High-fidelity battery modeling requires the estimation of numerous physical parameters in order to properly capture the physics of the electrochemical, thermodynamic and chemical processes that underlie the system. Using Julia, the parameters for this model were able to be estimated by speeding up the code such that a Markov Chain Monte Carlo approach (Hamiltonian Monte Carlo) could be used, combined with a high-performance computing cluster, to sample the vast search domain and reach the global error minima.