How I turned seemingly 'failed' experiments into a successful PhD
science.org
science.org
I finished my Ph.D. in 6 years rather than the usual 4 1/2 because ideas just didn't work out. My topic was much harder than those of my peers.
That said, I felt the 2 extra years I spent made me a much more solid researcher in my narrow field, because I spent more time learning and relearning the foundations of my craft.
I relate to what Winston Churchill said about being a dunce at school (who later become a incomparable wartime orator distinguished by his use of simple English):
"By being so long in the lowest form I gained an immense advantage over the cleverer boys... I got into my bones the essential structure of the ordinary British sentence–which is a noble thing. Naturally I am biased in favor of boys learning English; I would make them all learn English: and then I would let the clever ones learn Latin as an honor, and Greek as a treat."
I read it in my last year of college. It was a page turner, and helped me think about whether I wanted to do a PhD.
[0] https://www.dropbox.com/scl/fi/g8mc1lniyf26opxtrqgna/pguo-Ph...
I dunno about the "filthy rich" outcome but this strategy is actually fairly common.
The team was great, the topic was great, I did something really innovative.
I also partied a lot, met great girlfriends, met my wife, made friends.
One of the best times in my life.
Or without seeing what Matt Groening thinks of your plan. (Just in case the Ph.D. simulator was not enough to scare you off.)
https://www.pinterest.com/pin/grad-school-so-glad-i-am-done-...
The winning move is to mine for an idea, then just do that idea and nothing else until you get a paper or reject the idea. Rest when tired.
Got my [simulated] PhD in 5y 4mo with 99/100 hope left by following that algorithm. Perfect teachable moment. Thanks
My big issue with the PhD is that it was designed to treat me as an employee in exchange for an annual salary equal to 1-2 months worth of earnings as a software freelancer. But the work was interesting. So I wondered why not be an amateur researcher instead.. Of course once I quit, real life intervened and I did little of substance during the following couple of years. I neglected the value of the focus that doing a formal program facilitates. However, I had some ideas recently and was able to establish a dialogue with a relevant research group, so the whole idea may work out after all.
Back to paper writing...
Going to grad school was the wrong economic decision for me... and perhaps the wrong 'life' decision as well.
if you had the option of getting into a well-payed, cushy tech job grad school would result in less personal/financial freedom.
if (like me) you didn't have that option out of undergrad, grad school was comparatively a period of great freedom. * i made enough on research/TA stipends that i lived a slightly-fancier-than-my-undergrad lifestyle that wasn't too far behind what my classmates that became teachers were living. * TONS of freedom with respect to how I wanted to work and having full control of my schedule
I feel like grad school gave me a pretty idealistic way to spend my mid 20s. And (luckily) in that time I was able to develop enough skills that I could jump into one of those high-paying, cushy tech jobs when it came time to realize that academica sucks and I wanted to leave.
This, the economy was shit when I graduated, I wasn't interested in a phd, but strongly considered getting a masters, and would have likely been financially better off had I stayed in school those extra two years instead of graduating into a horrible job market and losing that fresh graduate advantage when applying for jobs once it finally got moving again. In retrospect, I would have much rather lived a college lifestyle and did research/ta type stuff instead of doing the tech support type jobs I ended up with to make ends meet.
My doctorate was essentially; run studies for 2-3yrs, write up papers for submission, smash them together with an intro and general discussion, graduate.
I think this is often useful. Maybe it's obvious, but it can be very tempting to develop ideas, or develop new shiny results, when you still have other ideas that haven't yet been turned into definite packages of well-supported results.
(I can only speak for my experience and those of my peers in my field, at the end of the day)
This was in a proper hard engineering field though. I think in other fields can be much more likely to be things that can't really fail. For example in computer science, a lot of PhDs are just like "I implemented this thing" where there's very little risk of it simply not working.
An exception in computing is AI research where it is very much like the "try some stuff; it didn't work" experience of engineering and science research. I imagine a PhD in AI is not a fun experience...
