REU - Research Experiences for Undergraduates

Mathematical, Statistical and Computational Methods for Problems in the Life Sciences

June 6–July 29, 2022

Department of Mathematics and Statistics

Texas Tech University

Website will continue to be updated throughout January 2022


Research Projects

Project 1: Statistical Learning of Binding Activity Using Structural Characteristics of Protein Binding Sites
Faculty Mentor: Leif Ellingson

Project 2: Demographic and Environmental Variability on Population and Disease Extinction
Faculty Mentor: Linda J S Allen

Project 3: Friedrichs Learning
Faculty Mentor: Chunmei Wang

How to apply


Stipend and Commitment

Student Application Requirements
The student application packet consists of completion of an online form and submission of
  1. college transcripts
    Unofficial transcripts are acceptable. A legible scan of an official transcript is preferred. Your name and the institution's name must be clearly displayed on the transcript. Official transcripts may be required upon admission to the program.
  2. resume
  3. a cover letter including an essay of no more than two pages
    The essay should describe what you hope to gain from the REU experience and how this experience will contribute to the attainment of your future goals. In addition, provide an ordered list of the three research projects on which you prefer to work (1 indicates your preferred project). For your top two preferences, describe how these projects are appropriate to your mathematical or computational skills and interests.
  4. two reference letters
    E-mail contact information should be provided for two faculty members, knowledgeable about the student's research potential.
Applications from women and underrepresented minority students are welcomed and encouraged. Applications completed by March 6, 2022 will receive full consideration. Notification of awardees will be made by April 1, 2022 or until positions are filled.

Online Application Form


Please send an e-mail to

Website based on designs by Giorgio Bornia.

Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No. DMS-2050133. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.