[emanuelev]

I quite agree that the post PhD job market is kind of challenging as there are few companies tackling big questions.

However, if you forget the job market, the argument the guy is making is absolutely spot on. There's a solid trend in academia that is "publish early, publish fast". Although one might argue that it actually makes sense (career-wise or whatever), it is intrinsic in such a system to penalise pursuing big, risky ideas. Considering that the PhD (and the few years after) are the most productive in a researcher's life, it is a shame that students are not actively encouraged to think bigger.

[lmm]

> There's a solid trend in academia that is "publish early, publish fast".

With an increasing number of researchers isn't that a great thing? If you publish your little incremental innovations then everyone can build on them. If you try to build your giant all-encompassing framework before you publish any of it, you'll have to do it all yourself (if it even amounts to anything).

[Fede_V]

It would be if what got published were plenty of incremental papers. That's the case in certain fields (deep learning comes to mind) - but in other fields, such as the life sciences, you instead get a bunch of results that claim to be groundbreaking and novel - but in practice end up being very difficult to reproduce (like the STAP controversy).

Why? Because small incremental improvements cannot get published in high impact journals, and high impact journals are the currency to scientific prestige/grants/tenure.

[jamesrcole]

You're assuming that all important innovations are incremental. Historically that is clearly not the case.

[lmm]

Not at all clear to me. Examples?

[roymurdock]

There's a popular paradigm shift theory that posits that we tend to adopt frameworks that explain the world, then work incrementally within those frameworks until they cease to make as much sense/have as much explanatory power as they once did.

Then someone (Newton, Darwin, Einstein) comes along and assembles a new framework based on new observations/theories that do a better job of explaining things. Eg the switch from creationism to evolution, or from newtonian physics to relativity.

Here are some more examples:

https://en.wikipedia.org/wiki/Paradigm_shift#Examples_of_par...

[mannykannot]

There is an important truth here, but be aware that the popular history of science and technology over-emphasizes the 'lone genius' narrative (it is the 'lone' part that is exaggerated.)

[roymurdock]

Agreed, but that's the story we like to hear, so it's the one that gets repeated. That nobody lives and works in a vacuum is an implicit assumption.

[lmm]

The switch to relativity seemed pretty incremental to me. Einstein's special relativity work builds hugely on that of Lorentz published one year before.

[jamesrcole]

Could Einstein have justified his course of research as an attempt to incrementally innovate on some existing work?

[jamesrcole]

Incremental innovations of the sort you are talking about means extending some pre-existing framework. There are obvious examples of important developments that involved developing different frameworks, which took many years to fully justify with evidence. The heliocentric view of the solar system, Newtonian physics, natural selection, relativity...

EDIT: I would also argue that developments like the printing press and the world wide web would have been difficult to justify as incremental extensions of existing work.

I'm not saying these developments came from nowhere, nor that they didn't build on previous work. I'm specifically arguing against the idea that it's fruitful to just focus on work that would be seen as incremental improvements on existing work.

[jmmcd]

If the printing press or web were proposed as research topics by a new PhD student today, they'd probably be laughed out of the room. But if they were proposed by someone with credibility, who knows what research is like from top to bottom, in a EUR2M grant proposal with a good demonstration of how the new ideas relate to existing work, featuring an appropriate-sized team and a detailed risk management plan up-front -- they'd be funded.

[mattkrause]

This implicitly "punishes" subfields that move more slowly. It can take over a year to train a monkey to perform complicated behavioral tasks. In the same time period, you could breed 50+ generations of fruit flies, or ~25,000 generations of bacteria. Furthermore, the monkey researcher will have fairly little interim data, whereas the bacteria or fruit fly work may have something interesting within a few weeks.

This could be normalized within fields, but in practice it's not. For example, the NIH K-awards have a fixed eligibility period, which seems to keep shrinking.

[rhaps0dy]

>the PhD (and the few years after) are the most productive in a researcher's life

Source? I'm curious.

[4ad]

Not a "real" study, but it appears to be true: https://youtu.be/Mpsc-BxAiHs?t=1537

[dagw]

It's a common view, but a number of studies seem to contradict of at least question this:

http://openaccessweek.org/profiles/blogs/age-amp-science-do-...

"A study in 2002 examined 50 Nobel prize winners from each of the three prizes for physics, chemistry and medicine. This study recorded the age of the scientists when they had done the work that was rewarded with the prize and found that the centre points for age were: physics, 34; chemistry, 37; medicine, 40 (Marchetti C, 2002.) A study published in 1993 investigated a similar data set and concluded that scientists tend to be the most productive in their mid-thirties (Stephan & Levan, 1993.) Finally, a 2008 study of 300 randomly selected bioscientists revealed that the most productive age was 36-40 (Falagas et al., 2008) based on the number of citations from their publications. These studies all indicate that a scientist's greatest potential for discovery is during their thirties"

If instead you measure productivity in number of articles published, this study (http://link.springer.com/article/10.1007%2FBF00142022) claims that productivity peaks at 45-49. However that number covers a wide variety of fields, not just science, and makes no attempt to account for the quality or significance of the work.

[toufka]

'On the ground' productivity, where the scientist is doing labwork ends before a scientist 'gets their name on papers'. That kind of work is different from the 'guiding the science' work. It's the boss who wins the Nobel Prize, not the student, though it's the student who is the 'productive' one in lab.

[emanuelev]

I'm sorry, I don't really have a source. My observation is based on the fact that during PhD/PostDoc years you have more time to spend on actual research. As you climb the academic ladder it is very probable that administrative/supervising/teaching duties become central to your job (unless you really don't want to).

Incidentally I remember also reading [1] that in certain fields, in this case mathematics, most of the groundbreaking research comes from younger mathematicians. Great contributions to the field from people over 40 are extremely rare.

[1] Simon Singh, Fermat's Last theorem. Ok, not great source but still!