Christopher Wolverton1

1, Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois, United States

Data science and data-driven efforts are making substantial impact on the discipline of Materials Science and Engineering. The underlying techniques and research in this area need to be incorporated into educational efforts and curriculum in order to prepare MSE students to use these methods in their materials work. In this talk, I provide an overview of some of the educational efforts in Materials Data Science at Northwestern. There are substantial efforts in this area in faculty members’ research, and these topics naturally have entered the educational curriculum. There are many examples of the incorporation of computational tools into both the undergraduate and graduate curriculum. These are focused on both the tools themselves, but also on the data and databases that result, and the use of these databases in materials design and discovery efforts. In additional, the Center for Hierarchical Materials Design (CHiMaD) is a center of excellence for advanced materials research focusing on developing the next generation of computational tools, databases and experimental techniques in order to enable the accelerated design of novel materials and their integration to industry, one of the primary goals of the U.S. Government's Materials Genome Initiative (MGI). The research within CHiMaD also provides opportunities for educational impact as well. Finally, we discuss the Integrated Computational Materials Engineering (ICME) Master’s program, in which students participate in interdisciplinary courses and seminars where some integrate machine learning methods in materials projects in collaboration with Computer Science faculty.