This is great and exactly captures the PhD experience. Both in the simulator and in real life, I mostly survived until the end by slacking off frequently, and needed around 5 years.
Some highlights:
> INBOX: Based on the reviewers' comments, we regret to inform you that your manuscript has been REJECTED for publication. One of the reviewers pointed out that there is no comparison with a state-of-art method.
> You came up with a bunch of ideas. However, upon further searching, you found that they have already been done before.
> You found the missing piece during a shower. You develop one of your preliminary results into a major result.
> You found one of your ideas appears in a recently published paper. You can no longer work on it.
> Three years passed. You have witnessed many graduations. You began to worry about whether your can graduate on time.
> The simulation took a much longer time than you expected. The results are not available yet.
What was missing:
1.) Growing feeling of getting too old
2.) Growing family obligations (marriage, kids, trying to write a thesis at 3am with a crying baby next room)
3.) Questions asked by friends and relatives regarding progress
One dynamic I experienced that also isn't in the simulation: if you focus too much on classwork early on in order to pass your RPE, it can actually be hard to find an advisor. Classwork is basically dead-end work and the more you focus on it the less you have to show for yourself when trying to convince an advisor to work with you. Your goal should be to optimize for doing just well enough to pass your classwork.
Also, random catalysmic events, like in year 4 your advisor accepts a job at a different university in another state.
I had picked my advisor at the start of my PhD. I also had 2 backups. My pick was on sabbatical my first year. He and I agreed I'd load up on the required classes that year.
He e-mailed me right before the year ended saying he had changed his mind and didn't want any more grad students, basically dumping me.
Right around the same time, my first backup decided to retire.
My second backup passed away.
I was left no longer making "sufficient progress" and no path to do so, losing my financial aid.
Thank you! I didn't have many options at the time, having a small family to provide for, so I went back to work as a software developer. The career has been good. I regret not being able to be a professor and devote more time to research, but I also try to make opportunities for those kinds activities in other ways.
This also depends on the field. I think this is good advice in fields where grad students are primarily there to help with grant-funded research. In those fields, the course and prelim requirements are reasonable because professors need warm bodies doing work. Eg, CS.
It's less good advice in fields where grad student research output doesn't matter as much, and where students do more teaching instead. Those fields tend to make much more aggressive use of weed-out exams to ensure that they have enough young grad students to meet teaching demand but not so many older (>=3yr) grad students that they saturate advising capacity. Mathematics in particular comes to mind.
Generally, the focus here should be on:
1) Not bombing any classes (i.e. A/A- in all, maybe a B+ in one; a B or below is failing)
2) Doing very good work and trying to write an original paper for professors that you want to work with while doing just enough to get by in other classes [this is in part how you figure out who you want to work with]
3) Being good enough with the literature to pass the comprehensive exams (or, as another comment points out, have some kind of protection from a sponsor; it is not uncommon to have profs use comps as a chance to take out students they don't like for various reasons, even as small as "they do X field, which I don't like" or "they work with Y, who really gets on my nerves).
Of course there's plenty of additional ways to derail this as well, including advisor moving, advisor getting into a fight with the rest of the department, advisor giving poor advice, advisor deciding that they don't like you, etc.
It really makes you wonder if the university should just have a mechanism to "fire" a grad student rather than pretending that these events aren't simply a mechanism to "fire" someone because they didn't pass X hurdle.
If the advisors can vouch for, or strike a student regardless of their qual performance - then why not simply have an end of year performance review?
For many schools that’s basically their qualifying exam. Normally multiple professors are involved so that your advisor can’t fire you unjustly, but if you don’t demonstrate you are up to standards on the exam and your advisor doesn’t go to bat for you in their deliberations, you will fail. Normally you have a chance to retake the exam, but two strikes and you’re out.
In my program we had annual committee reviews as well as a review submitted to the program chair and graduate school of the student by their advisor (with the student providing both a self-review and review of their advisor). Ultimately, unless you’re in a sub-field with many faculty, it is hard to get an accurate evaluation from three professors. My other committee members could understand the big picture of my work but they weren’t experts on the specifics, and they were the best equipped faculty in the department to be on my committee besides my advisor. The goal is to make sure that there is a paper trail and multiple professors aware of your progress (or lack thereof), so your advisor can’t just give you the boot for something tertiary like not watching his dog during a holiday weekend.
