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I am currently a postdoc in a genomics lab, doing computational work. I will be completing three years in the lab, this fall (this in the US). I graduated with a PhD in theoretical physics in 2012 (US university) and during a postdoc year at an obscure lab somewhere in Europe (this was the only offer I could land), I decided to switch fields and move into computational biology. It took me about a year to figure out the background for the field and land another postdoc (which is where I am now). I have managed to publish one paper in a high impact journal at this lab and also picked up lots of bioinformatics techniques.

However, the lab is not a good fit for me. It's not really multi-disciplinary and does not use any of my physics skills. But by going to conferences and talking to other people, I have managed to figure out what kind of work I'd like to do in the broad field of computational biology. I've also taught myself the necessary analysis methods that would be helpful.

So here's my question: I am going to apply this fall for another postdoc in labs that are much more aligned with my interests and where I can be a better fit. (a) But some universities specifically state that the PhD should be within five years. (b) Others state that the total postdoc time (including previous experiences) should be five years. (c) And there are yet others which state that the total postdoc time at that particular university should be five years.

Cases (a) and (b) could hurt me. Are there other researchers here who've been in similar (or remotely similar) situations? How strict are these five-year cut-offs? I have now acquired a lot of skills and have a much better vision of where I'd like to take my research in computational biology. I am worried though that this five-year cutoff rule could hurt my research plans and career.

In physics itself, I know many post-docs who did more than two post-doctoral stints with a total time exceeding five years. I wonder how they managed to deal with this rule?

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At least in the US, postdocs are hired by individual faculty members without consultation from others, so the guidelines are somewhat fungible, particularly if there's a compelling reason to hire you.

The one exception is for external (and some internal) fellowships—in such cases, the recency rules are pretty much absolute.

In other countries, though, the rules for what is or is not allowed are stricter, and it may not be possible to circumvent them without significant amounts of work on the part of all involved.

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I strongly agree that these time limits are a horrible idea, especially when applied indiscriminately and across fields.

For fellowships and "postdoc status", you're often stuck--the rules are whatever they are. Some places are willing to make exceptions for people who have changed fields or spent time away from the lab (e.g., to have a child or work in industry). If either of these apply, that might be your best bet.

If not, you still might be able to take a postdoc-like job without the postdoc title. These positions are often labelled "Research Associate", "Associate Research Scientist", or "Staff Scientist." Informally, these often still get call postdocs.

My impression is that it's sometimes slightly harder to be hired into one of these jobs: the salary is often (slightly) higher and you won't be eligible for time-limited fellowships, but it's not impossible and I think it's fairly common for postdocs to be 'promoted' into this job when they age out.

  • "I strongly agree that these time limits are a horrible idea" - Note that part of the reason for these time limits is that post docs are still not 100% considered employees under certain legal situations as "employees-in-training"; their situation is a bit better than graduate students in research assistant positions. The other positions you mention that omit the "postdoc" designation force those people to be hired as true employees. Although this could disadvantage the employees if they are not hired as a result, the intent is the opposite, to protect employees from 'in training' labels. – Bryan Krause Oct 11 '18 at 17:46

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