From tomorrow onwards (once or twice a week until February 5), I will be giving an online course on the topic of "Statistical Methods for Fundamental Science" for the INSTATS organization. This is a 5-day, 15-hour set of lectures that I put together to suit the needs of students and researchers who work in any scientific discipline, who wish to improve their understanding and practice of statistical methods for data analysis.

2023 is over and I am looking back at my achievements and failures, to take stock and try to learn something from the matter. This blog looks like a reasonably good place for such an exercise, so I am writing here an inventory of what happened to me in the past 12 months. Sorry if this sounds very boring!

Next month I will be giving three lectures to high-school students on using artificial intelligence for research in fundamental physics, and as usual I am not yet worried by the schedule enough to start thinking at the presentations. Except that in one case the school professor who organizes the event asked me for some preliminary task for the students "to get them in the mood" of the contents of the lecture. 

A number of Master courses in the STEM area mandate students to find a research project abroad to which they participate for 3-6 months. Many of the students find projects that arise their interest through internet searches- at least this is the way I got to know a few of them: as I regularly put details of my research progress in this blog (among other places), I am evidently a visible target. I do not complain about this: many of the students who contact me end up contributing to the projects they get embedded in. In return, they usually get to add a few lines to their CV, and maybe authorship of one or two papers.

In recent times, artificial intelligence has become ubiquitous. Besides powering our cellphones, directing what advertisements we get when we browse internet or read our emails, and creating content in the media, AI-powered hardware is more and more widespread, including self-driving vehicles, home appliances, and a host of other systems for industrial use.

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.