Professors are aware of their problematic peers in the department. Even if they can’t fire them outright (tenure has pros and cons), they can steer students away from them to more supportive professors (or give you a hint that maybe you should consider a different school during your visit day). Our program chair was very good at helping relocating students who initially started in the lab of one or two bad actors.
Most depts do have some kind of official review, but it's more of a formality. I think they're also concerned about how students would react if they suggest that academia isn't for them directly. So instead they resort to more passive-aggressive or arbitrary measures.
On the other hand, not all departments are good fits with students and there's a very wide asymmetry in information between many new students and programs, even if you "do your research" beforehand, given just how specialized these disciplines are at a high level. It would be nice if transferring programs was made easier and if more departments would just agree to help students "master out" and look for jobs rather than discard them like roadkill.
> Classwork is basically dead-end work and the more you focus on it the less you have to show for yourself when trying to convince an advisor to work with you.
nearly half of my year didn't get this and had to master out when we got to quals.
Are those different things? At departments where quals have high failure rates, it's really more of an annual layoff than anything else.
In many programs, the department aims to admit far more people than will pass the quals. They need the Calculus and Pre-calculus TAs but do not have the advising capacity.
Even if everyone gets a 95% on the quals, the majority will "fail" by necessity because the department simply does not have the advising capacity for the number of TAs they need. Of course, the department typically designs the quals to these needs either explicitly or implicitly.
This is usually at least implicitly understood by the faculty, who will navigate it when absolutely necessary. For example, I've seen it happen that if a professor really needs a student and vouches for/protects them (eg because the research is computational and the student came from 5 years at Google), then the student gets more goes at the plate on quals than is typical.
Depends on the school. My program requires you have an advisor before our version of quals. Our exam was also a research presentation followed by an oral exam where you had the pleasure of doing often a painful amount of algebra on a blackboard. It was also the culture that, while your advisor could ask you questions, they rarely would unless they were helpful (maybe a softball confidence booster or simple version of another question to get you started down the right track) or leading questions for you to talk about something not in your talk. People were largely concerned about being failed by the other examiners, not their advisor at that stage.
However, we were a small department and your acceptance was predicated on at least one faculty member wanting you to join their lab. Some people moved around within their first year, but the majority stayed with the first group they joined.
er, right, what other people call quals we called prelims. our quals were a presentation of early stage work, so when the deadlines rolled around, they didn't have an advisor, or hadn't been working with them long enough to have any results.
It's funny, my CS program in US you had to have an advisor by end of your first year and your quals were basically the thesis proposal you did with your advisor.
This would be incredibly bad advice in half of Physics and most of Math. An adviser would simply not trust a graduate student with middling grades to be competent enough to work with.
I think this depends on the field. For example in CS, my advisor straight up told me multiple times to stop worry about class work. His exact statement is that "There isn't anything more that you will learn in classes that you won't learn in greater detail doing research".
His logic is that when you are doing research, you are pushing the envelope into new territory that can't be taught in a classroom. When you are in a classroom you are learning old material that is already well-known and established.
This is very true in CS. But far from true in Math and Physics where there probably is a lot of advanced learning available in classes. The few classes I had that he actually endorsed being "worth your time" were Math classes focused around encryption (of which I took 3 different ones).
But my advisor was unique because he was 100% there for the research. He only taught because the university forced him to. He lived and breathed research and that was the only reason he was in academia. He was truly passionate and worked 10+ hours a day on research, but thats why he was there. He had a very low opinion of classroom teaching.
As a counterpoint, I knew a physics prof that would drop any grad students who got above a B average, since it meant the student had bad time management. Bad time management being defined by spending more tine outside the lab than strictly necessary.
Then again, knowing that that @£&$€¥ would drop you might make it a good plan.
IME it's more that the advisor doesn't trust the student to make it through the annual layoffs (quals culling), and only wants to invest in people who they know will be around long-term.
At least in the poor (and honestly mostly useless) parts of Mathematics. Maybe Physics is less poor.
