[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?

[dekhn]

The older, safer part of my says get the PhD. The younger, more risk prone part (which I ignored for too long) suggests you're going to make a bigger impact sooner by doing something computational and entrepenurial.

The PhD means, when you get to industry, you won't end up as a lab tech. it doesn't mean that you will be running a lab, however.