- Even the most blatantly wrong and illogical published work can only be displaced by another publication that explains/does the same phenomenon better; i.e., people are going to keep believing in phlogiston until someone shows them oxygen. If you simply point out inconsistencies in phlogiston theory, in person or in writing, they may well make a variety of unwanted psychological deductions about you.
- Similarly, nobody actually enjoys being around critics or enduring criticism, and therefore you will observe many senior scientists partially avoiding the major downsides of being a critic by artfully concealing criticisms inside what sounds to the uninitiated like mutual affirmation sessions. You have to listen very closely and learn the lingo to pick this up.
- Never question a scientific superior (other than maybe a direct mentor or very close colleague) with any other approach besides "I have a helpful suggestion about how you can maybe reach your intended destination better/faster/more precisely". Regardless of where that destination might be, such as off a cliff or into a wall.
- The opinion/fact ratio you are allowed to have as a scientist is directly and very strongly correlated with seniority, H-index, and so on.
- The incentive structure of scientific publication is such that there are big rewards for being right on an important question, bigger the earlier you are to the party, and little to no penalties for being wrong, so long as the error cannot be provably and directly linked to fraud. There are a variety of interesting consequences to this incentive structure.
[0] https://en.wikipedia.org/wiki/The_Structure_of_Scientific_Re...
[0] https://en.wikipedia.org/wiki/Research_program
[1] Lakatos, Imre. (1978) The Methodology of Scientific Research Programmes: Philosophical Papers (J. Worrall & G. Currie, Eds.). Cambridge University Press.
This is fantastic insight and I'd like to thank you for sharing it with our group.
Would you agree that the model of rewards for correctness and penalization only in the case of fraud is the core feature of science? And what separates it from business or politics where being an honest failure is worse than being dishonest but successful?
Again, this is a great post, and I think you have a fantastic future in the sociology of science!
I think science is too big a thing to have a small set of "core features", and the question of how to usefully define "honesty" in a scientific context is another big topic, but reading about "bullshit" (the term of art that has its own literature, not the colloquialism) is a good place to start thinking about it.
I would suggest that fraud is one of the rarest types of dishonesty, because people who are both smart and dishonest have less risky ways to proceed, and that such people are very glad fraud exists, because it misdirects attention away from their arguably more damaging and prevalent methods. Feynman has a passage about how honesty in science is more a state of mind, which I agree with. But really, the techniques to be dishonest with low risk are the same in science, journalism, politics, and business.
My field isn't sociology of science though; these are just views from the genomics trenches.
In your message I observe, very careful criticism, uncalled praise, admission and defense of a system that excludes most criticism...
"Never question a scientific superior?" Not parsing that concept, please elaborate.
I think the way it ultimately works is that you have to be disillusioned from the grade-school fairy tales told to the public about how science works before you can learn to live and work in the environment that actually exists rather than the one you wish existed.
> "Never question a scientific superior?" Not parsing that concept, please elaborate.
tech < grad student < postdoc < junior faculty < full prof < Big Guy/Gal < Nobel Laureate < NIH Director
People above you in that chain will accept limited feedback on methods to attain their chosen goals and will greatly resent questions about whether their selected goals are worthwhile/realistic/rational, or whether their gestalt vision of the field's conventional wisdom is correct.
1. Bad work only being displaced by good work: everything works like this. To replace some useless commercial product (take your pick) someone has to come up with something better. Same goes for information.
2. Nobody liking criticism can be rephrased as it being important to attack ideas, not people, when you have to work with those people.
3. "Never question a scientific superior" is the first piece of advise I think is too cynical. As a warning against undermining a colleague in public when you need their support, I agree, and that's kind of a restatement of #1 and #2. But science really does have a culture of publicly debating contentious ideas. You can definitely be more critical in an event specifically held as a debate / open forum than in a presentation Q&A though, and at a social event it's polite to be at least vaguely supportive.
