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I am likewise a staff scientist by choice. I'm confident that I have abilities and track record that would allow me to start my own lab if I wanted to, but I value being able to do science instead of writing grants full time. Our current system excels at taking bright scientific minds and turning them into middle managers.

Yeah. Although it is annoying that we both have to clarify "well, I could be a PI if I wanted to", because of this social norm that if you aren't a PI by the appropriate age, it means you weren't good enough. Because, obviously, everyone wants to be a middle manager. And we aren't talking to an academic crowd here, but a lot of academics would be skeptical when we say that.

If enough people in our generation take this approach, I think it will be very good for science. It is a happy medium between the old system of "everyone gets tenure eventually" and "no-job-security eternal postdoc" of the last few decades.

Science is inherently risky enough without also forcing everyone to essentially become an entrepreneur. That phenomenon is likely behind so much of the exaggerated findings that are getting published.

I think it's also important to recognize that hiring a staff scientist means that that the PI is further entrenching themselves in middle management. You need to write more grants in order to fund a staff scientist and give them the job security they expect.

Most PIs I know would prefer to spend more time in their lab.

"Hire me to do the things you wish you were doing, and in the process damn yourself not to be able to do them" is a steep ask for a lot of labs, especially small ones.

I thought the same thing -- given the choice, most PIs would just as soon hire a full-time "staff grant writer" and return to science themselves. Of course, you can't actually pay for such a position using government grants, and therein lies the rub.

If we're talking about unicorns, a competent "staff grant writer" has to be the rarest of them all. To write a grant well, you have to deeply understand the specific science at hand and be a good writer. Someone who would voluntarily choose such a job would also be someone who enjoys the process of writing.

So, in other words, someone perfectly suited to be a PI, a more prestigious and better-paying position with more freedom.

Our institution has one you can ask to help write/review/correct grants. They are pretty useless because they cannot possibly understand the science each individual lab is engaged in at an adequate level. Usually they just offer superficial suggestions/corrections.

I think I've met one person with a dedicated lab grant writer and yeah, I'm pretty sure the PI would take a bullet for them.

Yeah, if I had the money just swimming around, a grant writer or dedicated programmer would likely be higher on the list for me than someone to do work I'd rather be doing myself.

I thought it would be this way too. But I do actually try to help out with funding as much as I can.

Ultimately, though, I'm afraid I can't summon too much sympathy for a PI who thinks this way, because they knew exactly what they were getting into when they accepted that promotion. It is common knowledge that the tradeoff you make upon becoming PI is that you get the authority to direct the research aims while sacrificing the ability to do them yourself.

Exaggerating somewhat, a PI gets 100% of the intellectual freedom and responsibility, and has 0% of the fun. A grad student or postdoc gets 0% and 100%. I was looking for something like 50%/50%.

That is indeed the tradeoff - but the problem is your exaggerated example masks the actual problem.

Right now, rather than being at 100/0, I'm actually at something like 100/50.

Hiring a staff scientist will send me towards 100/0. Which means not only do I have to think "Can I afford you?" but "Do I want to afford you?"

Hmm, I can see how you got there, but I don't think it has worked out that way in my case.

The amount of time you have to spend writing grants is a function of: 1) how much money you are burning, 2) how much help do you have writing, and 3) how good is your science (better science will be more successful).

No doubt I hurt on #1. But I think I help enough on #2 and #3 to compensate, and therefore I don't think my PI spends a net larger percentage of time writing with me than he would without me. Anecdotally, over my time with him, I think has been a slow decrease in the fraction of his time he spends writing.

I think the issue is the cost of #1 is non-linear.

I think there's a space where yes, your impact on #1 is probably offset by gains in #2 and #3. But there's also a space, where I'm at right now (and I suspect many new investigators are) where your impact on #1 either moves a staff scientist outside the realm of possibility, or simply dramatically increases the likelihood of stochastic funding failure unless you're literally god's gift to the research world.

