Good Mentoring

July 1, 2021

One of the recurring discussions / rants in academic circles is the crediting of good mentoring to the Professor. I’m not going to tag the stimulus of the day because it generalizes and because I have no idea what motivates any particular person on any particular day.

There does seem to be a common theme. A Professor, usually female and usually more-junior, is upset that her considerable efforts to mentor students or postdocs does not seem to get as much credit as they should. This is typically contextualized by oblique or specific reference that some other professors do not put in the effort to “mentor” their trainees as well and this is not penalized. Furthermore, there is usually some recognition that a Professor’s time is limited and that the shoddiness of the mentoring of those other peers lets them work on what “really counts”, i.e., papers and grants, to an advantage over the self-identified good mentor.

Still with me?

There is a further contribution of an accusation, implicit or explicit, that those other peer Professors are not just advantaged by not spending time on “mentoring” but also advantaged by doing anti-mentoring bad things to their trainees to drive them to high scientific/academic output which further advantages the bad mentor colleagues against our intrepid hero Good Mentor.

Over on Twitter I’ve been pursuing one of my usual conundrums as I try to understand the nature of any possible fixes we might put in place with regard to “good” and “bad” academic mentoring, i.e., the role of career outcome in influencing how the mentee and evaluating bodies might view the quality of mentoring practices. My point is that I’ve seen a lot of situations where the same PI is viewed as providing both a terrible and a good-to-excellent mentoring environment by different trainees. And the views often align with whether the trainee is satisfied or dissatisfied with their career outcomes, and align less well with any particular behaviors of the PI.

Here, I want to take up the nature of tradeoffs any given Professor might have, in the context of trying to mentor more than one academic trainee, yes concurrently, but also in series.

My assertion is that “good mentoring” takes time, it takes the expenditure of grant and other funds and it takes the expenditure of social capital, in the sense of opportunities. In the case of most of the Professoriate, these are all limited resources.

Let us suppose we have two graduate students nearing completion, in candidacy and up against a program requirement for, e.g., three published papers. Getting to the three published papers, assuming all else equal between the two trainees, can be greatly affected by PI throw down. Provision of assistance with drafting the manuscript, versus terse, delayed “markup” activities? Insisting the paper needs to get into a certain high JIF journal, versus a strategy of hitting solid society journals. Putting research dollars into the resources, capital or personnel, that are going to speed progress to the end, versus expecting the trainee to just put in more hours themselves.

A PI should be “fair”, right? Treat everyone exactly the same, right? Well…it is never that simple. Research programs have a tendency not to go to plan. Projects can appear to level themselves up or down after each experiment. Peer review demands vary *tremendously* and not only by journal JIF.

Let us suppose we have two postdocs nearing a push for an Assistant Professor job. This is where the opportunities can come into play. Suggesting a fill-in for a conference presentation. Proposing conference symposia and deciding which trainee’s story to include. Choosing which project to talk about when the PI is herself invited. Pushing collaborations. Manuscript review participation with a note to the Associate Editor. Sure, it could be “fair”. But this is a game of competitive excellence and tiny incremental improvements to the odds of landing a faculty position. Is it “good mentoring” if taking a Harrison Bergeron approach means you never seem to land any postdocs from the laboratory in the plummiest of positions? When a focal throwdown on one would mean they have a good chance but divide-and-conquer fails to advance anyone?

More importantly, the PIs themselves have demands on their own careers. “Aha”, you cry, “this selfishness is what I’m ON about.”. Well yes…..but how good is the mentoring if the PI doesn’t get tenure while the grad student is in year 3? Personal experience on that one, folks. “not good” is the answer. Perhaps more subtly, how is the mentoring going to be for the next grad student who enters the laboratory when the PI has generated “fair” publishing prior trainees but not the glamourous publications needed to land that next grant? How much better is it for a postdoc entering the job market when the PI has already placed several Assistant Professors before them?

Or, less catastrophically, what if the PI has expended all of the grant money on the prior student’s projects which the student constructed and just happens to be highly expensive (“my mentor supports my research (1-5”))? Is that good mentoring? Well yeah, for the lucky trainee but it isn’t fair in a serial sense, is it?

