On the variability in career paths - an interview with Dr Aaron Clauset
edited by Ayaka Ando
On the basis of an interview with Dr Aaron Clauset
When looking at the requirements in prestigious grant programs, one could get a fatalistic picture that only a perfect CV following certain standards can lead you to ultimate success in academic career. This view was recently challenged by Dr Melanie Stefan, University of Edinburgh, who proposed a CV of failures as a form of a mentoring tool for early career researchers. A failure (or a ‘shadow’) CV can demonstrate that even the most successful people encounter difficulties on their way. Recently, there is also a body of evidence suggesting that ‘standard career paths’ are not as standard in academia as one might think.
Dr Aaron Clauset is an Associate Professor of Computer Science at the University of Colorado at Boulder and in the BioFrontiers Institute. His field of research is oriented at interdisciplinary network science - developing new tools which have broad applicability, including connectomics, as well as applying data analytic tools to datasets in multiple areas of science, from neuroscience, through ecology to research on the statistics of terrorist attacks. In the recent years, Dr Clauset and his colleagues (featuring Dr Samuel Way, Allison Morgan, Dr Daniel Larremore and Dr Roberta Sinatra) have also investigated the patterns of career trajectories in academia (Clauset et al., 2017, Way et al., 2017). We were lucky enough to interview him on his thoughts, opinions and his personal career trajectory.
In the paper, they analyzed academic careers from several thousands of computer science professors at US and Canadian universities. What they found was that the conventional research trajectory of a rapid rise in productivity to an early peak, followed by a slow decline, only emerges after averaging the individual trajectories of large groups of scientists. Even though the average number of papers per person per year is higher in highly prestigious institutions than in other institutions, the shape of this average trajectory is independent from the prestige of the affiliated institution (Fig. 1A).
However, the average pattern conceals high inter-individual variability in the career trajectories to the extent that only one in every three faculty members follows the average trajectory (Fig. 1B). Furthermore, related work on citation to papers by physicists, carried out by Dr. Sinatra, one of Clauset’s collaborators and colleagues, revealed that groundbreaking discoveries seem to be equally likely at each career stage (Fig. 2, a reprint from Sinatra et al., 2016).
The results from these studies are very optimistic - in a sense that there is not just one canonical way of pursuing a career in academia, and that success can come at every ‘academic age’.
Dr Clauset confesses that his own career trajectory reflects considerable luck at every stage; his failure rates were as follows:
12/15 college applications
9/11 graduate schools
5/6 postdoc positions
11/12 faculty jobs
...which gives an overall 84% rejection rate. It has been a long way to get to a tenured position, as combining basic research with applications to multiple fields of research (which becomes, effectively, a highly advanced data science) implies that you can never stay in your comfort zone, and are always learning a new subject for your next paper - quite like an actor preparing for a new role in a genre they have no experience with. He is now at a very happy point in his career though, having recently been awarded tenure at the University of Colorado Boulder - congratulations Dr Clauset!
Dr Clauset is an ‘academic libertarian’: he supports the idea of personal freedom in academia, including the training grant programs for PhD Students in the US, in which the trainees can freely move between labs during their PhD. He also strongly advises PhD students to support their careers by free exploration: going to summer schools in order to learn new skills and develop new professional contacts. This is a word of encouragement for early career researchers: standard research paths in academia are rare, and the best you can do to get really far, is to never stop searching for you own path.
Way, S. F., Morgan, A. C., Clauset, A. &. Larremore, D. B. (2017). The misleading narrative of the canonical faculty productivity trajectory. PNAS 114 (44) E9216-E9223.
Clauset, A., Larremore, D. B., Sinatra, R. (2017). Data-driven predictions in the science of science. Science 355, 477–480.
Sinatra, R., Wang, D., Deville, P., Song, C., Barabási, A.-L. (2016). Quantifying the evolution of individual scientific impact. Science 354, 596.