It takes a smart PI, but it also takes a well funded PI. I actually know relatively few PIs who wouldn't trade a postdocs/grad student or three for a good senior scientist. Thing is, because of the way things like training grants are structured (higher tier universities), and because in the worst case a grad student can support themselves by teaching (poorer disciplines/lower tier universities), senior scientists are far more expensive than the grad student or the postdoc (who is often expected to get his/her own grants). You can't get more of them without reforming how science is funded.

This. Having worked in a lab with a strong staff science presence, I know their value and what they bring to the table. I'd absolutely love one.

In the meantime, I'm shaking the couch cushions to be able to support more than one student.

You want 3X what a grad student makes makes? That makes you almost as expensive as me, and I'm the PI. I don't say that out of arrogance - I say that because that means I now have to pay for both of us while you go do science. In a grant, you're actually more expensive, because some of my salary is covered by the state/teaching/etc. while you're a pure soft money hire.

That's also ~45% of a non-modular NIH R01's yearly budget once you include benefits. Which means I'd be frantically writing grants with ~10% pay lines (being optimistic - the effective pay line for a PI under 40 is laughable) just to keep your paycheck coming. Because I can't fund you via a training grant, or an RA/TA line.

Keeping you employed for three years would consume my entire startup package. No travel, no data acquisition, no lab equipment...just you.

I'd like to be able to do all that. I'd also like a unicorn.

The reason this was easily possible in my case is because of the peculiarities of bioinformatics. Namely, equipment costs are low, so there is more money for staff per grant dollar.

We also have had much more luck with center and collaborative grants than R01-style individual grants. On collaborative grants, our sections are almost always the highest scored, on top of the fact that the pay lines are inherently higher. On individual grants, it is hit-or-miss to say the least, because reviewers seem to think, somewhat rightly, "why do you need $1M to play on computers?".

People come to us and say, "hey, I want to put you in as a small section for $75K, $100K, or whatever". Over the course of time it has meant we have a diverse and relatively stable revenue stream and low overhead, and there is less risk (because less time spent) on each individual grant. Although amusingly, my PI is still associate despite pulling in way more money overall than many fulls, because of this idea that only PI grants count for promotion.

> I say that because that means I now have to pay for both of us while you go do science.

Yeah, although I said in my OP that "I just want to do science", in reality I write parts of grants, mostly the technical parts, all the time, and I go to grant strategy meetings, where I feel my input is valued as I can often give a better idea of what's feasible than the PIs can. I guess more precisely, I don't want the responsibility and pressure of being in charge of the whole package, and I don't like dealing with all the paperwork. So in our case the funding is a team effort as well.

> way things like training grants are structured

I have been with him since grad school. In the early days, the way we got around this was titling me as a postdoc and paying me like a staff scientist, which was fine by me.

> The reason this was easily possible in my case is because of the peculiarities of bioinformatics. Namely, equipment costs are low, so there is more money for staff per grant dollar.

Ironically, I'm in just such a field as well. But that also causes another bit of pressure, because it does mean that I could stop sooner and go back to science if I wanted to fund less people. Covering myself and a grad student can be done with a few bits and pieces of funding. As I noted in the back of napkin calculation, a staff scientist vastly increases the amount of money I need to find.

> Yeah, although I said in my OP that "I just want to do science", in reality I write parts of grants, mostly the technical parts, all the time, and I go to grant strategy meetings, where I feel my input is valued as I can often give a better idea of what's feasible than the PIs can. I guess more precisely, I don't want the responsibility and pressure of being in charge of the whole package, and I don't like dealing with all the paperwork. So in our case the funding is a team effort as well.

In fairness, I reacted to this because I have met some people who meant it seriously - they want to be left alone in a lab to answer their questions while someone else keeps the lights on. And well...yeah...you just described the perfect job.

> I have been with him since grad school. In the early days, the way we got around this was titling me as a postdoc and paying me like a staff scientist, which was fine by me.

And this hasn't backfired by having one of his "postdocs" not progressing very fast?

> they want to be left alone in a lab to answer their questions while someone else keeps the lights on. And well...yeah...you just described the perfect job.