Kind of a tangent to the later points: Day to day scientific research is mostly chasing dead ends and other activity that is (in hindsight) mostly useless, but there is genuine societal value in having a large body of skilled workers available. That is, science spends a lot of time spinning its wheels trying to figure out the right question to ask, and once this becomes clear there is rapid progress. This means the papers published in between the breakthrough periods aren't really worth paying attention to unless you work in that area. Having a lot of scientists and engineers in the workforce so we collectively have a decent chance at obtaining and exploiting next breakthrough is the point, the papers are just a byproduct.
If you think you've been put on a bum topic or your supervisor has put you on the scientific equivalent of a PIP with no way up or out your room for maneuvering is limited, to put it politely.
Your observations aptly apply to industry as well except for your final one regarding the incentive structure.
Thank you for commenting.
I was just trying to learn. Learning bad is what I learned.
This one is a direct contrast to your advice (which speaks volumes about what's wrong with academia): "A good scientist, in other words, does not merely ignore conventional wisdom, but makes a special effort to break it. Scientists go looking for trouble."[0]
This was written about physics at Caltech, but applies more broadly. It explains why the ability to 'manage up' is so critical for early-career success. "[...] departments are run, for better and worse, by the professors who often lack managerial experience. Worse, they are generally unaware of this shortcoming, assuming incorrectly that management is trivially easy compared to their topics of study and merits minimal effort. We have now seen the consequences of this lack of attention." [1]
Academic politics is a great reason not to stay in academia: "Look for environments where competitors see themselves as playing a game, rather than fighting for survival — this prevents rankings within the hierarchy from becoming an existential problem." [2]
This book has a great chapter of career advice, here's a gem: "Don't build a pyramid. Everyone seems to build one pyramid per career. A pyramid is an ambitious system that one person really cares about and that winds up working well, but then just sits in the desert because nobody else cares the same way. This happens usually just after leaving graduate school." [3]
"In general, status-conscious places are miserable for everyone, and the more, the worse." [3, next page]
Gatekeeping is predictable from the incentive structure: "For all the high-level talk about how we need to plug the leaks in our STEM education pipeline, not only are we not plugging the holes, we're proud of how fast the pipeline is leaking." [4]
"So why am I not an academic? There are many factors, and starting Tarsnap is certainly one; but most of them can be summarized as 'academia is a lousy place to do novel research'." [5]
"...whereas Newton could say, 'If I have seen a little farther than others, it is because I have stood on the shoulders of giants,' I am forced to say, 'Today we stand on each other's feet.'" [6]
[0] http://www.paulgraham.com/say.html
[1] https://caseyhandmer.wordpress.com/2019/08/09/caltech-astrop...
[2] https://www.briantimar.com/notes/mimetic/mimetic/
[3] Phillip Hobbs, "Building Electrooptical systems: making it all work" 2nd Ed, p392
[4] https://danluu.com/teach-debugging/
[5] http://www.daemonology.net/blog/2020-09-20-On-the-use-of-a-l...
[6] Richard Hamming 1968 Turing Award lecture, Journal of the ACM 16 (1), January 1969, p. 3–12
It is several repeated and very costly attempts that I made to do just that which leads me to give the advice I did.
The pyramid quote is an interesting one. Obviously there is a tension between being passionate about an idea/goal/cause but not being overly siloed. It seems the best-case scenario is: pick your passion, find some people who're thinking in the same general direction, and compromise the vision among yourselves.
Let's just say that the thought of solving some of the problems I'm interested in from outside academia has occurred to me. But I'm sure it's not all sunshine and rainbows on the outside, either, and moving from academia whose primary motivator is risk aversion to something like a startup is an extreme culture shock, the more so because my objective would be building something real, rather than bilking gullible VCs into an acquihire.
Really good thoughts there.
In my experience, this fact was the #1 reason why some peers dropped out of PhD programs. They joined expecting a continuation of undergraduate education, which consists largely of recapitulating what appears in the secondary literature. Instead, what they got in graduate school was the expectation that they would be producing the primary literature. That's a very different game.