Another common theme in the “good mentor” debate is extending “freedom” to the trainee. Freedom to work on “their ideas”. This is a tough one. A PI’s best advice on how to successfully advance the science career is going to be colored in may cases by practicality of making reasonable and predictable forward progress. I recently remarked that the primary goal of a thesis-proposal committee is to say “gee that’s nice, now pick one quarter of what you’ve proposed and do that for your dissertation/defense“. Free range scientists often have much, much larger ideas than can fit into a single unit of productivity. This is going to almost inevitably mean the PI is reining in the “freedom” of the trainee. Also see: finite resources of the laboratory. Another common PI mentoring pinch point on “freedom” has to do with getting manuscripts actually published. The PI has tremendous experience in what it takes to get a paper into a particular journals. They may feel it necessary to push the trainee to do / not do specific experiments that will assist with this. They may feel it necessary to edit the hell out of the trainees’ soaring rhetoric which goes on for three times the length of the usual Intro or Discussion material. …..this does come at a cost to creativity and novelty.

If the “freedom” pays off, without undue cost to the trainee or PI or other lab members…fantastic! “Good mentoring!”

If that “freedom” does not pay off- grad student without a defendable project or publishable data, significant expenditure of laboratory resources wasted for no return – well this is “Bad mentoring!”

Different outcome means the quality of the same behaviors on the part of the PI is evaluated as polar opposites.

Asked and Answered

June 2, 2021

A tweet in response to a question I asked

said that perhaps a grad student’s job is to learn to answer questions and a postdoc’s job is to learn to ask questions.

I thought about that for half a second and concluded that this is backwards, for me. I think that I started into grad school thinking I knew how to ask scientific questions. I then spent the entirety of my time in grad school, right up until my committee signed off on my dissertation, learning the hard way that this was not so. I concluded that the main part of my graduate school training was learning how (not) to ask scientifically tractable questions.

In my postdoctoral training, I think that I learned how to answer questions. Not in the limited sense of “conduct this experiment, analyze the data and conclude a result”. Answering a question in the much broader sense of deploying available resources to address a scientifically tractable question and to bring this to an “answer” that was publishable in the scientific record.

I believe my career as a PI simply extends upon this, in the sense that my job is to secure the available resources in a broader sense and that “tractable” now includes the ability to direct the hands of more people. And the questions may no longer be my questions, but rather the questions of those who are in my laboratory. But it’s all just answering questions.

A quick google search turns up this definition of prescriptive: “relating to the imposition or enforcement of a rule or method.” Another one brings up this definition, and refinement, for descriptive: “describing or classifying in an objective and nonjudgmental way….. describing accents, forms, structures, and usage without making value judgments.

We have tread this duality a time or two on this blog. Back in the salad days of science blogging, it led to many a blog war.

In our typical fights, I or PP would offer comments describing the state of the grant-funded, academic biomedical science career as we see it. This would usually be in the course of offering what we saw as some of the best strategies and approaches for the individual who is operating within this professional sphere. Right now, as is, as it is found. Etc. For them to succeed.

Inevitably, despite all evidence, someone would come along and get all red about such comments as if we were prescribing, instead of describing, whatever specific or general reality we were describing.

Pick your issue. I don’t like writing a million grants to get the barest hope of winning one. I think this is a stupid way for the NIH to behave and a huge waste of time and taxpayer resources. So when I tell jr and not so jr faculty to submit a ton of grants this is not an endorsement of the NIH system as I see it. It is advice to help the individual to succeed despite the problems with the system. I tee off on Glam all the time….but would never tell a new PI not to seek JIF points wherever possible. There are many things I say about how NIH grant review should go, that might seem to contrast with my actual reviewer behavior for anyone who has been on study section with YHN. (For those who are wondering, this has mostly to do with my overarching belief that NIH grant review should be fair. Even if one objects to some of the structural aspects of review, one should not blow it all up at the expense of the applications that are in front of a given reviewer.) The fact that I bang on about first and senior authorship strategy for respective career stages doesn’t mean that I believe that chronic middle-author contributions shouldn’t be better recognized.

I can walk and chew gum.

Twitter has erupted in the past few days. There are many who are very angered by a piece published in Nature Communications by AlShebli et al which can be summarized by this sentence in the Abstract “We also find that increasing the proportion of female mentors is associated not only with a reduction in post-mentorship impact of female protégés, but also a reduction in the gain of female mentors.” This was recently followed, in grand old rump sniffing (demi)Glam Mag tradition by an article by Sterling et al. in PNAS. The key Abstract sentence for this one was “we find women earn less than men, net of human capital factors like engineering degree and grade point average, and that the influence of gender on starting salaries is associated with self-efficacy“. In context, “self-efficacy” means “self-confidence“.