Well, that IS what I want, probably what everyone wants. I don't like writing grants, as I said, but I am in touch with reality and consider it an important part of my value proposition. Plus, I like my PI and consider him my friend. It's not nice to leave all the shit work for your friend.

EDIT: In many ways, I have tried to alter my behavior to prevent exactly the kinds of problem you are talking about. I absolutely want my PI to feel like my presence is a net benefit. If a staff scientist didn't understand these realities, they could easily be both naive and unhelpful.

> And this hasn't backfired by having one of his "postdocs" not progressing very fast?

Interesting point, one I hadn't considered. We are a pretty small lab, 4 grad students, 1 postdoc, occasional summer/rotation/temp postdocs or students, and me. In the past we had 2 postdocs.

The 1 postdoc who is in the lab now is a statistician who has zero interest in his career or ever being a PI. He is extremely valuable but I don't get the impression he feels held back. He is a "give me a job and I'll do it" type.

For informatics, I believe the productivity multiplier for skill is higher than in wet lab. Thus, it is not only easier but potentially better to have a small lab with high skill than the converse. So we have little interest in rapid growth.

I, too, wanted a Unicorn Job of this sort: http://pgbovine.net/unicorn-jobs.htm

After some trial and error bouncing around in industry/postdoc/etc., I've found that being a PI in a field where I have to raise relatively small amounts of money (compared to Big Science labs) to be the best balance for me at this point. I agree with Fomite that unless I magically get amazing at grant-writing, there's no way that I could afford to sustain full-time staff ... I don't envision myself going down this path since I want to minimize time spent writing grants and maximize my research/teaching/service time.

The thing that distinguishes my situation from the type of "unicorn job" you are talking about is that I have some realism, and I compromise.

Clearly it is ridiculous to expect I can do what I want 100% of the time without any of the responsibility that normally goes with being a PI. Instead, I accept a middle ground of autonomy and responsibility between postdoc/student and PI.

Your article largely seems to be about why employers won't sponsor pure unicorn jobs. Quite true. That's why I have to continually make it clear what value I provide to the bottom line. But I have still done better than the 10-30% you talk about. It's probably 50-70%.

I have found that science and life in general can be quite flexible if you know what you want and take concrete, realistic steps to make it happen.

> You can't get more of them without reforming how science is funded.

Which really demonstrates how important it is to reform the way science is funded.

I bet most PIs also would love to accept a pay cut if they don't need to keep writing funding application to keep the lab afloat. A perfect example of such a position is so-called "biologist" title in NIH. However, what I heard is that it is harder and harder to get it. Nowadays funding in biology is not secure enough for many PIs to offer anyone a stable staff scientist position unless your institute is willing to offer such one. What I heard is that even in NIH, a staff scientist without "biologist" title would possible be/have been cut because of the budget or retired PI. The later case is more devastated because nobody would be willing to hire considering the salary.

Give me (a realistic and workable level of) freedom, a living wage, and treat me right, and I'll stay here as long as I can. He agreed.

Good on him. But I believe a fair number of institutions now have up-or-out type rules which explicitly forbid this kind of arrangement. Certainly wouldn't have flown where I did my postdoc.

What problems are you working on?

My interest is in applying bioinformatics methods to understand aging. His is bioinformatics in general. So most of the time there is actually no conflict between "my" projects and "his" projects, my interests just being a subset of his.

It doesn't hurt that my interests have introduced him to new people and funding mechanisms that he would not have otherwise had access to.

I'm not sure how much detail you want. That was the short version. The slightly longer version is that there are huge datasets out there, and I want to understand aging by building tools and workflows for the many datasets which were not necessarily originally gathered to understand aging, but which still contain information about it. And also to work with and complement wet-lab aging researchers by giving them context or leads for experiments.

When I read your first sentence my brain was briefly trying to figure out if I had sleep-posted to HN somehow because it sounded so similar to my interests (and there aren't a whole lot of people in the aging+bioinformatics area). I think I might have replied to some of your comments on other articles before but I seem to have lost access to the account I used to use.

