The strong interaction is responsible for the binding of protons and neutrons into atomic nuclei. Improved quantitative understanding of how this happens is essential not only for fundamental nuclear research at US experimental facilities but for progress in astrophysics, for experiments on the nature of neutrinos, and for applications to energy and homeland security. The era of precision calculations of nuclear structure and reactions is underway, enabled in part by research findings and products from past NSF grants to the PI. New activities use machine learning and quantum computing tools and will include extending the range and capabilities of statistical methods for assessing theoretical uncertainties and for physics discovery, improving the extraction of information from experiment that minimally depends on model assumptions, and developing and testing a novel approach to systematically describing the full nuclear landscape. The training received by undergraduates and graduate students in carrying out these activities contributes directly to the building of a skilled scientific workforce. The mix of analytical and numerical computation the students and postdocs must employ is excellent preparation for both academic and industrial careers that is validated by the strong track record of past members of this group. Activities are being pursued in three categories: statistical methods for effective field theory (EFT) uncertainty quantification, development and applicat