For the most part, these articles are descriptive. The authors of the first analyze citation metrics, i.e. “We analyze 215 million scientists and 222 million papers taken from the Microsoft Academic Graph (MAG) dataset42, which contains detailed records of scientific publications and their citation network”. The authors of the second conducted a survey investigation: “To assess individual beliefs about one’s technical ability we measure ESE, a five-item validated measure on a five-point scale (0 = “not confident” to 4 = “extremely confident,” alpha = 0.87; SI Appendix, section S1). Participants were asked, “How confident are you in your ability to do each of the following at this time?”:”

Quite naturally, the problem comes in where the descriptive is blurred with the prescriptive. First, because it can appear as if any suggestion of optimized behavior within the constraints of the reality that is being described, is in fact a defense of that reality. Intentional or unintentional. Second, because prescribing a course of action that accords with the reality that is being described, almost inevitably contributes to perpetuation of the system that is being described. Each of thse articles is a mixed bag, of course. A key sentence or two can be all the evidence that is needed to launch a thousand outraged tweets. I once famously described the NSF (in contrast to the NIH) as being a grant funding system designed for amateur scientists. You can imagine how many people failed to note the “designed for” and accused me of calling what I saw as the victims of this old fashioned, un-updated approach “amateurs”. It did not go well then.

The first set of authors’ suggestions are being interpreted as saying that nobody should train with female PIs because it will be terrible for their careers, broadly writ. The war against the second set of authors is just getting fully engaged, but I suspect it will fall mostly along the lines of the descriptive being conflated with the prescriptive, i.e., that it is okay to screw over the less-overconfident person.

You will see these issues being argued and conflated and parsed in the Twitter storm. As you are well aware, Dear Reader, I believe such imprecise and loaded and miscommunicated and angry discussion is the key to working through all of the issues. People do some of their best work when they are mad as all get out.


We’ve been through these arguments before. Frequently, in my recollection. And I would say that the most angry disputes come around because of people who are not so good at distinguishing the prescriptive from the descriptive. And who are very, very keen to first kill the messenger.

A certain someone has taken it upon himself to lampoon certain types of solicitations issued by a lab head for postdocs and occasionally for graduate students, when they appear on Twitter. The triggering material included in such solicitations are terms such as “independent”, “energetic”, “brilliant”, “highly motivated”, “creative” and the like. Sometimes the trigger for this certain someone is merely a comment that the applicant should be experienced in some particular scientific technique. Seemingly inoffensive and very traditional, right? I mean, every lab head wants the lab to be as successful as possible and that means that they want good rather than bad employees.


Whoops. But we’re talking about trainees, right? Graduate students and postdoctoral trainees.

They are supposed to be getting something from the lab, not the other way around. Correct? So this over emphasis on how the PI only wants to hire the most talented, rather than the most needy, individuals pulls back the curtain to reveal the seamy truth.

“Trainees” in biomedical science are in large part the workforce. Which is obtained for less money due to the “training” misdirection.


This is one that set me off recently, thanks to our beloved aforementioned trollerpants. Chit chat amongst the Professor class that they “need” a postdoc now. Or general announcements that they will be soon looking to “hire a graduate student” in their new appointment, whee! but…”need”.

And of course coupling this to the above focus on the very best, most motivated, well trained, energetic self-starting individuals?

The notion of actually competing for the best of the available postdocs raises an ugly head.

You will be entirely unsurprised that I couple all of this to my views on labor in academic research labs and, in particular, the way we go along deluding ourselves that we are not part of any sort of labor market. I couple this to my thinking about ways to make academic careers slightly less hellish on the factors which are usually rubbing points.

Thinking more about the labor aspects of what is now academic “training” lets us think, I believe, more creatively about making things better for all of us.

No, it does not magically invent more Professor jobs. It does not restore State level commitment of funds to public Universities and thereby relieve the pressure for extramural funds. It does not make the NIH budget double overnight and therefore reduce pressure for the grant seekers.

But creating stable, long term job categories for those who are now some thin rebranding of “postdoc” could advance us. Creating stable career jobs to do the pure work part of the graduate student job could advance us.

Yes, this means we will “train” fewer graduate students and replace that labor with technicians. Who will be more or less expected to journey through their career as a career. Benefits. Increasing salaries with experience and longevity.

It’s gonna cost.

That brings me around to grant review. It always comes back to grant review.

One of the reasons NIH put the modular budget in place is to get reviewers to stop with the ticky tack over costs. Costs that vary all across the country from place to place. Costs that a certain species of reviewer just could not get through their head would vary. Costs that a certain species of reviewer delighted in using to spike a grant because those outrageous cage costs at Big U were higher than they were paying at their LessBig U.

