Career Jealousy

As most of us will have experienced at one time or another, it is totally unfair that that person, over there, got this good thing that we did not get. They are, after all, no better or smarter than us, they were just lucky.

In the right place, at the right time. Anyone could have fallen into that luck. And we, ourselves, have not had such good fortune in our careers and of course that is unfair.

I have had my misfortunes in this career. I have also had several great bits of good fortune. I have most definitely felt the monster of jealousy hit for the observed good fortunes of other people that are my approximate peers at a given stage. In some cases I have felt that those folks, over there, are not just lucky but are super well-deserving. This is usually because I think they are brilliant and/or highly productive scientists, independent of the luck they enjoyed. In other cases I ground my teeth that such a dumbass incompetent lucked into that particular area of fortune while I, clearly more deserving, struggle.

I surmise, somewhat indirectly, that trainees these days are no different than I was. And they can be jealous of various things that seem to be falling into place for their peers, but not for them. It is, of course, amusing that their lucky peers often seem to be equally resentful of the luck of the person feeling sorry for themselves. It is a cycle.

As you know, Dear Reader, I am making an okay job of surviving in this career. So far, at least. It may crater any day, it may continue until I drop dead. But I’ve been doing this long enough to see a broad arc of what happens with people and their careers. And you know what? The distribution is an iron law of life.

Maybe this is just me, but I think the most profound effect that scientific training and participation has had on my mindset is that I think of just about everything in terms of distributions. In the distribution of career fortune, sure, there are going to be those that always get the sunny side of life. Surely a few people, just a few, have literally everything go their way. And conversely (and more sadly), some few people will have literally everything related to chance events fall against them. But the vast majority are in the middle. Where sometimes we get the good stuff happening and sometimes we get the bad stuff happening.

It’s only possible to see this in the career arc by living it for awhile.

At least one fellow graduate student that I thought achieved very, very high profile papers through no virtue of themselves, personally, ended up struggling just to earn the PhD and quickly exited science.

Postdocs that were much more productive in hotter fields than mine ended up out of science.

Then there are the faculty. Oh, yes, the faculty arcs. When I first started there were a fairly restricted number of individuals who I compared myself with. People in either approximately similar spheres of research or individuals in my own institution working under similar contingencies, albeit in strikingly different fields. Limiting myself to the first type, oh boy, you better believe I was slightly envious of the ones that seemed like shooting stars. Super productive or grant laden or just ones that seemed to enjoy better reputation as scientists. Some were viewed by me as highly deserving but one still gets a bit jealous, eh?

Well, shit happens. Maybe I had huge career and/or personal hurdles but eventually so did my peers. Because life happens. Some hurdles were run of the mill and some were truly life-changingly horrific. Some folks survived, some recovered and eventually thrived, and some said good-bye to academic science. Many folks just kind of faded away and I don’t know them well enough to know why. With some other folks it is clear that we only see part of the picture in public and there’s some weird shit going on somewhere. Not my circus, not my peanuts, but it is good to appreciate the impact of both good and bad circumstances even if you don’t quite know what they might be.

I keep learning about bullshit some peer or other had to put up with at various stages of his or her career. Even ones that seemed like they had it all. E.g., my previous institution was particularly uneven in terms of the insider club and the benefits they enjoyed relative to the rest of us. But eventually you realize there have been gradations of treatment within the ranks of the Annointed Ones. Within my fields of study, there are peers that seem like they were in the right research groups/departments/collaborations at the right time..but it turns out that in reality they were in a living hell.

Much of this information about other people’s careers has come to me long after I’ve made peace with my notion of the distribution of fortune. So I mostly just feel sorry for them and I lament the effect on their careers almost as much as I resent the effects of ill fortune on my own.

But I don’t know what to tell trainees. I just do this grampa thing of relating the anecdotes akin to the ones above and telling them the pendulum swings back and forth. Their peers who seem to be riding high will eventually be hit by misfortune. And any one thinking they themselves lack “luck” will eventually look back and admit some good fortune came their way. I’m sure it doesn’t help much.

Is it 8 pieces of advice? or just 1- PUBLISH!!!!

