Monday Open Question: what do you need to do to get a neuroscience job? (Updated)

Awhile back I asked for help obtaining information on people who had gotten a faculty job in 2016 – 2017. And it worked! With a lot of help, I managed to piece together a list with more than 70 people who had gotten faculty jobs during this last year! I am sure it is incomplete (I keep getting new tips as of ten minutes ago…) but it is time to discuss some of the interesting features of the data.

First, the gender ratio: there are 44 men on the list to 33 women (57%). Over at the neurorumblr, 62% of the people on the Postdoc List were men which is roughly the same proportion.

To get more data, I focused on faculty hires who had a Google Scholar profile – it made it much easier to scrape data. It was suggested that people in National Academy of Sciences or HHMI labs may have a better chance of getting a faculty job. Out of the 51 people with a Google Scholar profile, 4 were in both NAS/HHMI labs, 8 were in HHMI-only labs, and 4 were in NAS-only labs.  Only one person who as in a HHMI/NAS lab in grad school went to a non-HHMI/NAS lab. People also suggested that a prestigious fellowship (HHWF, Damon Runyon, Life Sciences, etc.) It is hard to tell, but there didn’t seem like a huge number of these people gaining a job last year.

The model organisms they use are:

(15) Humans

(13) Mouse

(6) Rat

(4) Monkey

(3) Drosophila

(3) Pure computational

+ assorted others

Where are they all from? Here is the distribution of institutions the postdocs came from (update: though see the bottom of the post for more information):

 

In case you hadn’t noticed, this is a pretty geographically-concentrated pool of institutions. Just adding up schools that are in the NYC+ area (NYC-itself, plus Yale and Princeton), the Bay Area, Greater DC (Hopkins + Janelia), and ‘those Boston schools’. I’m not sure this accurately represents the geographic distribution of neuroscientists.

What about their publications? They had a mean H-index of 11.98 (standard deviation ~ 4.21).

We always hear that “you need a Cell/Nature/Science paper in order to get a job”. 29.4% (15/51) of this pool have a first- or second-author CNS paper. 68% (35/51) have a first- or second-author Nature Neuroscience/Neuron/Nature Methods paper. 78% (40/51) have some combination of these papers. It’s possible that faculty hires have CNS papers in the pipeline, but unless every single issue of CNS is dedicated to people who just got a faculty job this probably isn’t the big deal it’s always made out to be.

There’s a broader theory that I’ve heard from several people (outlined here) that the underlying requirement is really the cumulative impact factor. I have used the metric described in the link, where the approximate impact factor is taken from first-author publications and second-author publications are discounted 75% (reviews are ignored). Here are the CIFs for all 51 candidates over the past 7 years (red is the mean):

I thought there might be a difference by model organism, but within imaginary error bars it looks roughly the same:

In terms of absolute IF of the publications, there is a clear bump in the two years prior to the candidate getting their job (though note all of the peaks in individual traces prior to that):

So far as I can tell, there is no strong signal in terms of publications that you had as a Grad Student. Basically, graduate work or lab don’t matter, except as a conduit to get a postdoc position.

To sum up: you don’t need a CNS paper, though a Nature Neuroscience/Neuron/Nature Methods paper or two is going to help you quite a bit. Publish it in the year or two before you go on the job market.

Oh, and live in New York+ or the Bay Area.

 

Update: the previous city/institution analysis was done on a subset of individuals that had Google Scholar profiles. When I used all of the data, I got this list of institutions/cities:

Updated x2:

I thought it might be interesting to see which journals people commonly co-publish in. It turns out, eh, it is kind and it isn’t kind of. For all authors, here are the journals that they have jointly published in (where links represent the fact that someone has published in both journals):

And here are the journals they have published in as first authors:


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12 thoughts on “Monday Open Question: what do you need to do to get a neuroscience job? (Updated)

  1. Interesting observation re: geographic distribution of institutions of successful applicants. Just wanted to say you could estimate overall geographic distribution of neuroscientists by plotting # of NINDS PIs from NIH Reporter by state. Might have to do some data disambiguation though.

  2. Is your calculation of the candidate’s H-indices correct? Average of 12 (albeit with high SD) seems really high. This means average is 12 papers with 12 or more cites, which means average candidate has >=12 papers. What I’m surprised about is that they have so many papers – it seems a lot.
    Very interesting post! Thanks!

  3. Question: does it seem like your sample is skewed towards faculty hired by research institutions as opposed to teaching colleges? And if so, how do you think that skew affects the gender balance and other features of the dataset? In ecology, I can tell you that that the proportion of women among recent tenure-track asst. prof. hires is a bit lower at R1s than at other sorts of institutions. The difference isn’t massive, but it appears to be real (why it exists is another question…)

    • It definitely seems to be skewing toward people who got R1 positions, especially compared to the number on the neuroscience job spreadsheet. I don’t know what the teaching college skew is in neuro; in my personal-experience sample that I can think of, it’s roughly equivalent. All I can say is that on the list of postdocs looking for jobs at neurorumblr, I know a certain percentage were explicitly looking for teaching positions and that list had a higher percentage of men to women than on this list of people who *got* the positions (though not statistically significant).

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