And salary.

A certain species of reviewer is very concerned about salaries paid, if they can just get their beady little eyes on the information. A related species is very concerned about how many individuals are being paid off the grant, if they can just get their eyes on that information.

It is very hard to get their eyes on contributions by graduate students or postdocs who are on a fellowship or Program paid stipend. It is inevitably that they get their eyes on technician salaries when looking at an itemized budget.

I have recently received a grant review comment that clearly I was paying my technical staff too much, coupled with an obviously grudging admission that the person had long experience as a technician.

I have related more than once on these pages that over time I have generally relied more on tech labor than on the “trainee” scam. This, as our second President of the USA John Adams famously remarked about his refusal to use enslaved labor, costs me. It costs my grants and therefore I get less productivity per dollar compared with someone who is willing to fully exploit cut-rate labor under guise of “trainee” job categories. I do not turn my techs over willy-nilly every several years to reset salaries, either. And the way things work in these here United States, people get paid more over time. Those with more experience get paid more than those with less, even if the lesser experienced person could do the same job.

So when my peers who review my grants say that the merit of my proposal is diminished because I make these labor choices in my lab, and suggest that what I should be doing is exploiting the heck out of labor by using less experienced and cheaper techs…..

I get a little shouty. and bloggy.

For every reviewer who is dumb enough to actually write this in a critique, there are ten that are thinking it. They are taking a less positive cant on my proposal as a consequence. And possibly looking for other ways to express their disapproval.

I myself have occasionally fallen into to the “too many staff for the work described” review space. I’ve done it super rarely, so I think I’m probably on solid ground. The only cases I can recall were really, really egregious. But I need to watch myself, as do you. How often are you thinking that a major grant will receive the supplemental help of undergraduate “interns”? grand students or postdocs on “their own” fellowships? How many times have you questioned the role of a staff scientist when surely a postdoc would do?

The NIH has a nice COVID-19 related FAQ page up now, it’s worth keeping bookmarked.

One category of person in science who is under particular COVID-related stress is anyone who has NIH opportunities available to them that are time delimited.

For example, any postdoctoral trainees on NRSA support. There are constraints on total support time on fellowships like the F32/T32 NRSA awards which limit postdoctoral fellows to three years maximum. There’s a FAQ answer here and a link to more information. The latter is more general and says, importantly, that stipends can continue to be paid even if the trainee cannot work, due to COVID-related shutdowns. That is all well and but fails to address the concern about burning daylight doing nothing. The FAQ answer reads: Yes, as outlined in NOT-OD-20-086 recipients may extend awards affected by COVID-19 through a notification to the funding IC. For awards where such an extension impacts research progress, the IC will provide support and address any impact on the NIH-funded research. which is fairly imprecise. There is an even more focused FAQ entry which is answered as follows: “Yes. Recipients may submit extension requests to the funding IC for consideration when the effects of COVID-19 have altered the planned course of the research training/activities. Extension requests must include a description of how COVID-19 affected the NRSA and/or fellowship award, and clearly outline how much additional time is needed.  All such requests must be signed by the fellow, the Authorized Organization and the fellowship sponsor.

It’s all going to depend on what “the IC will provide support” means in the end. Will this be a with cost extension of the F32 for however many months the person cannot work due to COVID-related formal shutdown? That seems to be the intent of this last statement. Will they entertain longer intervals if the shutdown entails a loss of productivity far beyond the interval of formal University shutdown? This is likely to be true for the researcher and I’d say the NIH is very unlikely to take this broad approach. The “clearly outline how much additional time is needed” part is somewhat encouraging, however. My advice to the audience is to keep beating this drum as loudly and as frequently as possible on social media and what not. NIH has to understand that their role is to make people whole, not to chinz out on narrow technical “replacement” of time lost due to formal University shutdown timelines.

The T32 awards could be more flexible, I think. They run longer than the F32s and so there is the possibility there that NIH simply permits keeping a T32 fellow on past his or her 3 years if the T32 Director chooses to do so. I’m doubtful any additional funds will be provided so the T32 training faculty are going to have to think hard about how and whether they would use such flexibility, if offered. Could get sticky. But you never know, perhaps supplements could be provided. Otherwise it is not simple for the T32 Director and her core of training faculty. Renewal of the T32 is competitive and reviewers tend to bean count the number of trainees and how successfully they’ve been rotated off into other things. Locally speaking, will it be just the few people who are in their third year right now that get extra support? Well the ones in their second year are also burning daylight right now, and are going to feel slightly miffed about that.