A career column in Nature by one Bela Z. Schmidt ponders his path in science and why he did not achieve a tenure track position. He presents this as a self-review colored heavily by interviews with “50 PIs” and concludes that there are eight factors that matter: Accept your data, Own your project, View yourself in your desired role, Ward off despair, Maximize your time, Outline your goals, Trust your intuition and Finish.

Before I get into this, I will remind you that there is a heavy dose of chance and fortune that dictates one’s career path in academic science. There are factors outside of your control, and factors that you don’t really see how important they are until it is far too late. But there are also factors that are within your control and this piece purports to address those, by way of these eight factors and related advice. Personally I tend to address this conundrum by the old saw about Fortune favoring the prepared, usually attributed to Louis Pasteur.

Yes, the good and bad luck can be career changing. Despite what we would prefer, success in academic science is not some sort of dispassionate, detached meritocracy of how deserving anyone is based on how much, or what, they have accomplished.

However.

This particular columnist reveals that he started applying for tenure track jobs after 12 years spent in “several” postdoctoral positions. This work had resulted in 12 peer reviewed publications of which 5 were first-author. Two chapters and 10 “published meeting abstracts” were also mentioned- this is an area where I am uncertain about meaning since some fields view these more highly. Nevertheless, the career search outcome gives us a clue. Over three years 57 academic applications produced 4 interviews (some phone), and 22 biotech/pharm and 25 government agency agency jobs produced no interviews.

From my perspective, five first author papers in 12 years of post-doc training is not enough, unless they are Cell papers.

Reading through the eight pieces of advice, we can distill a similar conclusion. Under Finish, Schmidt reiterates the maxim that finished is better than perfect. This dovetails with his comment under Accept your data that he was a “meticulous experimenter” and spent too much time looking for alternative explanations. It also harmonizes with advice under Maximize your time, which emphasizes the passage of time and being productive and Own your project where he laments not following his nose on some promising preliminary results and suggests it would have made a “promising publication”.

You have to produce. It isn’t just the prepared mind that Fortune favors. It is the prepared CV, the prepared resume and the prepared recommendations from peer scientists that Fortune favors. And if anything is under the approximate control of the postdoctoral scientist, or should be, it is scientific productivity. By this point, you should have read hundreds if not thousands of papers in your fields of study. You should have a very good sense of what is needed to support publication in various venues. You should have enough experimental chops to know how to get to a publication. If you feel shaky on exactly how to do this when fresh out of graduate school, and most are, the whole point of the initial postdoctoral years is to learn this part of the career.

Sure, some PIs are going to be a hurdle instead of an accelerator to your need to produce peer reviewed scientific publications. Fields differ in expectations along the path of frequency over depth/breadth and on journal reputation or metrics like the JIF. Yes. Your job as a post-PhD scientist is to learn how to navigate these hazards and produce published work. That’s the gig.

You have to be able to close.

I want to return here to the second theme in the eight pieces of advice because it gets into very touchy territory. This also echoes something that has been drifting about on sciTwitter lately under the usual hot button topic of how much you should be working and not complaining about it when you are a trainee. The optimism of giving eight pieces of advice on how to be a PI (and writing a blog focused on academic science careers for well over a decade, let’s face it) has a bit of an assumption that most people with PhDs deserve to be Principal Investigators running their own show. In a tenure track position or similar supervisory role within a government institute/agency or in private biotech or pharmaceutical industries. Or maybe if the term “deserve” is too loaded, perhaps we may say that they would be successful, if only given the chance.

Under View yourself in your desired role, Schmidt quotes one of his interviewees saying “I have always been a PI — in somebody else’s lab.” This works together with Outline your goals in the sense of having a plan to become a PI. But…what if you don’t view yourself as a PI or have any specific things that you want to do in science that require you to be a PI? I was a career doofus for many years and it hurt me. But I knew since early in graduate school that the kinds of questions I wanted to answer required me to direct the scientific effort of others. Explicitly. I knew that I was not going to be happy just with the data I could generate with my own two hands. This must inevitably have pushed me to pay a little bit of attention to the hows and whys of the career as I went forward. No matter how dim the prospects of independence looked at any point in my training. In Ward off despair Schmidt touches heavily on the self-confidence to believe in your science as an echo of themes in Own your project and in Trust your intuition. Just bull ahead, these comments say, you do you and everything will be fine. Don’t sweat the small stuff. Don’t let doubt get in your way- take risks on half-baked scientific ideas! (N.b., I’ve been letting some nutty ideas that fall far short of “half-baked” take up far too much time and effort in the lab lately- It’s fun, dammit.)

