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Comment by azhenley | Hacker News Reader

When I was on the academic job market in 2017/2018, most of the CS faculty positions I was applying to paid between 95-115k as the 9 month salary. So with summary salary from your startup funds/grants it would pay a total salary of 115-140k (assuming 2 months summer salary, which is common).

That is not bad. The university/department ranking seemed to affect the salary only a little. The cost of living surprisingly affected the salary very little. This means you could make 130k while living in an extremely cheap area, but living in an expensive area you would not make much more.

Of course, many fields don't pay anywhere near that. Some pay quite a bit more (business!).

Disclaimer: I'm tenure-track faculty at a public R1 university.

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Anecdotally based on some skimming of the California version of the salary database, there seems to be greater variation between fields than between universities. My wife is in the humanities, and the mid-career salaries of the professors at UCs in her field seem to be about the starting range for UC professors in mine (biology).

If you are currently tenure track at an R1, I would expect that most of your other offers were from a similar tier. So while there may not be a huge difference in salaries between the top-ranked and the 30th ranked school in your discipline, there likely is one between the 30th ranked and the 300th or 1,000th. I'd be curious to see the analysis in the linked article run on the California data, where there are multiple top-tier research universities as well an extensive CSU system. Maybe I'm even the person to do that analysis...

An analysis like that would be very interesting to see. Despite a lot of this data being public, I haven't seen any useful analyses of it (e.g., they always mix different fields or lump adjuncts in).

It would be helpful if I could select a field, a position (e.g., assistant prof), a range of school rankings, number of years since hired (e.g., hired last year), and a geographical region, and see the salary data.

Not to be condescending, but I should hope area of study should influence expected earnings of an academic.

I hope it's not too much of a stretch to see the difference between a professor of medicine and medieval tapestry or Viking theology

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