It was a game these peers discovered they hated playing. Nothing in college can prepare you for the isolation of spending your time becoming the world's expert on a narrow technical topic. Your usual reinforcement mechanisms of approval from family and friends gives way to slight comprehension at best. Then there is all of the alone time doing research requires. But I suspect the hardest part of all is the seemingly endless lineup of dead ends and false hope. Not only is success not assured, you often have no idea whether the result will have any utility even if you succeed.
Then, just when you've gotten the hang of this finding answers game you discover that the real expectation is to be the one who formulates good questions. The kinds of questions that, although they will certainly involve dead ends, will ultimately pay off in some meaningful way. Very little in a bachelor's prepares you for doing this. It's a hard-won skill that comes from a round or two (or three or four) of months (or years) spent answering questions that nobody cares about. A lot hinges on your relationship with your advisor on this one.
The PhD isn't just a bachelors degree but harder. It's a completely different animal. The skills in this article are very useful toward that end. But there's a lot more to the story when it comes to skills for finding answers to those unanswered questions, and formulating worthwhile questions without answers.
The benefit of all of this work and discomfort is that you come away with the ability to answer worthwhile questions that haven't yet been answered. And that's a highly transferrable and applicable skill.
Hit the nail on the head. I would like to add one point though - it's not just the unanswered questions, one sometimes doesn't even know which questions are unanswered.
Typically, up until a Ph.D - you are given a question and then asked for an answer which more often than not exists. Suddenly, in a Ph.D - not only do you not know the answer, you don't know the question too. The craft to come up with an important question, create a well-defined scope and then answer the question from different perspectives is the heart of a Ph.D program. The true skill is the ability to "learn to learn". The transferrable skill is to probe around for questions which are important, define them and then go ahead to answer them.
Mirroring what tasogare said: There are a lot of research professors who will not give you the flexibility of finding the question. They often are paying you to be an RA, and will want you to work on their topics, not yours.
This may vary per discipline. In the circles I was in, this was the norm, though. Some professors were open to you choosing your own topic, but the "contract" was similar: If they are funding your research, then you should work on your own topic "on your own time".
"Then, just when you've gotten the hang of this finding answers game you discover that the real expectation is to be the one who formulates good questions."
And that is where I personally failed.
On the other hand, there's that funny moment...
One of the things I've heard repeatedly from pilots is that first solo flight changes everything. Before that, you're just some human. Afterwards, you are some human who can fly. Everything is somehow different, although I've never seen anyone really successfully describe how. I suspect it's different for everyone. But then I'm not a pilot.
In your dissertation defense, someone whose knowledge and intelligence you respect immensely will ask a difficult question. When you answer that question confidently and to their satisfaction, the world is a different place. For one thing, you're no longer student and teacher; you are peers. But that's not all it is.
I hated this pressure. I wrote up the core of my thesis as a manuscript for a second-tier journal, but my advisor though I had a shot at a first-tier publication. I disagreed, but I rewrote the paper anyway, and had to significantly rework/descope it. It ultimately wasn't accepted for the first-tier journal, so I rewrote it a second time for the original journal. The whole process was immensely frustrating (cat-herding coauthors, playing volleyball with editors/referees, trying to discern whether my concerns about overselling my results were legitimate issues of integrity vs. instances of imposter syndrome, ...).
I fell in love with the hard sciences because "reality must take precedence over public relations, for Nature cannot be fooled." [Richard Feynman] Finding out how much PR is actually involved was hugely disillusioning.
This is why I have come to see that PhDs can in some cases make excellent founders. Source: CS PhD turned founder ;-)
1. Presentations aren’t really about conveying information.
I sat though so many dull presentations, they were very informative but I can read a paper quicker than they can badly present the same information.
The best presentations were the ones that covered the whys of the work, the applications, the next steps, the specific problem areas - often these aren’t covered in the paper but, armed with that extra insight I am far more likely to read the paper and remember it.
Presentations are (as the author says) about telling stories.