(Fortunately I was in CS, where the research output is actually needed by society and usually not pure masturbation, so the attitude toward coursework was "do well at what you need, enjoy what you want, and ignore what you don't need or want"
Most universities do not have "quals culling" and most universities that have "quals" (not that common anymore) do not use them for culling. There are a few notorious exceptions though.
This emphasizes how much you need to know before you even get into a program. If you don't know that much, you NEED those classes to just catch up to your peers as to understanding what the world even says about various things at a foundational level. The weight is so much easier to carry if you go in with a certain level of knowledge so that you can slack in classes if you need to rest.
This. Most grad school classes are poorly taught and the professors indifferent or discouraging to actually helping you learn. PhD students are assumed to be capable of learning these things on their own or already knowing them. If you are encountering things for the first time, you'll likely be behind.
In contrast, if you come in mostly ready to go and these classes are just refreshers, you can spend time in that class working on actual research and impressing the prof as well as not panicking if/when you realize you don't understand what's going on.
Every department I've worked in mandates 2 supervisors to mitigate against this, because it's reasonably common for people to move departments, go on sabbatical or just quit. Even with tenure, life happens and people need to leave their jobs. In theory, the department shouldn't allow advisors to take on more students if they're close to retirement though.
Turkish university system solved that problem by stipulating that thesis supervision and advice duties survive retirement unless the student explicitly requests otherwise, and end only if the student finishes or the supervisor/advisor is fired (not resigned!) or dead.
That depends on your department and your field. Even though, on paper, I had a year to pick an advisor, I worked with mine from day 1 (or day -n since he first sent me research papers and discussed ways to get started on my project before my first semester even started). My department was fairly small, though, so you getting admitted meant at least professor specifically was interested in you joining. Professors at larger schools will put on their website not to even contact them unless you have been admitted, and their departments are large enough that only a portion of faculty members are involved in admission decisions. In that case, your advisor of choice may not know about you at all before you enroll and thus you need to fight for a spot in their group among your cohort.
Ironically universities have already found a way to defeat that behavior, too:
At some places, advisors now also consider a list of students ranked by grades. I have seen advisorship being offered only to the top student in the Professor's class.
If you lack ex-ante information how and where your grade rank matters in a year, this just adds a fun new challenge to the first year PhD!
> You found one of your ideas appears in a recently published paper. You can no longer work on it.
This is one of the things I thought of right away when ChatGPT got released last year. "God, there's probably so many PhD candidates right now in NLP feeling despair like all their work was pointless ...as if million of voices cried out in terror and were suddenly silenced."
It's hard in the moment to know whether what you're working on has any utility. So just do your best and keep chugging!
I met someone recently who finished their PhD in computer vision related work a couple years ago and she said all of her specialization now felt useless, but that her PhD was still useful for understanding the fundamentals for a job she now has but does absolutely nothing with her research experience.
HmThat very heavily depends on the specialization. E.g, you did image processing, basically useless now, you did GANs, diffusion models took over. It's like that for probably most phds but the research skills, writing skills etc are with you forever.
And this attitude, my friends, is the reason why so much software out there is so bad.
We need more of a math mindset when developing software. What can we be sure about, what are the invariants, what can we prove? There is so much crap out there that somebody lacking understanding just tried to wing, and I'm constantly ashamed of it.
Number theory had no applications for centuries. Now, cryptography is based on it and the modern internet would be unthinkable without.
Foundational research does often not provide immediate applications. Still, if we don't do it, out understanding of the world is lacking and it hurts us later down the road.
While there certainly exists math for the sake of math, there is a trickle down effect that is quite real (there’s also a trickle up effect that is real but that’s unrelated). Someone does some math for the sake of math. Later on, someone who is slightly more applied sees a link between that math and a more applied problem they’re working on. If the idea is truly useful, it propagates down all the way to application-focused practitioners. Researchers exist on a spectrum, generally, between pure theory and pure application.
Math has no application until you find an application for it. Differential equations are just equations until you pair them with physics. Formal logic is just an abstract discussion of human reasoning until you build a circuit, etc.
One wonders if trickle down mathematics is any more efficient than trickle down economics. It seems like we might be better off not funding pure math, as forcing function to coerce those minds to work on more applied problems directly, instead of relying on this random serendipity.
