Although many researchers now prefer to write their papers using various SaaS solutions, such as Overleaf, I still promote an old-style way when everything is installed on your computer. Of course, this approach has some pros and cons. However, in this article, I am not going to discuss them and will concentrate instead on the topic of how to configure forward and inverse search. In particular, I will show how to do this for my setup with LaTeX Workshop, a VS Code extension facilitating text writing in TeX, and Okular, a PDF viewer available for Linux and Windows platforms.
In the previous article, I shared my setup for producing the graphs for research papers. However, recently when I was working on figures for a new paper, I discovered that my setup must be updated. The reason is that the new matplotlib version (since 3.6) produces a warning that the embedded seaborn styles are now deprecated. In this article, I provide the updates to the setup described in the previous article.
When you write a scientific paper, one of the most common tasks is to analyze the obtained results and design beautiful graphs explaining them. Currently, in the research community, Python’s ecosystem is the most popular for achieving these goals. It provides web-based interactive computational environments (e.g., Jupyter Notebook/Lab) to write code and describe the results, and pandas and matplotlib libraries to analyze data and produce graphs correspondingly. Unfortunately, due to the rich functionality, it is hard to start using them effectively in your everyday research activities when you initiate your path as a researcher. In this article, I would like to share some tips and tricks on how to employ the matplotlib library to produce nice graphs for research papers.
This is the time for me to start looking for a new position. The first thing to do when you start this process, is to update your CV and resume. Although a lot of people (including myself until recently) think that these are two identical documents, in reality they are not. Resume is a short (max 3 pages) concise summary of your experience and achievements that show how you fit the future position. HR people screen tons of documents everyday, and they want to know if a person fits the position from the first glance. In CV, you describe your experience in details, mentioning all the projects that you have participated in, your contributions, what technologies have been used, etc. Moreover, if you have an academic experience, you list there all your publications and academic achievements. As a result, your CV could be quite long especially if you have huge experience, a lot of publications or both. Thus, if you have been chosen the interviewers may understand your experience in details.
Still, both these documents may share the same sections like education and working experience. In order to follow the DRY (don’t repeat yourself) principle and unify the style of my CV and resume, this time I have made them using the same LaTeX template called moderncv. In this article, I explain how I maintain these two documents together and list the modifications that I have made.