My advice to most people would just be "don't". My second run of advice would be "find the most boring project imaginable" since it's likely to succeed on the basis of "do a bunch of fairly predictable experiments and publish them".
As a result, the criteria for graduation is often softer than in the US.
Also bear in mind in Europe you need a masters before entering a PhD program (or significant research experience), and you spend 100% of your time on your research, there's not courses or teaching. I think that better explains why they're finished in 3-4 years.
That's not true for maths at U of Tromso nor true for (as far as I know) all of Hungary.
In biology I've seen a lot of more recent theses where a couple of the chapters are from middle author works with a bit of extra context on what the student did, and only 1 first author chapter. But besides being slower to do generally, bio still has a lot of people that don't believe in shared first authorship. Sometimes what is technically a second author chapter was pretty close to 50/50 in what the student actually contributed.
―David Blackwell
My advice for young researchers is read more articles - like at least a solid month of reading and journaling full time (40 hrs per week) before you even start to think about what you want to start off with by replicating.
The other related mistake I see young researchers make a lot is not leveraging pre-existing work / results and wasting weeks or months reinventing the wheel.
You can typically make nice prototypes in a weekend and try out ideas. If one or two of these work out, you get a paper after a bit more work polishing it.
Of course you have to be competent and able to build prototypes, which is something I have seen about half of the students lack. In that case, you can typically also get a PhD by basically doing minor tweaks on existing tools and putting a lot more effort in benchmarking and story telling. Both are useful to science.
Your idea may be the ideal case :]
I must have been involved in ~20 projects in my PhD. Only 3-4 will ever be published.
If you anticipate low success rates, you can find success either through luck or through diligent experimentation with an expectation of null results. Null results which, by the way, can often improve your odds of downstream success.
Every lab usually has a few “I’ll bet it’ll work but I don’t have time to find out” projects.
But that’s actually a big part of doing independent research - using your time the most efficiently, so students need to get to the point where they have a dozen or so paths and they plan out the next year or two thinking about the best way to tackle them and “fail fast”.
They make a good point: By focusing only on positive results in publication, there is little common knowledge of pathways that don’t succeed. Back when I was doing grad studies in math, I remember thinking that this could be a useful thing in that field as well: compiling plausible pathways towards proving theorems that end up to be dead ends. I almost feel like something like this could in its own way spark new discoveries in mathematics.
When I was in grad school I was very hesitant to ask others for help or feedback. Big mistake! I see similar things with interns: they'll wait until a daily or weekly check-in to raise problems.
My approach now is to set a time budget; if I don't figure it out myself within X hours, then I have to ask someone for help.
For me in the U.K. there were 7 chapters to my thesis that I worked on for roughly 3.5 years. Two of those were “failures” in that they weren’t publishable as positive results but the others worked OK. One was an algorithm paper and I published the source code to GitHub because while it wasn’t useful to me (slower than the competing algorithm we already used) it was applicable in more general situations and it has proved to be so as people have emailed me about it at various times and it’s been cited.
Everyone has to turn failed experiments into a successful PhD because they have to finish and graduate by the time funding runs out.
It's also extra untrue because this author is describing running into a null result and turning that into a PHD when usually null results don't go anywhere, either to a thesis or a publication.
But it becomes true again in the context that the null result is nice framing for this article but isn't the framing in the intro/contents of the thesis. And also because:
"A turning point came when another graduate student suggested a dramatic change to my protocol. I was skeptical, but I thought it was worth a shot. It turned out they were correct: After trying yet another experiment, the results started to look better—and after a few more changes, I eventually got the protocol to work. "
doesn't sound like a failed experiment to me!
Especially that "life might be more complex in infectious disease research than in oncology" - as an outsider this really caught my interest, I'd have imagined the two have similar levels of grants? Maybe more than a field like Psychology or Developmental Biology, about the same?
Does this mean more people are going into in disease research because A) it's more interesting to them? (vs Oncology)... or B) The grants from COVID mean it's a better field?
You can see NCI (National Cancer Institute) leading the pack there, with NIAID (National Institute of Allergy and Infectious Diseases) coming in second.
