Abstract: In many problems spanning transition-metal catalysis and quantum materials, quantitative prediction hinges on treating electron correlation and electron–phonon coupling beyond standard mean-field and perturbative approaches. In this talk, I will describe our efforts to advance the auxiliary field quantum Monte Carlo (AFQMC) method, enabling first-principles electronic structure calculations in challenging correlated systems with accuracy beyond state of the art coupled cluster methods and more favorable cost scaling. I will also discuss how neural quantum states can be used to model electron–phonon dynamics and compute spectroscopic observables. Finally, I will present results on possible microscopic mechanisms underlying chirality induced spin selectivity (CISS).