It seems like I might be better off picking the winning lottery numbers directly instead of relying on the random serendipity of guessing them and most of the time being wrong.
Its sort of a mix of a lot of small things - 1) The coming conferences will be flooded with LLM analysis, so the space will be heavily saturated and more difficult to find a significant contribution; 2) LLMs are a new model that you might need to include in your analysis, which means learning about and becoming familiar with them; 3) your work might get overshadowed because its now obsolete in the land of LLMs
A slight equivalent I can think about would be the emergence of neural networks. When I was working on my Masters on face recognition, neural networks were not the major force they are now. Facial landmarks used a combination of haar features and edge detection. These methods weren't outright abandoned, but if NNs had taken off during my research, then I would have had to restart my work.
> 3.) Questions asked by friends and relatives regarding progress
This one in particular had me temporarily cut off contact with people who could not be bothered to remember that I had no interest in answering this question!
I would also add that the hope trajectory is quite right in the simulation. You really should start quite high and it starts dropping until your first conference, but then towards the middle of the PhD it gets very low. It only really goes up again when the end is in sight.
The hope level can be lowest (and cynicism maximal) late and at then end when one is the senior student and the major (only?) contributor in the lab or key project with no one coming up behind. A weak thesis committee won’t stand up to the PI to drop the cycle of “just address this loose end” tasks. Meanwhile relatively non- or lowly- productive fellow grad students in the program are given quick PhDs in other labs because the labs are underfunded and those PIs don’t want the burden of retaining or the stigma of failing those students, and …
Wow—-pardon the rant I’m having a flashback. I’m going to go exercise my anxiety away,
Yeah that’s how it went for me. My confidence was very high until I finished my qualifying exam and just had to sit there trying to solve a novel problem for over a year. Eventually I learned enough through trial and error that I could work productively in that space, but doing well in classes often does not translate to immediate research success and there were dark days and many therapy appointments in the middle.
During the PhD, I was a TA and instructor on record for several classes. Schools may have some form of mentor teaching assistantship that lets you get experience teaching while in the program. I think I taught ~6 courses by the time I graduated.
It can also help to position yourself in the "education" research space for your field. There is a strong CS education research space, so you can incorporate your classroom as your "lab", though you'll want to study up on Cognitive Sciences to ensure your findings support current literature. My publication count is much lower than my peers, but I was still able to receive several offers for teaching faculty positions.
Teaching faculty positions are available, though not in as much demand as traditional research oriented profs. However, I know at least in CS there are several universities looking for them. Likewise, by situating yourself in the education space, you can land a research prof position while still focusing on education. If you get funding, then you can buy out course obligations so you can specialize in teaching a single class.
A teaching university and not a research university. You can / will still do some research but your job is teaching students not doing research. The pay is generally better, but of course, you will have to actually teach a lot and have a lot of office hours. Maybe once every few years you can work out a research semester. The initial pay is better but less so the opportunities for advancement as you won't be publishing much. That makes it harder to differentiate on anything other than time.
I'm not sure the salaries are better. Most R1s are now offering 90-120k starting in my field, but regional teaching Us start around 50-60k, with liberal arts colleges in the 50-80k range.
The point about the lack of opportunities for advancement/moving due to the course preps and teaching taking up your time is very true. While your friends at R1s are on pre-tenure sabbaticals, getting course buyouts, and teaching a nice grad seminar for a semester, you might be doing 3-4 new preps a year and likely getting piled with service work.
If you want to have a tenure track "professor" position focused on teaching in a top-tier university, you need to be a great researcher as teaching skills are not considered much -- you just get to decide to focus on teaching after you get tenure. Thankfully, many universities (even the prestigious ones) are now starting to hire more semi-permanent teaching-focused staff (and some even use the title professor for these). You do not get as much independence in such a position, especially if you want to make a class for more senior students, but it is a good middle ground. Or you can be a professor at a school that is not in the rat-race to be "top-tier research institution" - you still need to have some small research output (but that is actually an awesome way to introduce a couple of undergrads a year to research) and you get to focus on making awesome classes (of course, there is still the expectation that you have a PhD to apply for these positions, but at these places your teaching experience is actually taken seriously in the hiring process).
