As hydrogen-fueled technologies gain traction throughout the world, a better set of standards is needed to govern the building of hydrogen-safe infrastructure.  As with most environmental degradation problems, industry-specific testing has been prioritized, leading to phenomenological standards that are adjusted as new data or new failures cause readjustments.  Physics-based predictive models are needed, which can remove or reduce the need for exhaustive testing of each new material.  NIST has one of the few in situ hydrogen testing facilities in the world and is producing data which has significantly improved several hydrogen performance standards.  However, modeling is needed to extend the applicability of the data produced to multiple standards and particularly to full classes of materials.  Techniques such as multi-scale computational modeling are needed to distill the current knowledge of hydrogen embrittlement mechanisms, from mechanical testing, microscopy, and diffraction techniques, into physics-based predictive models needed to implement hydrogen-safe infrastructure and predict hydrogen-resistant alloy designs for the future.  NIST has access to multiple modeling software options (e.g. ABAQUS, ANSYS, COMSOL), as well as large computational clusters. This opportunity focuses on applying or developing models of fracture and fatigue of materials exposed to hydrogen.