My hesitation with this set of themes as mentoring advice is that it sounds a lot more like selection criteria than it does like general advice. (This is somewhat related to advice to not let negative reviews of your work prevent you from resubmitting the paper, revising and resubmitting the grant or whatever else it takes to persevere.) And this is uncomfortable.

Science is replete with people who have personal stories of someone telling them they weren’t cut out for this stuff and yet here they are as a seasoned PI with a zillion citations of their published work to their credit. Many of us know people who we think should have been similarly accomplished, but they just fell off the path at some point. And many of us may have our little ideas about who, or what kind of person, is cut out for this business. Some of us are dumb enough to bray it about in public or tell specific people they don’t have what it takes. We’re often wrong, see first sentence of the paragraph. We are often wrong because of the limitations of our own experiences. We are often wrong because of our implicit or explicit biases. This is why the smarter people realize their predictions about who is suited to be a PI are not very strong ones and keep it to themselves. Or at least keep it to a limited conversation with their partner or closest peers.

Or blog it. 🙂

I’m pretty clear that I think that in order to set yourself up the best to be a PI one day, or to run a group in the private sector, you have to be able to produce peer-reviewed papers of a type and at a rate that is within the expectations for your subfield and desired future job type, while you are a postdoc. This productivity can be by various routes, and it is. Some of you are in well-oiled machine labs where the pubs are going to come almost despite you. Others will be in places where it is hard slogging with the whole shebang entirely on your shoulders. Still others will have to fight a zero-sum cage match for first author slots in Glam articles. I get that circumstances vary. But the advantages of a record of publication productivity do not vary that much.

Postdocs are expected to produce papers. Job applicants for professor gigs or for independent positions in government science (and even in industry) are expected to have produced papers…even if this isn’t a major job expectation going forward!

Obviously we can’t know exactly what jobs Schmidt applied for in the biotech and pharmaceutical industries. And we don’t know how well his skills fit those jobs. But I will make the leap of assuming that at least part of the issue leading to zero interviews in that sector was his lean publication output.

Another personal belief is that someone hiring you is concerned that you were a success in whatever you were doing before. It doesn’t matter how related or unrelated it may be to the job opportunity, they can’t help but be biased to think that if there is something unproductive about your past, maybe it is because you were bad at your job and you will be bad at this new job. And, conversely, if you were a success in a prior job, you are probably going to be a success in your next job. And when an academic postdoc has been at it 12-15 years across multiple labs, one starts to assume it is him and not the vagaries of Fortune.

Which cycles us right back to the discussion of intrinsic traits versus following the right career advice. As I said, many of this Op-Ed’s eight pieces of advice come back to point at publication record. The other ones boil down to a sort of career personality type.

Can you change your own behavior because you realize it is rapidly closing off your future possibilities? I have to be honest, I got one big boot in my career behind at an earlier stage and it changed my behavior significantly. But I still could be a lot more productive when it comes to papers coming out of my laboratory. I know this. And it doesn’t seem to help me get better.

Can you, as a mentor, train your postdocs to alter their behavior? We’ve seen how poorly it goes over to write op-eds complaining about empty science labs on the weekend. We’ve seen various pile-ons when any poor PI on twitter dares suggest maybe postdocs should work harder. We realize implicitly that every postdoc on twitter is amazingly hard working and is only held back by that terrible mentor they have who won’t return nearly finished paper drafts to them in a timely fashion. But….mentors gonna mentor. And it is very difficult to escape the bias that what we believe worked for us should work for our trainees. So we tell them that they gotta produce.

Is it less terrible to tell people that, in your best estimation, they are not cut out for an eventual position as an independent scientist? Many, many postdocs who do produce a lot of scientific papers will not be fortunate enough to land their dream job as an independent lab head. Is it a fool’s errand, or worse a tool of exploitation, to encourage postdocs to produce more and more papers? Is it more effective to observe that if you don’t feel like a PI temporarily shackled to your PI’s lab, or if you don’t have a driving need to get data from 7 (+/-2) people on your desk every week, or if you don’t have a half-dozen side project cooking at all times…that you aren’t he right person for this racket?

I have questions.