As to what to do during your PhD: find an advisor that is happy to have one or two students focused on teaching and outreach (they would like to have that because when applying for grants it makes it easier for them to explain how they have broader impact, pointing to your work).
> If you want to have a tenure track "professor" position focused on teaching in a top-tier university, you need to be a great researcher as teaching skills are not considered much
Except that UC Berkeley most definitely is “in the rat-race to be "top-tier research institution" (probably more accurately described as one of the rat-race winners in many fields) - it’s definitely important that top-tier research institutions also provide quality teaching.
We do agree on this. My second sentence is exactly what you just said:
> Thankfully, many universities (even the prestigious ones) are now starting to hire more semi-permanent teaching-focused staff (and some even use the title professor for these).
In academia, your Resume/CV is basically a list of what you have published.
Even if you are an awesome teacher, you are going to be required to continue publishing a minimum amount every few years and you will be hired based on what you published.
Sorry, but that's just academia. If you want to teach without doing research, then maybe look at Community Colleges, High Schools, or getting a job at a corporate job and being an Adjunct Professor for 1-2 classes a semester.
There are also smaller (typically private) colleges and universities that heavily focus on their undergrad programs. The Jesuits seem to lean into this style with both Santa Clara U. in the Bay Area and Loyola Marymount U. in LA falling into this pile. Research at these institutions definitely ends up taking a secondary role.
Tried that, the university considered lecturers to be disposable if there was a chance to replace them with a tenure-track who could get grants, and told me I could come back if I got a PhD.
As a former PhD student who is now faculty, I have to say that the pace of the game is one of the most realistic aspects. Every small step forward takes about a month, it may or may not pan out, but it passes in the blink of an eye.
It's a game, so it can't model everything. But I thought the biggest missing thing was "leveling up." As you accomplish more, you should have a higher likelihood of future success, and your hope should increase as you gain confidence and experience.
That's how a PhD works -- those who can get early wins (or stick through a lot of bad bounces) can build on success will finish well.
To rip off Tolstoy, "Happy PhDs are all alike; each unhappy PhD is unhappy in its own way."
Building on early success isn’t even easy. I had some early success in mine but then years of stagnation until I developed enough understanding to iterate in a way that didn’t feel like a trivial waste of time.
On the other end, the suffering paid off. I’m a much better thinker and researcher for it. However, it was brutal getting there.
What I found interesting and I think is true for almost everyone is that doing a PhD is hard, but it will likely be hard for different reasons than you expect. Because of the PhD students I knew as an undergrad and their experiences, I expected to be grinding out work in lab 12 hours a day. My advisor didn’t push me that way (thankfully), and gave me a lot of freedom, but that also meant having very few training wheels and guidance (I liked him as an advisor and he cared / wanted to help as he could, but I got into topics he didn’t know much more about than I did for a long time and I just had to figure it out myself). As a result, my PhD was less of a death march but more a constant battle with existential dread stemming from the uncertainty of whether I’d ever figure things out.
It's interesting because I know maybe two dozen people with PhDs and every single one of them has a story about a moment of hitting rock bottom during the process and losing all hope. Obviously they all pulled through and make it out to the other side but it really doesn't sound like a pleasant experience.
It’s not even necessarily the program, but the nature of research. I liked my advisor a lot and he was helpful but at some point you need to figure out how to fly out of the nest and they can’t do it for you. During my dark period I ended up in an outpatient therapy program because my anxiety was so bad some days I wasn’t leaving my bed. My failure to figure out my problem at the time (even with a good advisor) had eradicated my self-esteem. I came in feeling a vocational calling to do research and I was just not getting anywhere with it.
The two comparisons I always made were a priest, who felt called by god to be a man of the cloth his whole life, losing his faith and the part in Moneyball where Brad Pitts character reflects on skipping college to sign a contract has a hot baseball prospect out of high school, yet being unable to succeed in the bigs.
Eventually, in conjunction with therapy and medication, I reached a critical mass of knowledge where I became, what I’d like to think at least, a good researcher. The process was just painful and I’m not sure how anyone could have made it easier.