Then we come to the K99/R00 (and the NIH intramural version the K22). The K99/R00 is designed to offer one or two years of postdoctoral support under the K99 mechanism, followed by three or four years of research grant support in the R00 phase. The first concern has to do with eligibility to apply, which is limited based on the time since the applicant’s doctoral award.

Applicants must have no more than 4 years of postdoctoral research experience at the time of the initial (new) or the subsequent resubmission application.

Ok, technically that is a running clock on postdoctoral employment so I suppose if you take time off after the PhD to do anything else, your clock is not expiring. But most applicants will be closely watching this eligibility. My stock advice (under normal circumstances) to any newish postdoc is to take a look at the last possible date for the “subsequent resubmission application” that comes in within the 4 year deadline and work back from that to where the first application must go in. Well, COVID-19 shutdowns are going to play havoc with this. Now the NIH has issued several notices stating flexibility in this timeline for various things, child bearing, elder care, etc. So this is probably a no-brainer even absent any specific COVID guidance. But the above mentioned FAQ specifically references this question. The answer is: “Yes, K99 applicants can request an extension to their K99 eligibility window due to the effects of COVID-19 on their research productivity. Affected applicants should consult with the funding IC for further guidance.” So far, so good. But still nerve-wracking, of course, because any given applicant can’t know for sure if he or she is going to be permitted the extension, or denied, by his or her target IC. They cannot know how much of an extension will be offered. One round? It may not be enough for full recovery of the person’s best possible proposal, including preliminary data.

Harkening back to yesterday’s post, this means that the very nervous K99 hopeful is going to be highly motivated to press ahead and stay on the schedule that she or he knows for a fact will be approved. I really wish NIH would find a way to be more definitive, such as saying the eligibility interval will just be a default 5 years for anyone who had 1-4 years experience as a postdoc as of March, 2020.

Now what about those lucky few who managed to land a K99/R00 award? There is a very nasty little problem for them, which is that the training phase is supposed to be no longer than 2 years and the R00 is supposed to start right afterwards. The R00, you will recall, requires that the person be hired in an Asst Professor job. So that has to be signed, sealed and almost delivered by the end of two years of K99 support. I’m sure I don’t have to remind this readership how hard it is for hopeful postdocs to land a job. And that many professorial jobs on offer follow the academic cycle of applications due in the fall semester, review in the early winter with interviews commencing soon thereafter. With luck, a candidate has things settled by April or May but this stuff can drag on, depending on…factors. In the Time of Corona, some Universities are putting a freeze on hiring, save for “essential” hires. How will this be interpreted for professorial hires? I don’t know. But I guaranfrickentee there are K99 holders sweating bullets about this right now. If the candidate is not lucky (in the ToC or just generally), they may have to wait an entire year for the job cycle to start up again. The text of the K99 is not very friendly about this.

The K99/R00 award will provide up to 5 years of support in two phases. The initial (K99) phase will provide support for up to 2 years of mentored postdoctoral research training and career development. The second (R00) phase will provide up to 3 years of independent research support, which is contingent on satisfactory progress during the K99 phase and an approved, independent, tenure-track (or equivalent) faculty position. The two award phases are intended to be continuous in time. Therefore, although exceptions may be possible in limited circumstances, R00 awards will generally only be made to those K99 PDs/PIs who accept independent, tenure-track (or equivalent) faculty positions by the end of the K99 award period.

Emphasis added. As I’ve tried to point out in many blog posts, almost everything at the NIH that appears to be a “rule” is negotiable. The phrase in this that exceptions “may be possible in limited circumstances….generally only be” is a perfect reflection of my understanding. I’ve heard of all kinds of exceptions being made to all kinds of stated rules. I’ve heard even more stories about people trying to get exceptions to one thing or another being totally stonewalled. It is hard not to confirm one’s bias about such anecdata that it seems like the insider club types get a lot more exceptions than us strugglers. And K99 holders pick up on this sort of uncertainty.

