The generalized Polynomial Chaos(gPC)method is a popular method for solving partial differential equations(PDEs)with random parameters.However,when the probability space has high dimensionality,the solution ensemble size required for an accurate gPC approximation can be large.We show that this process can be made more efficient by closely hybridizing gPC with Reduced Basis Method(RBM).Since the reduced model is more efficient,costs are significantly reduced.