[RK]

I'm under the impression that it has only gotten worse.

Anecdote: A super smart friend of mine from physics grad school finished in 2008 and went on to post-docs at Caltech and Harvard. He was unable to get a tenure track job, primarily because in that 4 year timespan only 1 faculty position opened up in the entire US for his (tiny) field. He now works at Google.

In fact I'm not sure that anyone from my cohort is still in academia. Other students used to come ask me questions all of the time, because I had worked in industry before going to grad school. Their questions were always some variation of "what are my options if I get out of physics?".

Edit: I'll also add that most grad students I knew gave little thought to their post-grad job prospects before starting grad school. It seems now that the message has trickled along a little better that the outlook is very poor.

[pavanred]

I interviewed recently for a Data Engineer position in Chicago and was surprised when 2 interviewers from the data team introduced themselves as astrophysicists. They reasoned that they weren't happy with the career path in academia and so found a way out.

[Bahamut]

It's becoming more common as far as I can tell - I also left academia (mathematics) since academia is less about the work you do now. My brother stuck it out and finished his PhD in chemistry, but he too bolted from academia since he hated it as well (and that is with the fortune of having a high reputation thesis advisor, but who milked him for as many papers as he could before my brother threatened to just up and leave) - he's now a senior engineer at Samsung.

The academic landscape is just poor these days - it is a pretty brutal world to operate in.

[dekhn]

I'd just like to emphasize:

while most people would agree that we train too many PhDs, I can assure you: the process of training many PhDs (in any discipline) has been very, very good to Google. It selects for, and hones the skills of, people who are quantitative, can form hypotheses, and test them.

I went to Goog- and took a significant temporary hit to my bioinformatics career- while working as a software engineer on stuff that was far from science. However, I can assure you: my training could be easily transferred.

Looking at the alumni list for my program, http://biophysics.ucsf.edu/people/alumni I see a very wide range of outcomes- yeah, a few professors, but also SVPs of companies, venture capitalists, doctors, software engineers, patent counsel, and industrial scientists. You can also see the postdoc bolus.

Another way to put it: going to school is not the fast or easy path.

[epaladin]

I'm seeing more and more bioinformatics-related positions in industry that are listing a PhD as a requirement. I'm currently trying to decide if it's worth it to do the PhD now (in Bioinfo or a strongly related program) or to side-track for a little while doing something more directly computational or entrepreneurial. I'm ultimately interested in coming back to bioinformatics regardless. Would you say it's worthwhile to do the PhD (even if intending to work in industry), or to try to make up for the lack of a PhD with other experience?

[kaybe]

Do you have a write-up of your answers lying around somewhere? I'd be interested.. (half a year to go on a Master's)

[RK]

No write-up, but people I know have left physics for:

* Quantitative finance

* Insurance (working on models that were beyond what the actuaries were trained to do)

* Data science

* Scientific equipment R&D

* Scientific equipment sales

* Popular science writing (this is a bit of an outlier!)

* Defense contracting (engineering, "scientific" programming, etc)

* Programming

* Door-to-door insurance sales (no joke)

I usually tell people to brush up on their programming skills as much as possible. If you're a theorist who only does pencil + paper or maybe Mathematica, it might be hard to find a decent job. Also, it never hurts to talk to / network with any industry people that are related to your field (software or hardware vendors, etc).

I'm now doing data science, but have also done hardware development and electrical engineering related things (signals). When I was transitioning to data science I also did some very specialized consulting related to my PhD. A few people paid me to do simulations and/or help then implement some techniques that I worked on as a grad student.

Also: I had a very supportive advisor, who encouraged me to accept a job offer before I graduated.