2. Show up. So many PhDs waft around not doing a whole lot, and so land up being on the program forever. This only benefits the uni and is detrimental to the student. I noticed in the first month of my PhD that most people did a lot more work at the end than the beginning - so I flipped it, worked consistently from day one and got done in just under 3 years.
Carry this over to your daily life and it’s almost a super power for getting stuff done. Consistently showing up and plugging away in something reaps rewards.
Amen. PhD is a marathon. Other degrees may be a 100m or 400m race but PhD is about consistency.
To anyone reading this who is considering a PhD, start writing up your thesis as soon as you can, like 6 months in if you can and have enough to start. You can always go back and change when you’ve written but it makes life so much easier if you’re “always writing up” then you’re not terrified of starting.
Oh and yeah: 9 to 5, full time, give yourself a standard holiday allowance and stick to it.
As a faculty member, each of your three constituencies is almost completely invisible to the others. So each one thinks you work hardly at all. Only your family sees the total hours, and only your tenure and promotion committee sees the total contributions (and typically they up-weight research, so don't skimp there).
I think many of these points come down to confidence. When you are in the trenches, you really, really do know a lot, and you know it in incredible detail. In fact, in your career, if you leave academia you will probably never know a unique small "thing" in such detail ever again simply because you will have to make something as opposed to studying it. Not even your professor knows everything about what you do, and so she may give advice that seems to contradict what you think. It is vital that you trust yourself enough to speak up. Yes, the professor is really smart, and knows more than you, but she didn't spend 3 weeks in the lab wrestling with some optical setup like you did and you know some things better then her, better than anyone in fact. It's hard to admit, I know.
Also, you may really have wrong assumptions about the progress you're going to make in the project. You may feel very bad after a year of messing around while the prof thinks you're doing well. Talk about these feelings. The prof knows what's normal, you on the other hand may think you're the next Einstein (and assume Einstein wrote something great every other month) and constantly disappoint yourself.
It's really not. It was obvious to me about 9 months in that my advisor really didn't know all that much. The professors who really seemed to have technical chops were either new faculty still trying to get tenure, or the rare iconoclast who didn't play the game and had a single grad student. The tenured professors with large research labs were frankly better politicians than they were scientists.
Amen to that! It's better to have the discussion than to silently disagree (well, assuming your thesis advisor isn't a raging narcissist, and assuming you are sufficiently tactful about speaking up) because there's a chance you are mistaken & the feedback would be helpful.
>You may feel very bad after a year of messing around while the prof thinks you're doing well. Talk about these feelings.
Another one that I wish I had known (again, needs caveats about unhealthy advisors, though). It's easy to underestimate the scale of a task as a grad student (the devil is in the details), and to therefore bite off more than you can chew & feel guilty for choking.
That's also an advice I give to aspiring PhD students, look for a warm place, talk to the other PhD students about the working atmosphere. You don't want to end up a "measurement slave", as one of the 4 PhDs that (and I quote a prof during a talk) "was burned on this subject".
A professor in undergrad gave me the tip to get excited or even feign interest when reading dense written material in order to retain more.
After trying it throughout a difficult class I was amazed at how well it worked. I applied it to every other academic thing I didn’t want to do and noticed immediately how much easier and enjoyable school was. I still use the “fake excitement” trick for my work all the time.
Also, it’s kind of like a Trojan excitement because after I fake the intense interest I do genuinely become interested more often than not.
Maybe you have a more independent mindset having gone into a PhD program a little later than most, but the whole point of a PhD program (at least in the sciences) is that it’s an apprenticeship. You study under an established researcher using their grant, so it’s not “your” paper. You are supposed to work together using grant money from your advisor.
If you have obtained grant funding on your own and are working independently on a novel research project you thought of yourself, then you can call it your paper. But that scenario usually doesn’t happen, because it’s hard to come by funding without a good proposal, and it’s hard to write or qualify for a grant without the training one gets in a PhD program.
If you are working using grant money, lab equipment, lab space, data, models, software, or methods acquired and developed in your advisor’s lab, then even if you write an entire paper yourself it’s still both your names that go on the paper. I’ve had a few like that and was glad to share the credit, because it wouldn’t have been possible otherwise.
