\(Pr(\theta \lvert y) = \frac{L(y\lvert\theta)Pr(\theta)}{Pr(y)} \propto L(y\lvert\theta)Pr(\theta) \propto L(y\lvert\theta) \)

where the last proportionality statement follows from assuming that the prior is uniform, hence having a density equal to a constant.