During a PhD, one can read and store hundreds of papers. There is always a need to keep the papers well organized and kept, and also to have a way to easily transfer the citations of the papers to a manuscript.

Earlier this week, I was using Freesurfer to generate some nice brain cortex images to add them to a paper. My go-to program to create scientific figures is Inkscape, mainly because it is free, relatively easy to use, and there are lot of nice guides online. However, the problem with this kind of software is that sometimes, simple actions can actually only be done with workarounds or with unintuitive tools. This small blog post is a testament to one of those times.

Processing images and scans of the brain has been a big part of my PhD activity. When I started, I had never worked with brain images before, neither with neuroimaging tools and libraries. I was given a set of scripts that my supervisor had used for processing brain images, but apart from that I had no other support: nobody else in my department worked on brain imaging.

In this small blog post I will detail how to use Jupyter applications (notebooks and JupyterLab) from a computing node in a HPC. This post is a follow-up to the previous post.

One of the most important aspects of a machine learning related PhD is the large computing power needed for the experiments. Normally, in research centers and universities, this is solved by the availability of a cluster infrastructure with large computing capabilities, accessible by every researcher.