This could be hard to do such early in your life, as one does not have much experience. Usually it falls in one of two categories - either you are someone that can do the work but needs support and guidance, or you prefer working on your own, in which case a more hands-off supervisor would be OK.
If you are of the former type and find yourself working for a supervisor that doesn't offer much support, it will be very hard to finish anything, and most likely you will become demotivated and drop out. Likewise, if you want to try things on your own but your supervisor wants to dictate where to go next, there will be a lot of conflicts and even the possibility that they block the thesis until it is done their way.
Having other PhD colleagues around and bouncing ideas off of them is worth its weight in gold, make sure that there is at least one that is working on something similar as you are.
I'll add something else I have realised:
Your Gantt chart is not for you.
I hate Gantt charts - they're out of date the second they're created; they take too long to update; there's very little decent free software for them that everyone uses; etc etc.
But your supervisor will probably want to see one. Or your funder, or examiners, and so on.
That's the point: sometimes you just gotta transform information into the format that's expected. From your perspective it may be easier to say "I've completed task X but task Y will drag on for another two weeks" than it is to update a spreadsheet and render a Gantt chart, attach it to an email and stick it in a shared drive. But from the supervisor/funder/examiner perspective, they need a way to very rapidly assimilate complex detail and spot problems.
A lot of academia is about clear communication of complex material. Your supervisor probably has several students, as well multiple projects of their own, teaching duties, management duties, and so on. Your Gantt chart is for them, not for you!
Simple and obvious in hindsight, but it really helps me put aside the grinding resentment I feel whenever it comes to updating a Gantt chart :)
I left academia after a failed postdoc because I realized I had no clue how to conduct research on my own; I didn't know how to pick good research topics, or how to manage my time, or how to find people to collaborate with, or how to collaborate productively with someone for that matter.
I'm not sure if the fault was my supervisors or mine. I'm a bit "on the spectrum" and have lots of difficulties with social interaction, but I guess so do many other people drawn to technical fields and still they manage to navigate the system somehow. I certainly never sought for any kind of mentorship because I didn't realize it was needed and, also, because it felt extremely awkward.
Also, the whole academic system seemed a bit fucked up. People do research and write papers because they have to produce something measurable, not because the research they do is actually interesting or important. I published five papers during my PhD and I would say that maybe only one of them was slightly interesting or important, and even that could have been much better. All of the papers were published in proper, highly regarded journals (mostly Physical Review). Towards the end of the PhD I started having some vague ideas of stuff that would be _actually_ interesting and more worth my time, but also more difficult and less certain results. When was I supposed to do those? I was still in the mindset that I wanted to stay in academia so I couldn't take any risks.
Yes, so much of this. I think it's a direct consequence of your next point:
>I wanted to stay in academia so I couldn't take any risks.
That's how boring research gets prioritized.
Yes, I realized I was part of the problem, but couldn't help it (except by leaving). If it was only a bunch of PhD students and postdocs wasting their time, the boring research wouldn't be such a problem. It becomes a problem, however, when everyone is doing it and the actual good publications get drowned in noise.
Students, new employees, and other inexperienced folks need to be led initially, and then rapidly, transition into a self-directed paradigm. Success emerges if and only if the advisor and student recognize the need for this transition at a similar moment. The alternative is either the student who runs down rabbit holes repeatedly despite being guided elsewhere (those students tend to at least get SOMETHING done and while they take forever to graduate, do find some interesting results along the way) or the student who after a couple years is still just reading papers and waiting to be told what to do (these students often fail outright as advisors get fed up with the hand-holding).
The real question is whether they learn to focus efforts on the relevant goal (in which case, these original thinkers with innate curiosity can be fantastic hires) or continue their rabbit-hole-exploring ways (in which case they generate publications as post-docs, but generally struggle in the private sector where folks want THEIR questions answers ASAP). Which are you?
(Fascinating discussion!)