Me, I would say, talk to Program. But I actually have, about this exact scenario, and I got a sort of hard-line response. Of the “no way, no how they HAVE to get a job by the end of the first year”. I, being aware of at least one exception and the above text, tend to take this with a grain of salt. For one thing, I was asking as a PI. The PO might be keen on sending a brush back message to any PI who is angling to keep the K99 awardee in their lab as long as possible. The PO may also be trying to keep the fire lit under their K99 awardees to take job searching seriously. And with urgency. The PO doesn’t care a whit if their K99 people end up in a more [insert some aspect of the variety of academic jobs] job than that person would prefer in their heart of hearts. Perhaps that is all this person was trying to communicate, hoping to get their ICs K99s employed in anything that would vaguely permit them to do research. I don’t know what the intent was. But it was very clear that this PO was trying to be all hard ass about their particular IC’s viewpoints on K99 transition.

It’s stupid to me. Why not let the K99 take a year off of funding before starting her R00 if that is the way it has to be? Why force them to maybe take a job under less than ideal circumstances? Maybe there is a spousal hire situation that is complicating things? Maybe they just haven’t been able to land something really awesome that they maybe could with one more hiring cycle.

Anyway, particularly in the Time of Corona, I’d like to see NIH do this. They almost are. In response to this particular FAQ, they say: NIH is providing maximum flexibility and will accept these requests from recipients affected by COVID-19. Individuals and mentors should contact the funding IC in writing to provide details on the delays related to COVID-19.

WHHHYYYY????? Why do they have to say this in Bureaucratic Weaselish? Why can’t they just fricken say “The NIH will permit a one year unfunded interval between K99 completion and R00 initiation.”? Or even “The NIH will permit the recipient to choose three years of K99 time at the expense of only two R00 years (something about the extra budget rolling over).”?

It’s so frustrating. Good that they are addressing this. Good that in all liklihood the existing K99 awardees will be able to adapt their course to the ToC related circumstances. ….but for goodness sake, why do they always have to make this so uncertain and nervewracking for their awardees?

Career Jealousy

August 26, 2019

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.

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.


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.

Lab Size, take 3

May 17, 2019

I was struck by a couple of tweets. The first seems to find it worthy of remark that staff on a grant are expensive.

and the second seems to outline what appears normal for one grant proposal in the eyes of this tweeter.

One postdoc, three grad students, an unspecified part time for an undergrad and similarly unspecified time for a tech. Lets say part-time is half and “some hours” equals a quarter. But the specifics here don’t really matter because “my technician” gives us a pretty good clue when it comes to lab size.

I return to a question I have asked this audience before. What, in you view, is a standard, average lab size? What size do you think would be about right for yourself? What are the bounds? What size is too small for you really to feel like you have “a lab” going? What size is getting up there into “whoa, that’s a big lab” territory?

The follow up question is, once you have this ideal lab size in mind, how does it fit with your heartfelt beliefs about how NIH grant moneys should be distributed. This tweep came up with a number that is significantly above the full-modular NIH limit of $250,000 per year. It is a number that would require traditional budgeting and, in some ICs, might get cuts even larger than their default 10%. It is a number that would fit a lot more comfortably into two R01 scope grants…in terms of the budget.

Can you square your ideas of fair NIH grant award with your ideas on normal average nothing-special lab size?

A recent twitt cued a thought.

Don’t ask your staff for a meeting without giving an indication of what it is about.

“Hey, I need to see you” can be very anxiety provoking.

“Come see me about the upcoming meeting Abstracts deadline” is not that hard to do.

“We need to talk about the way we’re doing this experiment” is duck soup.

Try to remember this when summoning your techs or trainees.

As mentioned in Science, a new report from the US Academies of Sciences, Engineering, and Medicine have deduced we have a problem with too many PhDs and not enough of the jobs that they want.

The report responds to many years of warning signs that the U.S. biomedical enterprise may be calcifying in ways that create barriers for the incoming generation of researchers. One of the biggest challenges is the gulf between the growing number of young scientists who are qualified for and interested in becoming academic researchers and the limited number of tenure-track research positions available. Many new Ph.D.s spend long periods in postdoctoral positions with low salaries, inadequate training, and little opportunity for independent research. Many postdocs pursue training experiences expecting that they will later secure an academic position, rather than pursuing a training experience that helps them compete for the range of independent careers available outside of academia, where the majority will be employed. As of 2016, for those researchers who do transition into independent research positions, the average age for securing their first major NIH independent grant is 43 years old, compared to 36 years old in 1980.

No mention (in the executive summary / PR blurb) that the age of first R01 has been essentially unchanged for a decade despite the NIH ESI policy and the invention of the K99 which is limited by years-since-PhD.

No mention of the reason that we have so many postdocs, which is the uncontrolled production of ever more PhDs.