She's got her bachelors back in 2010 and got a Masters while working full time. This part was brutal, but not technically PhD yet. She's in Health Policy, a lot of statistics and junk.
Anyway, she works for some special interest think-tank for a bit, works on insurance company some other bit, and finally settles down in the CDC where her skills in statistics / health policy were very much appreciated. She's getting to a point where it takes a Ph.D however before she can move forward with her career (she's already surrounded by Ph.Ds, and she sticks out in a bad way by not having one), so she's going for her Ph.D.
From her side of the aisle, she's seeing a whole bunch of silly 20-something year olds who don't even know what the field of Health Policy is about, trying to create Ph.D Thesis topics that have obviously no relevance to anybody in any of the fields she's ever worked in (politics, insurance, or CDC).
Meanwhile, her first idea was basically "Think of something CDC is blind at, which she can think of rather easily because she's worked there for 5+ years and everyone at the office is basically spitballing complaints about the CDC's statistics every damn day", and propose it as a Ph.D thesis.
Granted, her day-to-day work is filled with constantly interacting with Ph.Ds who are interested in improving the CDC's statistical collection techniques / improving accuracy / finding new ways to slice the data and innovation. That's literally her job. And those subjects just so happen to be very useful Ph.D thesis material for advancing the state of Health Policy.
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How much blood, sweat, and tears are we setting up Ph.D candidates for because they're straight-out-of bachelors with no real world experience or knowledge of their damn field?
Some of these things _are_ easy to figure out after you've got 5 to 10 years of real world experience.
The treadmill of Bachelors -> Masters -> Ph.D is broken. It probably needs to be Bachelors -> Real world experience -> Masters -> Real World Experience -> Ph.D.
This "Read paper -> Think of idea -> Woops, someone already did it -> Read another paper" loop from the video game, is that how most Ph.Ds try to come up with their thesis? Isn't that obviously broken compared to other "life-loops"?
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Ex: her office solved the question of "how to report statistics within one month to policy makers", because as late as 2018 or so, CDC was still on a yearly schedule of death statistics releases.
Imagine if we were still on the yearly-schedule when COVID19 happened, instead of the rapid schedule of monthly-statistics that we actually had! Monthly statistics, much like Inflation NowCasting, is actually a forecast / prediction because not all the data is in. But coming up with a forecast for this month (or last month) of data is still a problem that needed to be solved, especially in a way that policy makers would accept in a political environment where everyone's nitpicking at the details.
There's so many blind-spots and questions about how to improve statistics and statistical reporting at the Ph.D level in that field. But you are only aware of these blind-spots if you actually work in the field for a bit.
>It probably needs to be Bachelors -> Real world experience -> Masters -> Real World Experience -> Ph.D.
This was my path and my experience largely mirrored your sisters. I came to my program with a decade+ of industry work and I think that was invaluable to understanding the context of what problems are of interest. When I eventually matriculated to a position that valued PhDs, I now had a pretty concrete handle on what problems were enough of a stretch to be useful to a thesis, but not so far away as to be unrealistic. I also had a way to fund my studies without the burden of teaching and while making better pay. The younger cohort I worked with seemed to struggle because they often lacked a grounding in understanding real and feasible problems. So they were left bouncing between one half-baked idea to the next. That's what a lot of research is, of course, but it also left many to be either dropped or leave the program willingly.
I think you're right that we do a disservice to treat the bachelors >> masters >> PhD as a template to follow. There's lots of ways to skin the proverbial cat.
I know people who quit and were glad that they did so. I know people who graduated, but with the realization that research wasn't for them, and they pivoted into something else. But I honestly can't think of anyone who stuck through it and was worse off afterwards.
So you're saying you've heard of people who quit and were successful and you've heard of ones who graduated and pivoted and were successful, but not ones who graduated and weren't successful. It's almost like when you hear of someone it's more likely because they were successful in some way and the unsuccessful ones you hear less often.
That was...a lot more straightforward than I thought.
First try: Year 4 Month 5
Second try: a lot more things went wrong. Year 5 Month 11.
Third try: Year 5 Month 11.
