Clémence Corminboeuf
Interview by Carey Sargent, EPFL, NCCR MARVEL
The biggest challenge that woman scientists face is…
I used to say that it’s finding a good time to have children (if you want some), but now that I am a bit older, a posteriori, I think it’s more understanding that there’s no bad time to have children. Of course, you don’t know this early on. You cogitate, okay, when is the good time and you worry, because it is a very demanding career, but actually there’s no bad time—I prefer to say that then there is no good time. At the end of it, I think we are superheroes, and this is something that becomes very clear when you have kids.
Solving the dual career issue (the “two-body” problem, as a quantum chemist would say) was also a big puzzle for me. Switzerland is very much behind in this respect and our academic system has zero mechanism aiming to facilitate the life of scientific couples.
It is obvious that most woman scientists will meet their spouse at work (because we work so much). If the Swiss Institutions (and the SNF) want to attract and retain more women, they will need to take better care of their supportive partners.

I chose a scientific career because…
The question I asked myself was more specific, actually, it was which science—would I choose physics or chemistry? And I though physicists were weird, so I chose chemistry. I think though that I always wanted to do science. I cannot remember a time that I was not interested in science and so it came very naturally, I just had to decide which one. I picked chemistry because of my ideas about physicists – I wasn’t very mature at the time!
If I were not a scientist, I would be…
Frustrated! I think it’s kind of a luxury to be a scientist and I think I would be frustrated if I weren’t one.
My most exciting MARVEL discovery to date has been…
The most exciting MARVEL discovery to date has been the true collaboration that I had with several people within the group. For instance, the machine learning and catalysis with Basel group of Anatole von Lilienfeld, there’s machine learning of the electron density with Michele Ceriotti, there’s now also work related to analyzing the topology of the electron density with Berend Smit and so I think that that’s really the key great MARVEL work, combing the expertise from these different groups.
My top two papers are...
In terms of MARVEL papers, the Chemical Science with Anatole von Lilienfeld “Machine learning meets volcano plots: computational discovery of cross-coupling catalysts” is one and the other I’d cite is the recent ACS Central Science paper “Transferable Machine-Learning Model of the Electron Density” with Michele Ceriotti. Again, these are the top two papers, I would pick in a MARVEL context not only because of the associated synergy but also because they are really great examples of cutting edged innovations in the field of machine learning applied to quantum chemistry problems.