On to the actionable bullet points that interest me.

Work with the National Institutes of Health to increase the number of individuals in staff scientist positions to provide more stable, non-faculty research opportunities for the next generation of researchers. Individuals on a staff scientist track should receive a salary and benefits commensurate with their experience and responsibilities.

This is a recommendation for research institutions but we all need to think about this. The NCI launched the R50 mechanism in 2016 and they have 49 of them on the books at the moment. I had some thoughts on why this is a good idea here and here. The question now, especially for those in the know with cancer research, is whether this R50 is being used to gain stability and independence for the needy awardee or whether it is just further larding up the labs of Very Important Cancer PIs.

Expand existing awards or create new competitive awards for postdoctoral researchers to advance their own independent research and support professional development toward an independent research career. By July 1, 2023, there should be a fivefold increase in the number of individual research fellowship awards and career development awards for postdoctoral researchers granted by NIH.

As we know the number of NIH fellowships has remained relatively fixed relative to the huge escalation of “postdocs” funded on research grant mechanisms. We really don’t know the degree to which independent fellowships simply annoint the chosen (population wise) versus aid the most worthy and deserving candidates to stand out. Will quintupling the F32s magically make more faculty slots available? I tend to think not.

As we know, if you really want to grease the skids to faculty appointment the route is the K99/R00 or basically anything that means the prospective hire ” comes with money”. Work on that, NIH. Quintuple the K99s, not the F32s. And hand out more R03 or R21 or invent up some other R-mechanism that prospective faculty can apply for in place of “mentored” K awards. I just had this brainstorm. R-mechs (any really) that get some cutesy acronym (like B-START) and can be applied for by basically any non-faculty person from anywhere. Catch is, it works like the R00 part of the K99/R00. Only awarded upon successful competition for a faculty job and the offer of a competitive startup.

Ensure that the duration of all R01 research grants supporting early-stage investigators is no less than five years to enable the establishment of resilient independent research programs.

Sure. And invent up some “next award” special treatment for current ESI. and then a third-award one. and so on.

Or, you know, fix the problem for everyone which is that too many mouths at the trough have ruined the cakewalk that experienced investigators had during the eighties.

Phase in a cap – three years suggested – on salary support for all postdoctoral researchers funded by NIH research project grants (RPGs). The phase-in should occur only after NIH undertakes a robust pilot study of sufficient size and duration to assess the feasibility of this policy and provide opportunities to revise it. The pilot study should be coupled to action on the previous recommendation for an increase in individual awards.

This one got the newbie faculty all het up on the twitters.


being examples if you are interested.

They are, of course, upset about two things.

First, “the person like me”. Which of course is what drives all of our anger about this whole garbage fire of a career situation that has developed. You can call it survivor guilt, self-love, arrogance, whatever. But it is perfectly reasonable that we don’t like the Man doing things that mean people just like us would have washed out. So people who were not super stars in 3 years of postdoc’ing are mad.

Second, there’s a hint of “don’t stop the gravy train just as I passed your damn insurmountable hurdle”. If you are newb faculty and read this and get all angree and start telling me how terrible I am… need to sit down an introspect a bit, friend. I can wait.

New faculty are almost universally against my suggestion that we all need to do our part and stop training graduate students. Less universally, but still frequently, against the idea that they should start structuring their career plans for a technician-heavy, trainee-light arrangement. With permanent career employees that do not get changed out for new ones every 3-5 years like leased Priuses either.

Our last little stupid poll confirmed that everyone things 3-5 concurrent postdocs is just peachy for even the newest lab and gee whillikers where are they to come from?

This new report will go nowhere, just like all the previous ones that reach essentially the same conclusion and make similar recommendations. Because it is all about the

1) Mouths at the trough.
2) Available slops.

We continue to breed more mouths PHDs.

And the American taxpayers, via their duly appointed representatives in Congress, show no interest in radically increasing the budget for slops science.

And even if Congress trebled or quintupled the NIH budget, all evidence suggests we’d just to the same thing all over again. Mint more PhDs like crazee and wonder in another 10-15 years why careers still suck.

As you know I am not a super big fan of NIH grant review sentiments which boil down to “tut, tut, Dr. Junior Faculty, let’s not get too big for your britches. Try this small starter award and see how you do with that before you get to play with the big kids.”

I believe things like size of grant and number of grants (and relatedly, overall total direct costs) should be taken on a case by case basis. And I believe that modern “junior” faculty are pretty old, phenomenally broadly experienced and generally pretty capable compared to junior faculty minted in, say, the early to mid eighties.

