PhD Productivity Strategy: Do Deep Work in Less Hours

I want to second Xaa's point. When I was a PhD student, my advisor told me to enjoy the time because I was free from concerns like funding. We were poorly paid, but it was a good time to just be able to concentrate on research. It was common for people in my physics program to take 6 years to finish. But I wouldn't say that most of us "derped" around. During my PhD, I had a portfolio of projects--some that I thought had a high likelihood of success and others that could (and sometimes did) fail miserably.

As Xaa mentioned for NIH, there are clocks that start ticking after your PhD. This is true for other funding agencies as well. Also, when it's time to start hiring faculty, the fact that someone took 3 years vs 7 years for their PhD is not as important as their publication record and their plans for future research. We recently brought on a guy with 80+ publications (with a large number of those high impact) during his PhD and one postdoc.

I think "rushing" to finish isn't a worthwhile goal (even though I will admit that when I was a student, the stipend was horribly low, so there was a huge opportunity cost for those who decided to do something else later). Being productive during your time is worthwhile. Asking yourself if you are still being productive or if it's time to move on is productive. Not being a technician during your PhD is worthwhile. In that sense, the article has some good advice about taking time out to think. But, in some fields you sometimes just have to grind it out. Say for example, someone is doing an x-ray experiment at a synchotron, or doing MBE synthesis, there are times you just have to put in the hours to get results.

Hedge funds, prop trading etc. do hire from math heavy background. But I agree.

My advice is only good for CS or similar (ECE, Data Science) PhD's.

> Americans tend to look down on anyone who has a doctorate from anywhere in Europe that isn't Oxford or Cambridge.

Look, this just isn't true. I've heard it repeated a lot online, but I've never encountered it myself.

For context, I have a UK PhD, not from Oxford or Cambridge, and I got hired as a postdoc in a top-10 school in the US doing really exciting research.

There are differences between PhDs in US and the UK and Europe, but the differences are complex... there's no clear answer that one is better over the other.

It's a little unfortunate, because I've known Americans who were put off a UK-based PhD because they think professors look down on them, but I've seen little evidence to back it up. My colleagues come from all over the world, and they're all super smart, and everyone's treated equally and with respect. When it comes down to it, the quality of your research, and your ability to work hard, is far more important than what country or institution you're from.

(There are also a lot of anecdotes out there... in this thread, someone who completed early (congrats btw!), someone else with 20+ papers... you can be guaranteed there are people reading this thread who might be discouraged reading this. The one unifying factor with PhDs is that personal experience is highly variable, and artificial targets (finish in x years with y papers etc.) do not correlate with later success or the value of your research. So for anyone still slogging through who's reading this, good luck!)

> Or instead of iterating 5 times, you take your time and do it right on the 2nd attempt, figuring it out in 1/3 of the time. Hurrying only leads to mistakes.

In an abstract sense this is true, but there are some fields were you do just have to do it again, and again, and again. I know an exceptionally smart biochemist who routinely has 16 hour days. There's no substitute.

In my own field, someone who would later go on to win a Nobel for the work, was working on something that simply required a huge amount of time and iteration to get right. This is often the case.

This is not true in all fields, of course. I just want to caution against extrapolating from experience in one field to all PhDs, which is the sense I get from a lot of comments in this thread.

True, but as a heuristic I it is safe to say that if you'd use integer units to represent a quantity then you should use "fewer" rather than "less". That tends to capture the majority of cases for using "fewer". Admittedly, the discrete but non-integer-valued cases are a bit more nuanced.

(And yes, I do realize that the actual definition is in terms of mass vs. countable nouns.)