I just followed these rules:
- Study for the qualifying exam until I'm "very confident"
- If I have no ideas, read papers
- If I have an idea, work on developing it. If I have a preliminary result, work on developing it. If I have a major result, conduct experiments etc...if I have a rejected paper, revise and resubmit. Prioritizing whichever option gets me closer to an accepted paper (because presumably the ideas get outdated quickly)
- Whenever I get the "ask my advisor for a break?" say yes. Whenever I get "I am tired" and no "ask my advisor", "Slack Off" for one month.
Fortunately I got no abusive advisor, rejected papers usually end up getting accepted later, no extreme life circumstances or cut funding. But my computer crashed way more often than I'd expect, especially since backups are so common nowadays.
Every time I tried the game (using OP's described steps) I "lost all hope and quit". I thought that was the joke / funny commentary: that all paths through the game involve you ending up losing. Didn't know there was a path to actually win the game until reading the HN comments. So I kept trying it over and over doing the same steps and finally won once.
I guess that's an even funnier commentary on how it's pretty much entirely luck based.
I followed this strategy + parallelized developing preliminary ideas and wrapped up in 3 years, 11 months with 100/100 Hope. If it only it was that easy! Haha
A bit disappointing it doesn't go into other details like being a women. As most PhD candidates are in their mid 20s and often by the end of the beginning of their academic careers they immediately have to decide to either have a family or pursue academia.
Didn't realise at the time but you have made me appreciate that that was one good thing about the British system - I was 24 when I submitted my PhD which is fairly typical so still time before such decisions (it was another 11 years before I discovered the challenges of combining a career with motherhood!)
Reducing a PhD program to 4 years can help but in many fields this is still a problem. For many fields and form of absence of leave can be the end of your academic career. If I recall correctly the average PhD graduate is still 26-27 years old. Which doesn't help much too much even though the average US grad is 31. For many field though this would help a lot. In tech and stem not so much. I remember some of the female faculty I knew telling me exactly how and why so many women end up filtered out. Simply because they wanted to have a child and by the time they came back their research was outdated and their works published by others. They themselves never having children. It's why many women often leave academia for industry jobs.
I personally believe how we conduct research and academia is outdated and does not allow for the proper inclusion of women. And does not allow men to be proper fathers. Sorry for the long talk.
Edit: Got the average age for PhDs in UK wrong it's mid 30s. Even if they started right at the age of 22 it's a wall they will face almost immediately.
In my opinion, a first step is to equalize maternity and paternity leave. It should be equally disrupting for men to have children as for women (from the perspective of an employer). I like the Swedish implementation of this model, where partners get 480 days of leave per child which they are free to divide among themselves, with a minimum of 90 days for either.
That's a ridiculous amount of leave. A man does not need much time outside abnormal circumstances for paternity leave. I would almost never work, as my wife and I have a baby every year or two.
> I was 24 when I submitted my PhD which is fairly typical
Good for you - that's very fast. According to [1] the median age for starting a PhD in the UK is 24 to 25 for full-time students. So you actually graduated around when the typical student starts.
I basically followed this approach but my paper kept getting rejected from the conference which really put a ceiling on my hope; ended up quitting the PhD after just under 5 years.
Second try the conference paper got accepted right away. Advisor even asked me if I needed a break after I'd had some success (never happened on the first run) and was getting tired. Wrote my thesis in 5.5 years.
There is also a hidden variable about being tired too, and if you don't slack off you waste months in forced situations with asking for breaks with the supervisor or burning out.
As a current 4th year graduate student, I opened the link and found the choice to accept or decline the admission offer, I don't know why I clicked decline without thinking.
"You decline the PhD offer and end up happy with an intellectually satisfying six-figure role in tech. You are surprised when you learn that your older colleague with a PhD earns just as much as you do."
Your prize is always wondering if you should have done it. I know people that say one of their biggest regrets was electing to pass on the PhD path. The grass, unfortunately, is always greener.
Also just pictures of them enjoying life in the city of their choice, the families they’ve started, the vacations they go on, the fun hobbies they have time for, etc.
I think the most realistic thing here is the luck element. You have people around you passing and making it look easy and saying to do exactly what they did and those people make it all out to be a skill game. But you follow their exact method and still fail. And keep failing. Making you think there's some secret sauce that they aren't telling you about. But in reality the difference was just luck. That in one game you can slack off half the time and graduate just fine and the other half of the time you can't even get a single paper submitted. The tyranny of the stochastic system is probably one of the most damning things in a PhD.
