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Fluid at microscopic scales is modeled by random particle simulation methods, which capture fluctuating behavior (e.g. Brownian motion) but have extremely high computational cost. Fluid at macroscopic scales is modeled by partial differential equations, which can be solved efficiently but assume away fluctuations. Motivated by applications where microscopic fluctuations drive macroscopic action, I develop a multiscale algorithmic hybrid, which couples a particle method and a stochastic formulation of Navier-Stokes.