It surprises me how few people, even in my field(s) (which are overwhelmingly funded primarily by NIH), know of or use these tools. Particularly RePORTER and the advanced project search functions.
Oncology has way way way more funding because there's a much bigger market for it - infectious diseases primarily affect poor people who aren't Americans so not much money in it. Even at the peak of covid I remember advisors warning phd applicants passionate about infectious diseases that the funding surge wasn't going to last and to be careful (which was right). Consider how moderna was originally founded as a vaccine company before almost completely shifting focus to oncology because that's where the money was. Obviously they swung back to vaccines when the pandemic showed up but now they're back focused on oncology.
Funding priorities are also set by the government - there's the cancer moonshot etc which means tons and tons of cancer funding. For universities new cancer treatments are quite valuable IP. And so on. Within a field it becomes very obvious where the funding and momentum is - what are the buzzwords everyone is putting in their grants and papers (nanotech? AI?), what types of publications are getting published int he big journals. Gene therapy came out of its winter after luxturna for example. Car-t was booming after the first approval there, entire departments were set up for it. Mrna stuff is super hot right now, but one of the researchers behind the core technology (that made her university like a billion dollars in royalties) was denied tenure and pushed out of academia when she originally developed the technology because it was considered not useful. First lab I worked in - the PI was fresh out of his postdoc and got hundreds of thousands of dollars in funding and his own lab and bought his own flow cytometer and everything (absolutely not the normal path lol) because he was a first author on a particularly good CRISPR paper. On one hand - trend chasing and bubbles have their obvious downsides. On the other hand - it does mean a lot of resources get funneled into new interesting areas when something cool pops up. But on the original hand - trend chasing and bubbles, welcome to humans on earth i guess. But yeah in terms of how you know about it - you'll know it's quite obvious who's getting money and tenure.
Infectious disease in particular is going to have a really hard time. No market for it, no industry demand. Investments there are already winding down in general: https://www.fiercebiotech.com/biotech/johnson-and-johnson-sh....
Making a regular experience sound like a special sort of skill only you have is itself a special sort of skill that it's valuable to have if you want to apply for grants.
I'm afraid that I don't have the faintest idea, both because my grant activity hasn't been noticably effective (and I held no grants while pursuing my Ph.D.), and because I've never applied for a Startup / Innovation grant.
“If an experiment doesn’t go as expected, it doesn’t necessarily mean you did something wrong.”
That’s why it's called an experiment… I don’t get why this is insightful.
I guess there is a lesson about carefully noting down failures, in the corporate world handing over a document detailing all the things you tried that failed is much better than just failing silently.
The outcome of the research (experiment) could be both success and failure, right? That's why we study it, experiment with it, we do not know it yet, we want to see if it is as believed or not. The important is to grow the body of knowledge here - and knowing if something does not work the way we thought will is knowledge -, not to pretend being successful, right? For pretending there are countless other (much much better paying) occupations anyway.
So unsuccesful results are very difficult to publish and to be the base of a thesis. So you must find a twist or secondary result and make it the central part. (Does listening to Macarena for 8 hours per day cause brain damage in mice?)
Also, I think I seen that Macarena article. : ) It suggested to extend the research to primates and Spice Girls and finding songs that cure the damage of Macarena.
But, taken as a whole, they offer some ways out of the single-track-grindset that some people in the academic system have -- and that the system promotes.
It turns out that there are a lot of stories out there of people who had to give up on something, change fields, recognize their strengths or weaknesses, etc. People don't talk about this stuff as much as they should.
In actuality, science done right is all about disproving things.
You can spend a lifetime tracking down all the white swans to “prove” that “all swans are white”, but you need to find only one black swan - as the British did when they reached Australia - to disprove that hypothesis.
Science is about disproving things, as it is by far the easier path - and frequently, the only possible path - to take. And by disproving things, we push back the darkness more and more, until what little remains must contain the truth.
And when science “changes it’s mind”, it’s simply science obtaining more data that points better towards that truth, more of the darkness has been pushed back and the old position was eliminated by the new evidence.