Automation of analysis pipelines allows streamlining the analysis process resulting in more efficient processing with fewer errors. Moreover, it provides the means for quantifying the accuracy of experimental results, as systematic uncertainties can be easily quantified by re-running the analysis to test the sensitivity of the outcome to various factors including different algorithms, as well as experimental and analysis parameters. While these techniques are standard processes in mature hard sciences such as nuclear and particle physics, they are seldom applied in neuroimaging resulting in poorly verified outcomes. I am interested in pursuing this in the drive to better quantify neuroimaging results. To this end, I wish to fully utilize the high performance computer cluster at Unveristy of Toronto, SciNet, building on vast experience running highly advanced parallel algorithms on the WestGrid cluster (www.westgrid.ca).