Using Bayesian for estimating parameter

My problem is finding the Posterior distribution:
Via the Bayesian theory Posterior ~ likelihood function * Prior distribution.
in here: I has the likelihood function P(k/s)has the normal distribution with mean = 1.3 and standard deviation = 0.05 and Prior distribution P (s) is uniform distribution [0,1].

How to find the posterior distribution P(s/k) by bayesian method and Markov chain Monte carlo in pymc3.

Thanks you.