Are you working on just Human data right now? I have thought about trying to propose something very close to what you're talking about, but in the environment I'm in right now there's a pretty strong bias against non-hypothesis-driven work, and unfortunately the really big picture multi-omic approach is considered to be too vaguely defined. I wish I could just say "let's collaborate!" and then make it happen so I don't end up trying to duplicate what you're doing but if only the funding model actually supported that sort of cooperation (assuming you're in the US). If you don't mind, what institution/lab are you at now? I'm at University of Rochester, trying to make a co-mentorship arrangement work between a lab that works with C elegans as a model for aging (where the PI has no informatics experience) and a lab that works on computational modeling of biological networks (where the PI has no experience in aging/C elegans) because we don't have a real "bioinformatics" program.

Also if you have any advice on bridging the gap between biologists and computationalists, that's something I have yet to master in my now more than half-decade of experience of trying...

I'm at Oklahoma Medical Research Foundation. My focus has been on human, mainly because that's where the impact is, and because of minor technical issues making it easier to do human data. But we do other species as well, the system is just rougher around the edges for them.

The way we get around the bias for (supposedly) hypothesis-driven work is to get a lot of our funding on collaborative and center grants. We can augment our local aging research work by providing them with context and pretty figures for their papers and grants, and they are happy to send a few $100K our way in exchange. We got a Shock Center award a year or two ago which has accelerated things a lot. A lot of it has been catalyzed by Arlan Richardson and Holly van Remmen, who came here from UT San Antonio.

When it comes to "bridging the gap", yes, it is hard. The key I guess is to be flexible and understand what they want. A lot of them are not looking for grand, informatics-driven hypotheses, but they are ecstatic about extra figures or data they can put into their papers to spice them up. Sometimes I slum it a little and do routine statistical analyses on their experiments just to keep the connections live.

In general, I think it is sensible to try to design systems in such a way they bridge multiple species from C elegans to rodents to humans. If you do one, it's not that hard to do them all, and they all have their place, as C elegans is good for quick testing of lifespan stuff but may or may not generalize, so it is considered helpful if you can use data to give tips about what may or may not translate.

The best brief advice I can give is to figure out what the wet lab people want, and give it to them in a way that maximizes the overlap between what you are doing and what they are doing.

Thanks, the alternative funding approach makes sense. It really doesn't make any sense that everyone wants to utilize the output of large scale science that might not necessarily be hypothesis-driven at the start- but as an individual scientist it's heavily discouraged to start by approaching things that way. I think that's going to have to change, but I have to work within the system for now...

That's fascinating. I started a company that cryopreserves adult stem cells. Would you mind sharing what kinds of datasets you are mining? Here or email (in my bio).

Sure. The most mature part of this is analysis of expression data from GEO. We had to take the raw expression data and textual metadata, extract attributes from the semi-structured metadata into something statistically useful, and devise methods to do automated meta-analysis between experiments and platforms on the expression data. We are talking about >1M samples here by 20K-50K transcripts.

Now we are basically extending the same idea to new data types and sources, like methylation and sequencing-based data. When we ask "what should we do next", we look for basically what archives are biggest, and if they conceivably have something useful to say about aging, we put it on the queue.

The big-picture goal is to take this approach and apply it to all these different levels of organization (DNA, epigenetics, RNA, and ultimately hopefully protein) and put it all together in a cogent picture, using way more data than anyone has done before. We ask questions like "how does the aging process differ between tissues?". We also want to go "wide" by comparing species, as the whole "intervention X works in mice but not humans" is an important thing to address.

Then on the smaller scale, the system is also of use and interest to individual investigators who want to know "what's happening with my gene X with age in tissue Y?". They like to include figures from us for example if they have some findings from mice and want to give evidence that the pattern may also hold in humans.

Finally, we built the platform to be a pretty generic meta-analysis tool, so we have occasionally used it to answer questions completely unrelated to aging. Once you do all the background legwork, asking many different questions is largely a matter of changing the meta-analytic model.