A useful side effect is that whenever I wasn't feeling really inspired, I could pick a paragraph at random and just fill it in. I would not call any of my paragraphs "filler" but there was stuff that needed to be written down, that didn't require profound brain work to produce.
Anyway, that's how we're supposed to write code, right? It was, 30 years ago. ;-)
For me, I started from the slides I had presented in my immediate group meetings (~6 ppl, including my advisor, typically once per week, 2-3 slides each) plus the larger group meetings (~40 ppl, including the lab director, typically twice per year, 20-30 slides each). That gave me bullet points and figures. I wrote one chapter at a time, starting with the central chapters & ending with the introduction & conclusion. I had a 6-month time table for writing, and I was only delayed 2 weeks in the end. Remaking figures and messing with LaTeX took more time than I wish it had.
I do the same when programming btw, my function names read like a story with their complexities hidden lower in the class/library. Yes I have function names that some may find ridiculously long but it helps me a lot.
\documentclass{report}
\usepackage{color}
\begin{document}
\newcommand{\topic}[1]{\color{red}\textbf{#1}\color{black}}
%\newcommand{\topic}[1]{#1}
\topic{Lorem ipsum dolor sit amet, consectetur
adipiscing elit.} Praesent vel consectetur est,
sed accumsan dolor.
\topic{In malesuada in nulla eget aliquam.} In
facilisis erat neque, non sollicitudin felis finibus a.
Sed pellentesque suscipit lorem, quis lacinia mi
suscipit at.
\end{document}The trainees supervisory committee is usually there to push them out but in many cases they also have a close relationship with the PI and aren't going to force a productive student to graduate. Those extra years are rarely useful for their overall career prospects.
I think students need to be aware of when they should draw the line and move on. Spending three more years in their PhD probably won't pay off nearly as much as three years of accumulated experience in industry job or in a post doctoral fellowship in a new lab.
I graduated in 6 years (including 2 years of coursework), which was the mode (not the median, though) for my department. The distribution skewed to the long side, and 5 years was the shortest I can recall.
(1) Role of Math. In most fields of research, the most respected research mathematizes the field, that is, makes progress with math techniques and results. So for Ph.D. research, try to have math play that role.
(2) Ugrad Preparation. To be successful with that role of math, have a good ugrad math background. Then maybe get some more math from independent study, work in a career, a Master's program, or whatever. Likely the math topics that both come first and are the most important are calculus and linear algebra.
(3) Find a Good Problem. In your career, independent study, whatever, find a good problem to solve. Pick a practical problem and intend to get an engineering Ph.D. where a solution to that problem is regarded as good research. Make some progress on solving the problem.
(4) Pick a University and a Department. Want a department that respects applied research, maybe in a school of engineering. Hopefully the university will state their standards for a Ph.D. dissertation, e.g., "An original contribution to knowledge worthy of publication." Look at their description of their Ph.D. qualifying exams. Do enough study at the ugrad or Master's level and/or independent study to be well prepared for the exams. If the department offers courses for preparation for the exams, in addition plan to take those courses.
(5) Enroll. Become a grad student in the chosen department.
(6) Progress. In your first year, take some courses, especially in subjects you already know well. Continue your research. Pass the qualifying exams. If you see some opportunities for doing some fast publishable research, as co-author, better as sole author, do that. Show the department that you have done publishable research. Then, sure, technically will have done a Ph.D. dissertation (I did that).
(7) Finish. In your second year, finish your research project, stand for an oral exam, and graduate. Of course, if there is any question about your research being publishable, then just PUBLISH it.
Done.
To give some context as to my experience:
- PhDs are funded. You get a stipend and tuition is paid for. This funding is either through a research assistantship (RA), or a teaching assistantship (TA). Either way you are expected to devote 20 hours a week to this task, and the rest would be devoted to your coursework. Typically you take 9 credits per semester for about 4 years, and then after you enter candidacy (you're not really considered a PhD candidate until you pass qualifiers, before then you're a mere PhD "student") you reduce that to a 1 credit "dissertation maintenance" per semester.
