P.s.: note that a uniform prior does not by default mean that the prior is uninformative. A rare case where it truly is uninformative is the U(0,1) distribution for a proportion (and even there some may disagree XD). For unconstrained and positively constrained parameters, I would argue that a uniform prior is rarely uninformative. Look around the forum for discussions about what is and isn’t informative. Maybe here is a nice place to start: A Bayesian Workflow Question: prior sensitivity with respect to observed data for complex models