I am a postdoc doing Particle Physics in a university in a small town in US midwest , and I am thinking of moving from academia to industry. But I have been facing a dilemma because I think I like academia in general and is mostly just struggling with my situation.

I was very ambitious when I was young and picked a really "bad" field. Not that I don't like it, but everyone knows that the chance of getting a faculty job in theoretical particle physics is as harsh as one can imagine. Obviously, it's a very hard subject, and I didn't get to publish much in grad school (just one first author paper). I was fortunate to get this job, but it's not a very popular school, and my current research is also going nowhere, so I think my chance of getting any faculty job is close to zero.

Additionally, my partner (whom I was in the same graduate program with but later moved to Silicon Valley) was doing quite well in industry, and the long-distance relationship is really taking a toll on us. I would like to move closer to her since in my current city there is not much she can do for her job, and there are a lot of industry opportunities in the Bay Area.

But I have been feeling very conflicted about it, because I am still very excited about research and teaching especially in physical sciences and not so much of data science jobs etc. etc. . So I just wonder if there is a way that I can switch field somehow- as I heard from friends, it's fairly easier to get a faculty job in computer science or statistics since a big number of the students just go to industry without looking back. So maybe I can apply for a job in a national lab or those big companies that have research scientist positions that allow you to publish in machine learning related subjects, and if I get good publications I can apply for faculty jobs in computer science/statistics? Is that too idealistic? Anyone on this forum has had that experience?

Or maybe I should just admit my academia career is done and just stop thinking about any academia jobs?

Another question would be, has anyone had experience applying for another PhD program when they already have a PhD under his/her belt? I know it's not a top option given the financial setbacks but I think given that I have extensive coding experience and strong math background I could probably finish a statistics/computer science PhD in a shorter amount of time, then go on to find a faculty job in that area.

Let me know of anything that would be helpful.


To get things out there:

  1. Applying for another PhD after your first PhD is possible and I know a few excellent researchers who are now professors who have two PhDs. It does depend on the field you are moving into of course, but coming from Physics I think your options are good. Basically anything that you can fill in while you work will be relevant.
  2. Where do you feel most comfortable? I have debated this myself (academy vs. industry), but it's not always a matter of deciding. If working in the industry doesn't suit you, then there's no point considering it while you are choosing what you want. If you can't choose what you want, maybe it is an option. Try to imagine what a day's work looks like there, and then a year, and then a career. Will you be satisfied with your work? It's a tough question, I can't figure it out myself.
  3. Check all the options! Have your possibilities set out on the table so you can decide knowing that you considered everything. Check PhD programmes, check companies which do basic research along with commercial projects, relevant startup positions, and check all the various living arrangements. It takes time but I think the worst mistake is deciding without the full picture. Remember that industry has as many, if not more different settings than academia, and you could find a suitable niche in either system.

You have loads of options. The end of a post-doc is really a cliff-edge, and I think it is mainly like this because we don't get exposed to alternatives, and something in our head tells us that not continuing to a tenured position in the same field constitutes some kind of failure. That's just one option out of many.

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