Pseudomonas aeruginosa is a highly antibiotic-resistant, biofilm-forming, opportunistic human pathogen. Recent experiments observe striking spatial and dynamical patterns formed by aggregates of Pseudomonas aeruginosa during the early stages of surface colonization. The physical mechanism responsible for of these complex patterns, and the role the patterns play in late-stage biofilm formation are open questions. I will discuss a new multi-scale, statistical dynamics approach - dynamical self-consistent field theory - that we developed to study these out-of-equilibrium patterns in this active matter system. Dynamical self-consistent field theory reduces the interacting, self-propelled, many-bacteria problem to the problem of a single self-propelled bacterium interacting with a mean force field determined self-consistently from the other bacteria. This will allow for relatively fast simulation of large, inhomogeneous colonies while bridging length- and time-scales to preserve biologically-relevant information at the single-bacterium level, such as the self-propulsion mechanism. I will discuss our numerical implementation of the theory, and our ongoing effort to apply the theory to study pattern formation in colonies of Pseudomonas aeruginosa.