NSF-Funded REU Program: Application of Data Science to Chemistry


NSF REU Site: Application of Data Science to Chemistry

Atlanta, GA – May 22, 2022 until Friday, July 22, 2022

Are you interested in any of the following areas?

  • Materials Chemistry
  • Application of Data Science to Materials Chemistry
  • Application of Machine Learning to Materials Chemistry
  • Application of Mathematics to Materials Chemistry
  • Application of Computational Chemistry to Materials Chemistry

Chemistry majors and other STEM (Science, Technology, Engineering and Math) majors interested in the interface between materials chemistry and data science are encouraged to apply to participate in a 9-week undergraduate research program hosted by Clark Atlanta University and Atlanta University Center Data Science Initiative. Participants will gain broad perspectives by participating in a dynamic research environment while working with a faculty mentor at one of the five research groups consisting of one chemistry and one data science faculty member. The program also includes several professional development activities, REU seminars with faculty and research scientists, and an end-of-program symposium.


Participants will receive a stipend of $5,400 for the 9-week program, a travel allowance, and housing on the Clark Atlanta University campus. In addition to this, the HarvardX’s Data Science certificate and GRE preparation costs for participating students will be covered under the program. Participants must be U.S citizens or permanent residents of the U.S. and currently enrolled in an undergraduate degree program at a U.S. college or university (be rising sophomores – seniors).


Download our Sample REU Research Projects HERE! 

Intent to apply: E-mail Dr. Seyhan Salman at with REU Summer 2022 in the subject line.

Application Deadline: TBD; however, early application is encouraged.

Questions? Contact Dr. Seyhan Salman at


Acknowledgement of Support and Disclaimer

This material is based upon work supported by the National Science Foundation under Grant No. 2150206. 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.