The question of the day, however, has more to do with lab size and specifically to do with the number of academic trainees.

Is there a limit to the number of grad students, postdocs or grad students plus postdocs that most junior faculty should be training?

My gut take is “heck yes”. I don’t know that I’ve ever had to act up this. I can’t recall a time when I ever had to judge a R-mechanism or F-mechanism where the PI or supervisor (respectively) was seemingly overburdened with trainees. But my gut says that this is possible. There would be times where I might raise an eyebrow about how many concurrent trainees a junior (or senior, but that’s another argument) PI might be proposing to have. Whether that be due to taking a look at the “training environment” for a F32/F31 application or in looking at relative commitment levels for a new Rproposal there are seemingly times that this might come up. Conceivably.

My gut feeling on this is guided by my own experience which, as we know, is wildly out of touch with y’all.

We have had one or two conversations about what people think of as a small, medium or large lab. My takeaway from these is that people think a 6-7 person lab is average, medium, normal and basically expected value.

To me this is “on the larger side”.

I have run anywhere from 0-4 concurrent academic trainees and when I am at 4 postdocs I definitely feel a bit stretched.

I have been doing this gig for some time now. When I was a wee newbie PI I thought that two concurrent trainees was pretty much good. Three was not something that I thought was sustainable.

Whatcha think, Dear Reader?

Can most junior PIs handle 5 or more concurrent academic trainees? Should they just take as many as possible?

*I solemnly swear this is not a troll to further complain about the training of too many PhDs.

PI seeks postdoc

March 23, 2018

Every PI wants only the most brilliant, creative and motivated trainees that will put in insane levels of effort to advance the lab agenda.

We know this because it is how they write their postdoc solicitation blurbs.

This is not what is consistently available.

I know this because a consistent backchannel theme of my dubious life online as science careers nerd features PIs complaining about their trainees.

My usual response is to point out that they became PI due to being much better than average. So of course most of their trainees aren’t going to be as good as they are*.



Delay, delay, delay

March 20, 2018

I’m not in favor of policies that extend the training intervals. Pub requirements for grad students is a prime example. The “need” to do two 3-5 year postdocs to be competitive. These are mostly problems made by the Professortariat directly.

But NIH has slipped into this game. Postdocs “have” to get evidence of funding, with F32 NRSAs and above all else the K99 featuring as top plums.

Unsurprisingly the competition has become fierce for these awards. And as with R-mechs this turns into the traffic pattern queue of revision rounds. Eighteen months from first submission to award if you are lucky.

Then we have the occasional NIH Institute which adds additional delaying tactics. “Well, we might fund your training award next round, kid. Give it another six months of fingernail biting.

We had a recent case on the twttrs where a hugely promising young researcher gave up on this waiting game, took a job in home country only to get notice that the K99 would fund. Too late! We (MAGA) lost them.

I want NIH to adopt a “one and done” policy for all training mechanisms. If you get out-competed for one, move along to the next stage.

This will decrease the inhumane waiting game. It will hopefully open up other opportunities (transition to quasi-faculty positions that allow R-mech or foundation applications) faster. And overall speed progress through the stages, yes even to the realization that an alternate path is the right path.

Our good blog friend, occasional commenter and behind the scenes provoker of YHN’s blogging nearly on par with CPP, @superkash put up a twitt poll:

An extended discussion is going on and there are a few things of interest to me that are emerging.

What IS a “staff scientist”? Does it have a defined role? How is it used both formally by institutions and in less formal career-expectation space? How is it viewed by the hiring PI? How is it viewed by postdocs?

Is it, or should it be, a mere evolution of a postdoc after a certain interval of time (e.g., 5 years)?

Is it, or should it be, in part a job-job where a person is hired to do one sciencey thing (generate data from this assay)?

Is it, or should it be, a job where the person “merely” does as the PI instructs at all times?

Does it come with supervisory responsibilities? Is part of the deal to remove this person from ever having to consider grant-getting?

Is permanence of the job in a way that is not the case with postdocs an implied or explicit condition of the job title?

If the lab head tells the trainees or techs that a specific experimental outcome* must be generated by them, this is scientific misconduct.

If the lab head says a specific experimental outcome is necessary to publish the paper, this may be very close to misconduct or it may be completely aboveboard, depending on context. The best context to set is a constant mantra that any outcome teaches us more about reality and that is the real goal.

*no we are not talking about assay validation and similar technical development stuff.