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Post-Doc and Assistant Faculty Position


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Nowadays when I see job talks at my statistics department(top 30), I have an impression that Post-Doc is kind of the norm for one to stay in academia. Since when did this become the norm?

Plus, I just can't help being shocked by the number of top tier journals(Annals, JRSS-B, JASA, Biometrika and etc) that each candidate has published. How can a person who just finished Ph.D. and spent 1-2 years of Postdoc could produce 4-5 top-tier papers at the minimum? (in fact, this year, I see the minimum is seven, at least in my program.) I am not denigrating anyone, but several professors I am aware of did not even have a paper published when he was hired as a tenure-track assistant professor. Isn't this situation a bit insane?

I think this does not stop at the faculty position level, but even for doctoral applications. While I was talking with the person who graduated in 2013, I realized that this student was able to crack into many top statistics Ph.D. programs with a weaker profile, while those who recently graduated could not even get any admission with a stronger profile. 

I just feel that there is a huge surplus in talented people who could do well in academia being wasted because of the current situation. I do realize that many programs are trying to expand the size of faculties, but the current situation is a bit overwhelming to me. Shouldn't there be a university level of expansion of statistics programs instead of designing so-called cash-cow Data Science programs? Are all these due to limited funding issues?

Edited by Statmaniac
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2 hours ago, Statmaniac said:

Nowadays when I see job talks at my statistics department(top 30), I have an impression that Post-Doc is kind of the norm for one to stay in academia. Since when did this become the norm?

Since around the time of the financial crisis (2008-2010). In those years, there were very few jobs to go around and so a lot of graduating students ended up in postdocs. Then, when those folks went out on the market a couple of years later, they looked "better" (i.e., had more publications) than graduating Ph.D. students, and the pattern was established.

2 hours ago, Statmaniac said:

Plus, I just can't help being shocked by the number of top tier journals(Annals, JRSS-B, JASA, Biometrika and etc) that each candidate has published. How can a person who just finished Ph.D. and spent 1-2 years of Postdoc could produce 4-5 top-tier papers at the minimum? (in fact, this year, I see the minimum is seven, at least in my program.) I am not denigrating anyone, but several professors I am aware of did not even have a paper published when he was hired as a tenure-track assistant professor. Isn't this situation a bit insane?

Yep, volume has exploded and I don't quite know what to make of it either. The cynic in me says that advisors are wielding a much "heavier hand" in helping their students (and even postdocs) prepare papers. Regardless, it's a vicious cycle; people with long CV's get jobs, which incentivizes everyone to try to bulk up their publication list as much as possible.

2 hours ago, Statmaniac said:

I think this does not stop at the faculty position level, but even for doctoral applications. While I was talking with the person who graduated in 2013, I realized that this student was able to crack into many top statistics Ph.D. programs with a weaker profile, while those who recently graduated could not even get any admission with a stronger profile. 

This aligns with everything I've seen. The applicant pool has gotten much, much deeper in a relatively short time. I don't know if the top end is any better, but the sheer volume of very good applicants is staggering.

2 hours ago, Statmaniac said:

I just feel that there is a huge surplus in talented people who could do well in academia being wasted because of the current situation. I do realize that many programs are trying to expand the size of faculties, but the current situation is a bit overwhelming to me. Shouldn't there be a university level of expansion of statistics programs instead of designing so-called cash-cow Data Science programs? Are all these due to limited funding issues?

It's hard to expand Ph.D. programs quickly. You have to identify sources of funding for students, and hire enough faculty to advise them. I think you are seeing some amount of program expansion, but it clearly hasn't kept pace with demand for spots. Of course, the "data science" craze won't last forever; just ask computer scientists about the late '90s and early '00s.

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