date: June 22, 2020

data science illustration

New sources of data from high-throughput experiments, observational studies, and simulation are transforming all of science and engineering. In this new era of data-enabled science and engineering, discovery is no longer limited by the collection and processing of data, but by data management, knowledge extraction, and the visualization of information.

The REU in Data-enabled Science and Engineering (RDSE) will provide support for a select group of undergraduates to participate in data-enabled science and engineering research under the mentorship of UW Chemical Engineering’s world-class faculty and graduate students. Students will complete a nine-week immersive research project in a single lab leading to an abstract and poster.

Program Goals

  • Encourage students to pursue STEM careers
  • Provide exposure to hands-on wet and dry-lab research
  • Introduce students to the core areas of data science: data management, visualization, and statistical and machine learning
  • Improve student knowledge about the nature of research including ambiguity, evolving understanding, and the open-ended nature of research
  • Develop student inquiry skills including formulating research questions, designing experiments, analyzing data, communicating results, and envisioning future steps
  • Impart relevant, state-of-the-art content in biomaterials, clean energy, molecular simulation, nanoscience, nanomanufacturing, and systems and synthetic biology

Examples of Past Projects

  • Employing data-driven techniques to better understand, engineer, and predict the behavior of CRISPRa
  • Using COMSOL Multiphysics simulations to improve the efficiency of roll-to-roll (R2R) nanoimprint lithography
  • Evaluating surfactant effects on nanoparticle toxicity in the brain microenvironment
  • Exploring neural network, random forest, decision tree, and naïve Bayes models for olfactory receptor deorphanization

How to Apply

Please prepare the following:

  • A 250-word (max) personal statement explaining your preparation for this experience and its relevance to your career goals. We suggest drafting this offline and then cutting and pasting it into the form.
  • A 100-word description of a data science problem or application that interests you. This does not need to be limited to the RDSE research topics. We suggest drafting this offline and then cutting and pasting it into the form.
  • Unofficial Transcript(s) and CV. As part of the online application process, you will need to upload .pdf files of transcripts from all colleges or universities attended as well as your personal CV. Please combine these as a single file and include your last name as the first word of the title. Please note that tentative offers of admission will be made based upon unofficial transcripts, but official transcripts will be required if admission to RDSE is offered and accepted.
  • Email addresses for two professors or other mentors who are familiar with your academic abilities who would be willing to serve as references on your behalf (letters are not needed). An email message will be automatically generated notifying your references that their names have been submitted on your behalf.

Apply using this Google Form

Application deadline: February 14, 2020

Additional Information

RDSE is open to students who have completed two years of college, community college, or tribal college

A stipend of $5,000 and on-campus housing (if non-local) will be provided

Questions? Please contact Prof. James Carothers at