- Grant money is the lifeblood of a PhD granting research-focused department. Here's how the economy of a typical CS department works:
-- Newly hired faculty are given a "startup grant" that they use to bootstrap a lab. Their motivation is they want to get tenure in 6-8 years. To do that, they will need to justify to the Dean that they are capable of generating sufficient grant revenue.
-- Grant agencies award grants largely based on published research papers. Therefore the primary directive of a new academic is to publish research, and use that to obtain grants. Hence the phrase "Publish or perish"; if a researcher fails to get enough grants when the tenure clock is up, they will usually be put out to pasture; failing to get tenure is the death knell for a young academic's career.
-- So they hire a couple PhD students as RAs and they work on producing research papers for conferences. The new academic uses the published research in grant applications (the first target is usually the CAREER award). Soon enough grant this grant money is flowing to the researcher and they use it to pay for all sorts of things. Chiefly though, it is used to pay for the stipends and tuition of graduate RAs.
- As an RA, you will be expected to spend 20 hours per week on grant funded research. This means you don't have room to explore your own research topics! All of the grant money is allocated for the funded grant research, not your own whims. The best you can do is carve out some interesting angle on the research that you can call your own.
- By the time you get to maintaining your candidacy, you're already knee deep in publications on the funded research project. The path of least resistance at this point is to bundle them up into a dissertation and defend it.
- If you have your own research agenda, now is the time to execute it as a faculty member at another University. One of their primary concerns during hiring will be: "How is your research agenda different from your advisors?" You will perhaps not be surprised to find that many candidates fresh out of a PhD program will not have their own original thoughts yet. This is why many departments prefer that a new PhD actually take some time doing a postdoc where they can gain some independence from their mentor.
Anyway, what I would say is that instead of picking a problem or a university or a department, pick a person you want to work with for the next 5-8+ years. Like I said, 2 years is very atypical. In my department, we have built in buffers that would make the minimum I think 3 years with a Master's, and even then I think the typical time would be 4 years.
For funding, I got tuition but no stipend.
For an advisor, I didn't want one or really have one. On paper I had two advisors, but I brought my own problem, did my own research, both for the dissertation and some publishable research I did before the qualifying exams, and didn't want, need, or get any advice from either of my advisors.
The best I got from my Ph.D. work was just terrific, fantastically good, powerful, valuable material. But there was a downside: I was attacked by some profs who resented me, wanted me to fail, and tried hard to have me fail. The actual academic work, including the research, was easy; most of the effort was just defending myself from attacks.
I do not now nor have I ever had any desire to be a college professor. I got a Ph.D. to be better qualified for a good career in applied math and computing I had going before my Ph.D.
Now I'm in business for myself. Math is not all there is to my business, but it is an advantage, likely a crucial one. The math is some math I derived together with some advanced pure math, a bit amazing, long in some advanced textbooks but not well appreciated for its potential for applications. The business is based on computing, and I've written all the code, all in Microsoft's .NET (which I like). The computer science used is just (a) the heap data structure used as a priority queue and (b) AVL trees for a cache. At one point I make use of LINPACK -- downloaded the Fortran version; got the Bell Labs program F2C to translate the Fortran code to C; compiled the C code as a DLL; and call it with Microsoft's platform invoke.
I've published in applied math (optimization), mathematical statistics (multivariate, distribution-free), and artificial intelligence. I didn't publish my dissertation research because I wanted, maybe, to SELL it and certainly didn't want to give it away.
Other people generally don't care about your personal struggles with a problem, so leave them out. Or at the very least don't lead with them. Lead with something that piques the interest of your target audience.
There’s nothing better than a student you wind up and they go off and solve a bunch of problems in interesting ways. They’re having fun, you’re workload is reduced and there’s even potential for a publication. Meetings are indeed about giving feedback and learning on both sides.
In contrast other students show up empty handed, unmotivated and expect a list of instructions some of which they might attempt. You feel like repeating yourself constantly and that they are not listening.
