The Craft of Scientific Research

In my career, I have established three research groups from scratch.  The first, from 1990 to 2011, at the Rizzoli research hospital; the second, at the Insigneo Institute for In Silico Medicine at the University of Sheffield, from 2011 to 2018; the third and last, at the University of Bologna, from 2018 to 2025.  Along the way, I have made many mistakes, but I have always tried to learn from them.   Over the years, some ground rules have emerged from this trial and error, bolstered by specific readings I had on leadership, team building, etc.; all this is summarised in this chapter. Specifically, I talk about leadership, vision and strategy, funding and resources, upskilling and motivating team members, and building effective internal communication. As usual, I take some space for some digressions on whether, in my humble opinion, academic research is a job or a vocation. Enjoy the reading! Summary of Chapter 9 of “The Craft of Scientific Research”, by Marco Vicecon...

While the central part of the book was focused on transferable skills such how to write and how to present which are relevant to anyone doing scientific research, the last three chapters of this book focus on skill that you need at a later stage of your career: how to lead a research group, how to get funded, and today subject, how to choose a research topic. Chapter 8 starts by re-analysing the purposes of scientific research and, from this, discusses why one should choose fundamental rather than applied research and how the research question differs across this divide.  We briefly explain what Pasteur’s Quadrant is, and then we move to the core question: how do we choose our next topic to research? As usual, I first reviewed what was said about this, and I found very little; we report it in the book, but this left me quite unsatisfied. Thus, I decided to take a completely different approach. From 1990 to 2023, I selected 211 papers in which I was an author or co-author and in whi...

Public speaking is a well-developed craft, but for some reason (snobbism?), many researchers I know consider it debasing to put any effort into improving this skill.  I disagree: throughout my book, I insist that scientific research is also effective communication of our findings to our peers.  The best research result may be underappreciated or, worse, misunderstood, if we communicate it poorly. The chapter starts by stressing how a good talk is always the balancing of three elements: storytelling, factual reporting, and public performance.  Then, we discuss each of the key steps to prepare a talk: pick your story, frame it, develop your stage presence, plan the multimedia, put it all together, and plan your delivery. As I go through this, I drift into nostalgia and tell the story of how preparing a scientific presentation has changed, moving from analogue projectors to fully digital systems (here, the figure of an analogue slide projector). Kodak Carousel slide projecto...

Chapters six and seven move to two of the most fundamental crafts of our profession: how to write a scientific research paper and how to give a scientific research presentation. It is with these two seminars that the “business” of doctoral training began many years ago; I was tired of always repeating the same things to my students, so I started giving a seminar once a year. In Chapter 6, after addressing the basic question “Why should you publish?”, we discuss how communication first implies comprehension, and we offer some advice on written language. We introduce the concept of International English, a written form distinct from any spoken dialect of English, and direct non-native speakers to Strunk & White’s “The Elements of Style”.  We then move to a short history of science and of scientific communication, to reach January 5th, 1665, only 27 years after the publication of Galileo Galilei’s “Discorsi e Dimostrazioni Matematiche Intorno a Due Nuove Scienze”, when the first i...

Originally, this topic was not part of the doctoral course for which this book serves as the syllabus. But I felt the need to add it because I believe there is, in various scientific domains, a true crisis about how to assess the credibility of information. I start by referring to the classic theory of information, where quantitative information is treated as an estimand whose estimates are produced by an estimator, which can be of three types: measured, inferred, or predicted.  I propose that the distinction between inferred and predicted is whether the estimator uses prior knowledge; in that case, we call it a predictive estimator. And prior knowledge is, in this narrow definition, considered only as explicit knowledge, such as the second law of dynamics (rigorously defined as an undefeated justified true belief). Then to assess the credibility of the estimator (and thus of the information it estimates), we have three separate frameworks: for measured estimators, it is provided b...

In Chapter 3, we discussed in detail the process through which research is conducted in both basic and applied sciences, and we concluded that, in all cases, conducting research involves idealisation. The concept of idealisation is linked to and connected to the model concept. Thus, the next step in our journey, marked by big questions,  is: What is a scientific model? The chapter is based on a seminar I have offered to PhD students for many years, which is in turn the pedagogical version of this paper: Viceconti, M. (2011). A tentative taxonomy for predictive models in relation to their falsifiability. Philos Transact A Math Phys Eng Sci 369(1954), 4149-61. https://doi.org/10.1098/rsta.2011.0227.  We attempt to define what a model is by examining examples, conducting logical analysis, and revisiting the philosophical debate on the topic, yet we fail all the time.  Then, we turn the problem on its head, and instead of assuming that models are a product of science, we cons...