Materials Discovery is one of the research areas where gaining a deeper understanding of the workflows,  research computing and data requirements, collaborations, and challenges will enable the ERN to have the broadest impact across multiple research disciplines, pedagogical approaches, senior level college and university administrators, and other organizations within the region and beyond. Researchers in materials discovery are realizing that their traditional data-intensive HPC workflows are reaching the limits of spatial and temporal scales required to make deeper insights and predictions. For this reason, they are looking to new paradigms that include convergence of HPC and Machine Learning (ML) methodologies, algorithm development, and novel ways to access the data distributed across multiple institutions used in training systems as promising approaches to overcome the major computational performance limitations.  Materials Discovery offers an attractive testbed for advanced cyberinfrastructure of the sort the ERN can offer through future funding opportunities such as the Mid-Scale RI-1 program and DMREF. As with Cryo-EM/Cryo-ET, this session will explore possibilities for extending collaborations to include other institutions as well as the community of Research Computing and Networking organizations and to form a working group to focus on future workshops and content for the Mid-Scale proposal.