Here we are: 2013 is out, 2014 is in. It is time to examine one’s life in the past year. For me, it is time to examine life more generally, as for any person who is on the academic job market this season. Specifically, I would like to discuss today some issues surrounding a job search that completely or partially fails. Let’s start with the paradox that gradually arises in the applicant’s head. If you are applying for jobs, at some level you certainly believe that
(1) You are a good scientist, i.e., you know how to ask interesting research questions, obtain solid results and publish in good journals.
If your job search is failing, it means that
(2) No one wants to hire you.
Clearly, one of these two statements has to be wrong! One’s first reaction is of course: (2) gotta be wrong. Just be patient, wait another week, and an interview invitation will come. But as time goes on and silence continues (with an occasional rejection email), the second thought creeps in: Maybe (1) is wrong after all. Maybe you have delusions of grandeur, a condition not uncommon among scientists, but the truth is that nobody wants to hire you because you are a lousy scientist. Being a scientist (even if lousy), the next step is of course to test this hypothesis. So, you ask your advisors to take a look at your application and tell you the truth, no matter how bitter. But their uniform response is that your application is very strong, and that they are surprised by the lack of interview invitations. Thus, you that you are not delusional, and (1) is correct. So, the paradox remains.
This brings me to the main point of this post. You can be an excellent scientist and still not get a professor job. I am sure this sounds as obvious to some people as shocking to others. In fact, it is both obvious and shocking to myself. It is obvious because we all know how tough the job market is right now, with some especially horrifying stories like this one where a person applied to over 150 position, without much success. At the same time, deep in our hearts we believe that the system somehow still works, and those few jobs that exist go to the best of us. That’s one reason (aside from loving science) for why so many grad students and postdocs spend nights and weekends in the labs pushing their science forward – in the end, all these efforts will be rewarded with recognition, jobs, and grant money, won’t they? This disconnect in one’s mind between the general population and oneself is similar to what was happening in the Soviet Union in the 1930s. Everybody was well aware of the night arrests and millions of prisoners in the Gulag. Yet, everybody believed that all those arrested were in fact spies and saboteurs… Until KGB knocked one’s own door one night. We, humans, are just inherently good in deceiving ourselves (listen to this Radiolab podcast).
Unfortunately, it is not the case that the jobs go to the best people, just as grants do not necessarily go to the best PIs (see for example here and here). This is not to say that the people who get interviews and eventually offers are bad scientists. Most of them, if not all, are good scientists. But they are not the best, because, for one thing, it is impossible to determine who the best is with precision of 1 in 300. Some have written that subjectivity of the search committee causes noise in the selection process, but I actually don’t think that the selection process is that random. There is anecdotal evidence from my own circle of colleagues that the distribution of interviews a candidate gets is bimodal or at least leptokurtic. In other words, most candidates get no interviews, but those who get one, get many. Thus, I suspect that the probability of getting an interview as a function of “hireability” of a candidate has a sharp transition: either you are hireable, in which case you get many interviews, or you are not, in which case you get none.
What determines how far one is on the hireability axis? The usual stuff, of course: papers, grants, and references. And this I think is precisely the source of the illusion of fairness that many of us firmly cling to. It seems that if you published good papers, your PI will write you a strong letter, and you will get a good job. Alas, not all good papers are equally good, and not all strong letters are equally strong. Consider two candidates A and B, doing similar type of research, with the same number of papers, all good quality, and with equally strong letters. Just based on this information it is impossible to decide which of these two should be interviewed.
Now consider the following. Candidate A graduated from Ivy League School 1, is now working as a postdoc with independent funding in Ivy League School 2 in a lab of an HHMI investigator and has 2 papers in Nature. Candidate B graduated from State School 1, is now working in a junior PI’s lab in State School 2, has no papers in Nature, and has no independent funding. The interview decision is a no brainer now, isn’t it?
But did this new information actually tell us anything new about who a better scientist is? I don’t think so. The stories could be as follows. For some (perhaps chance) reason, candidate A pursued her PhD in a top-tier school, in a lab that regularly publishs high-profile papers. Her project went reasonably well, and she published a Nature paper too, which helped her secure independent funding. Working in an HHMI lab as a postdoc, she had access to virtually unrestricted resources and could pursue her wildest experimental dreams. The results were interesting, and of course were published in a high-profile journal. Candidate B, on the other hand, pursued her PhD for some (perhaps chance) reason in a lower-tier school, in a lab that does good science, but does not regularly publish high-profile papers. Neither did she. Because she is a foreigner, she wasn’t eligible for most of postdoc-level grants. She chose to work with a junior PI as a postdoc because she wanted to work on a particular system. She had to do it on a smaller scale than desired because of tight funding, but the results turned out to be interesting. Nevertheless, the junior PI didn’t have enough weight to push through for a Nature paper.
Yet, despite lack of real differences in the quality of science between candidates A and B and a rather random chain of events that led to differences in their CVs, one can make three convincing arguments why candidate A should be strongly preferred. First, given equally strong recommendation letters, the one from an established HHMI investigator from an Ivy League school should carry more weight than the one from a junior faculty in a state school. Second, two Nature papers will increase the chances of publishing further Nature papers and securing grants. Finally, and perhaps most importantly, being part of an influential clique (alumnus of well-established labs in Ivy League schools) is in itself probably the best predictor of future publishing high-profile papers and securing funding. In short, candidate A objectively has higher chances of running a successful lab than candidate B, despite absence of substantive advantage in ability. One of my senior colleagues called this situation taking an A train versus taking a B train.
In reality differences among candidates are, of course, not as clear-cut. But the train-factor is very real. (I personally know of several train B riders who were superb scientists but failed to get an academic job.) The earlier in your career you realize this and switch to the A train, the better. In other words, if you want to succeed in today’s climate in science, it’s not enough to be good or even brilliant. You have to be strategic. If you go to an Ivy League school as an undergrad, you are on a good track. If you do your PhD in a productive lab, get proper guidance, and get into the right network, you are on a good track. Postdoc is your last chance to switch trains, and here you really have to be strategic. My friend and colleague Pleuni Pennings gives some advice here on how to choose your postdoc, and I agree with all of them. I would strongly emphasize joining a lab of a productive senior PI who has a good track record of his postdocs landing in professor jobs, because this is the best predictor of your own success.
Where does this leave us with respect to science in general? I think everybody is in agreement now that the trends and perspectives are not rosy. Roughly speaking, the motivations of scientists have shifted from trying to understand Nature to trying to publish in Nature. The old way to do science was to pursue the question that you are passionate about, do what you have to do in a lab that is best equipped to do it. Stuff may fail or may take longer than expected – after all research is unpredictable. But something good will come out of it if you are a good careful scientist. You may not win the Nobel, but you’ll be okay. These times are gone. Thorough careful science is not really rewarded today (for example, two of the B train riders that I know have the highest standards of science that I know). Today, as a postdoc, you have two, maybe three, years to complete a major project that results in a Nature paper. If it fails or takes too long, you are screwed. The new way to do science is to do the “hot stuff” (whatever it currently is) in a powerful lab which publishes all results in Nature and Science, no matter how important. How this will affect future progress is unclear, but some trends in areas of research that have practical applications, such as in drug discovery, are certainly worrying (see here, here, and here).