What do you do in that situation? When I encountered it, I assumed it was a communication problem at first, so I asked the student to take notes on what I had requested. This didn't help. I then realized they didn't understand what I had asked for in the first place. I suppose I could have requested they repeat my instructions back in their own words. Ultimately, I figured it was a lack of motivation, b/c they would half-jokingly complain about whatever I requested, and I usually found them watching videos on their computer when I walked by.
Sometimes you need to have a talk about what is going on. This usually happens after Xmas when they screw up their interim report/presentation. They get to see their peers succeed so it’s a strong motivator.
With PhD students it’s even tougher. You have to work with them for years and build them up. Some lack confidence, some are over confident but can’t actually do anything. You need to avoid doing too much for them — that’s the hardest part for me.
Occasionally you get postdocs that are difficult. They really should know better at this stage and should not have been hired.
I didn't, and simply tried to power ahead on the assumption I'd pull it out of the fire: this was absolutely the wrong conclusion. You already have a university degree, and you'll get paid more in industry: the right answer is to abandon ship it you're not looking at a clear path ahead by then.
In my opinion, there is nothing unique that can be learned only through a PhD for a successful career (except maybe for a tiny slice of outlier of CS researchers). Most people will be well better served to take a job that provides some agency, or better try to start a company and fail. They can learn a lot more this way without jeopardizing their financial future.
"These lessons are so ingrained into me now that I'm shocked when I find out that not everyone knows them! I think they can be applied to virtually any office job."
Taking a job that provides some agency is harder than it sounds. As is starting a company and failing without jeopardizing one's financial future. (And not everyone is really enthusiastic about learning those lessons that can only be learned that way.)
Wholeheartedly agree.
This is why there is a term for people who do the whole program but drop out without finishing the dissertation: ABD (all but dissertation). It’s the one non-degree people feel justified to list on their resume, because it takes at least 4 years to get there, and it’s still quite an achievement.
I was ABD for 3 years when I got bored, and I almost quit. I figured since I had all the skills, it didn’t matter that I didn’t have the degree. It’s just a meaningless credential. I asked a friend of mine who had gotten his degree whether it was worth it, and he said “Don’t do it, the plus side isn’t that great”
Then I went to his wedding. He was the only PhD in his family, and his mother made the DJ introduce him as “Doctor”. What he considered a meaningless credential made his whole family so happy and proud. That moment made me change my mind, and I finished my PhD.
And you know what, he was wrong about the credential being meaningless. Employers look at you differently when you are ABD versus PhD. He didn’t experience that because he was never ABD. Truly it was like night and day. Governments care when applying for visas. Grant agencies care. There is also a lucrative market for expert opinions, and ABD are not considered at all in this market. Credentials matter in our society, even if they don’t matter so much in the tech sector.
Anyway, I hope something I said here will convince your wife to stick it out! If you want a specific tip, I would say take a leave of absence. For me I could take up to 2 years off no questions asked, and rejoin. If her school has a similar policy, she can use that time to recharge, and come back fresh and ready to bang out her dissertation.
A secret that no one often admits is that most PhDs get more out of the credential than advertised, because they aren't a von Neumann or a Fermi, whose credentials never mattered because everybody knew they were one in a billion geniuses.
Thanks for the thoughtful reply, I'll share your words with her.
[PhD candidate] is finishing up [gender pronoun] PhD in [field] and I can tell [gender pronoun]'s getting bored.
I just turned your statement into a template that works for every PhD candidate of the last 100 years.
Is there such a place today as a professional?
There was just a Reddit post saying that 54% of US adults have a reading level equal to or below a sixth-grade level according to the US Department of Education. Many communication problems can be attributed to differences in prose, document, and numeracy literacy.
"If we want to have an educated citizenship in a modern technological society, we need to teach them three things: reading, writing, and statistical thinking." – H. G. Wells
At the same time, it will not teach you some things you'd pick up in industry - team work in particular.
What is the appeal of posting your daily progress on a public form? Do you not feel this to be a kind of invasion of your privacy? Is there some benefit that isn't immediately clear?
I've put that on my list of things to distil, review, and put into action.