Bin Mu, an assistant professor for the School for Matter, Transport and Energy of the Ira A. Fulton Schools of Engineering, has a research opening for Fulton Undergraduate Research Initiative (FURI), Master’s Opportunity for Research in Engineering (MORE), Honors Research students and volunteer students regarding the design and prediction of materials’ structure-property relationships by machine learning/data mining.

The project is to develop a machine learning /data mining code for developing structure-property relationships of porous materials, which can be used in gas separation, CO2 capture, and water treatment applications.


  • porous material
  • structural design and modeling
  • machine learning/data mining

Student qualifications/requirements:

  • résumé
  • transcripts
  • strong programming skills and communication skills

Semester(s) or start/end date of position: Start immediately and may last for more than one year

Number of hours per week: 10

Stipend amount/hourly wage/volunteer position: Volunteer position

How to apply: Please contact Bin Mu by email at