"Typical postdoc pay is $40-60k/year depending on where the job is located ($40k in Urbana-Champaigne, $60k NYC or Chicago)."
I say thee "Ha!", sir. The offers I was getting for post-docs were consistently on or below the low end of that range, even in San Francisco (which ain't cheap).
Probably one of the biggest nudges I had away from academia was the realization that as a post-doc, I'd have a lower standard of living than I did as a graduate student. It didn't seem like a smart trend to follow.
Wow, I guess my experience (in applied math/computational science) was atypical. I didn't get a single offer below $45k, and the only person I know who took less than that was working in New Zealand.
I guess applied math is the place to be if you want to stay in academia.
It also varies widely by funding agency. NIH-funded postdocs are paid abysmally small amounts; DARPA or industrially-funded postdocs can pay quite a bit more reasonably.
I'll echo that that depends very much on funding source. For some university postdocs, it is around $35K, for NIH postdocs, it's less than $50K. Given that the typical postdoc has done a PhD for 5-7 years and many people do two postdocs, it is something to consider. For example, the typical biologist gets her first from NIH at 42....Then, there are those that don't find employment using their science skills, but percolate into other industries (consulting, finance, etc.). I think it's a great lifestyle for those that succeed, but it is extremely competitive--finding faculty positions has also gotten harder due to contracted state funding of universities...
Bayes' theorem states that P(A|B) = P(B|A) * P(A) / P(B), so in this case it says P(PhD|jobless) = P(jobless|PhD) * P(PhD) / P(jobless). It seems that you stated it incorrectly but used the correct version in the computation (the incorrect gives 0.2244).
But who cares about P(PhD|jobless)? P(jobless|PhD) is important; it's a measure of how much job security a PhD leads to. But P(PhD|jobless) is only important if you're a jobless PhD and you want to know what your chances of finding someone else who's survived grad school in the unemployment line. I wouldn't know how to interpret "1 out of every n jobless people has a PhD"; the first thing I'd ask is "what proportion of all people have a PhD", and then essentially run things through a crude mental version of Bayes' theorem.
P(jobless|PhD) is important; it's a measure of how much job security a PhD leads to.
No, it is a measure of how much job security a PhD is correlated with. I believe that the qualities that lead to one being able to complete a PhD are positively correlated with being able to get and hold a job. Therefore you need to restrict to just those people you think could get a PhD to figure out how much the PhD helps or hurts you.
Yes - but take it from me that it can reaaaaallllllyyyy drag out the process if your results disagree with the status quo. I was made to show that something didn't work in general (in lots of cases in practice), as opposed to just showing that
1. it has not been proved to work,
2. it didn't work in a specific case,
3. my replacement method is mathematically rigorous.
And that is why I work for a megacorp, at the moment.
The best, sure, but the majority? I've seen many people in academia fall prey to the flaws and capriciousness of their advisors, so people often toe the line in order to minimize confrontation. And we haven't even taken into account the evil, corpulent morass that is the world of academic bureaucracy.
I'll probably read the whole article, but the first line of the abstract is already losing me:
"The unemployment rate for PhDs in science, engineering, and health is about one-fourth that of the general population."
Oh, come on, you're comparing this against the general population? People who get PhD's in these subjects are typically great high school students who get into good colleges, major in difficult subject matter with high attrition rates, score high on standardized tests, survive a highly selective admissions process to grad school, spend up to a decade in an immensely difficult academic program with astoundingly high attrition rates compared with elite medicine, dentistry, law, or mba programs, and do some unpaid postdoc work.
A low unemployment rate compared to the national average. Gee, now there's a good control group.
For a more sobering viewpoint, take a look at a recent RAND study about the employment prospects for scientists and engineers relative to professions:
31 comments
[ 3.2 ms ] story [ 75.5 ms ] threadThe unemployment rate for panhandlers is also very low, very few of them face redundancy
Probably not very many. Typical postdoc pay is $40-60k/year depending on where the job is located ($40k in Urbana-Champaigne, $60k NYC or Chicago).
That's about 2-4x lower than what the postdoc could get in the outside world, but it's a far cry from minimum wage.
I say thee "Ha!", sir. The offers I was getting for post-docs were consistently on or below the low end of that range, even in San Francisco (which ain't cheap).
Probably one of the biggest nudges I had away from academia was the realization that as a post-doc, I'd have a lower standard of living than I did as a graduate student. It didn't seem like a smart trend to follow.
I guess applied math is the place to be if you want to stay in academia.
According to Baye's Theorem, the P(PhD|jobless) = P(jobless|PhD)*P(PhD)/P(jobless)
Where according to [1], P(PhD) = 0.01 (for all PhDs) so assuming roughly half are science, P(PhD) = 0.005, and we get
P(PhD|jobless) = 0.0013, or 0.13%, which means that roughly 1 out of every 1000 jobless people has a PhD.
[1]http://factfinder.census.gov/servlet/QTTable?_bm=y&-geo_...
(I have a PhD. In probability.)
No, it is a measure of how much job security a PhD is correlated with. I believe that the qualities that lead to one being able to complete a PhD are positively correlated with being able to get and hold a job. Therefore you need to restrict to just those people you think could get a PhD to figure out how much the PhD helps or hurts you.
You'd be foolish not to hire one.
If so, then who doesn't consider that a "job", and why should we care that they have this bizarre viewpoint?
1. it has not been proved to work,
2. it didn't work in a specific case,
3. my replacement method is mathematically rigorous.
And that is why I work for a megacorp, at the moment.
"The unemployment rate for PhDs in science, engineering, and health is about one-fourth that of the general population."
Oh, come on, you're comparing this against the general population? People who get PhD's in these subjects are typically great high school students who get into good colleges, major in difficult subject matter with high attrition rates, score high on standardized tests, survive a highly selective admissions process to grad school, spend up to a decade in an immensely difficult academic program with astoundingly high attrition rates compared with elite medicine, dentistry, law, or mba programs, and do some unpaid postdoc work.
A low unemployment rate compared to the national average. Gee, now there's a good control group.
For a more sobering viewpoint, take a look at a recent RAND study about the employment prospects for scientists and engineers relative to professions:
http://www.rand.org/pubs/issue_papers/IP241.html