Did you recently finish a Master in a scientific discipline, and wish to do some research before deciding whether to embark in a Ph.D.? Do you fancy coming to Padova and work with me and a team of physicists, computer scientists, and astrophysicists on detector optimization? Do you like the idea of traveling to Kaiserslautern for significant periods during the internship, to work under guidance of Prof. Nicolas Gauger at RPTU? Or do you know somebody to which the above might apply? Then please read on.

The 8th Congress of the USERN Organization took place during the past three days (November 8-10, 2023) at the RAU University in Yerevan, Armenia, and it was a complete success, which has left me overwhelmed by the amount of great interdisciplinary science, fantastic art in multiple forms, and the intensity and rate of positive feelings I received throughout the event. I offer below a short report of the event and my impressions, which may of course be biased by being the President of this fantastic network, but does feel a rather trustworthy report now that I read it again.

Since most of the building blocks of our own body are protons, the above title might disturb sensitive readers. On the other hand, describing a proton as a bag of garbage has several merits, as it is a fruitful analogy that may be carried forward when we wish to examine experiments that studied the structure of matter. I will explain what I mean in a moment below.

The occasional reader of this blog will excuse me if yet again I do not report here of this or that new result by the LHC collaboration, and instead discuss matters of lesser relevance. But to me, education is important. Even if I am not a University professor, but rather an employee of a research institute (and as such, not obliged to spend some of my time teaching), I do teach courses to university students. I do that because I believe I can give students a positive imprinting on the beauty of physics, on the exciting nature of research in fundamental science, and on how interesting all of that is. 

As I am waiting in Prague airport for my flight back home, after a few days spent discussing the options of the SWGO collaboration for the detectors we are going to build, I came across (through compulsive scrolling on twitter) a thread that caught my attention. It was about emails to academics on PhD openings. Since I found the discussion there a bit too forgiving on the academics, I wish to express my position here - possibly in a less toxic environment.

Last week I received in my mailbox a copy of the Princeton University Press book "Machine Learning for Physics and Astronomy" by Viviana Acquaviva. They sent me a copy because I had reviewed its contents for Princeton Press.


I am happy with the book. When I accepted to review it, I was a bit hesitant because I am not a computer scientist. I might pass as an expert in machine learning because after all I have been developing such tools for 20 years now (or maybe I should say over 30, as my first attempt was in 1992, with a bootstrap-powered classification method), but I feel I still lack knowledge in some of the theoretical underpinnings, and there are holes in my knowledge base.