Reminds me of the poem The Road Not Taken by Robert Frost. Initially it seems like it's a poem about working hard and taking risks, but it's actually about old people lying to themselves, trying to forget that their success was actually just luck.
About half the professors I worked with were responsible adults, and half were narcissistic children who would do exactly what you described, "just do what I did", and when it doesn't work they quickly changed to personal attacks and insults.
And of course, the professors who had PhDs from MIT or Stanford just breezing through, getting approved for everything they applied to on the first round, even when their past deliverables and future proposals were garbage, and people who went to second-tier schools having to fight tooth and nail every incremental gain. Just a pile of crap. Couldn't stand it.
There's a saying I really like "the harder I work, the luckier I get." It being about how the time you invest makes you able to take advantage of more opportunities. BUT it also recognizes that the luck element exists. I think Veritasium also had a video along the luck+work lines. Basically if you just are unlucky you just have no opportunities and you'll fail no matter what work you put in. But if you don't put in work, you're also passing up possible lucky opportunities. Either way, it is a combination of a stochastic process plus skill (think about the design of any good {video,board} game. They require both skill and luck, just like life.
You definitely need both, and I think this is what people forget. Work is incredibly important, but you can do a lot of good and hard work and just be unlucky. That honestly is probably one of the more distinguishing differences between students/faculty at top institutions vs mid. Especially since success is a compounding event, thus an early success can catapult someone forward. We shouldn't diminish their hard work by saying it is all luck, but neither should they diminish others hard work and frustration as a lack of working hard enough when luck plays a significant role in the system. Neither is failure strictly due to luck. It is messy and we need to accept that this is the reality of the world, especially if we want to make the system more efficient and more "meritocratic" (quotes because previous comments and their relationship to Goodhart, the difficulties in evaluation and necessity to embrace noise).
Though your last point about the top tier breezing through, I can completely relate. I see a lot of low quality papers from those institutions get high marks and it is very surprising and definitely not consistent with a blind evaluation system... but I think most of us already know that.
I wanted to go all the way to a PhD. So did my classmates. We were going to change the whole world.
But after an internship at a FAANG during my 2nd year undergrad, the money was too good. Got some return offers and basically slacked off the rest of my undergrad, just waiting to graduate.
I was not born into wealth. I am a 1/2-generation immigrant. My parents struggled to keep me afloat during my undergrad years. Even my internship pay was more than my parents' income at the time. So really I had no choice but to sell out early.
Now 10 years after undergrad and a couple of FAANGs later, the baby crying in the other room at 3AM, parents retired and vacationing around, I think I made the only choice for me. But I cannot help wonder how life might have been different, and if I really did have a chance to change to world.
> But I cannot help wonder how life might have been different, and if I really did have a chance to change to world.
You made the right choice. Life as a PhD student is ultimately a life of poverty and uncertain future. You might get lucky and be able to explore a meaningful research topic, but more often than not you would end up in a miserable path with no future, and with the best option at securing your material needs to be in an ungrateful and very hard to reach academic role.
or after a few years of postdocs and job security that comes in 12-24 month bouts, you might have moved into industry anyway and just starting making 60% of what you're making now.
In the sim, at "Year 3 Month 9" I apparently "lost all hope and quitted your PhD".
In my real one (20+ years ago), I submitted my thesis after 3 years and 6 months, by which point I was no longer on speaking terms with my supervisor and was hanging on to my sanity by the skin of my teeth.
My viva went surprisingly well, after which I did the minor corrections that were requested, handed in a copy of my thesis, packed up my stuff and left that hateful group behind me.
This is great but it's missing one thing: having to apply for funding each year (time consuming!) with the statistical expectation of not receiving it. Then having to TA to help towards making-up the difference (it does not).
Then, spend egregious amounts of time each year filling out expense reports for conferences you attended. Also, take-up more part time work because it takes 4-6 months for the reports to get processed and you need to pay off your credit cards.
Profs apply for research grants that, depending on the grant terms, can be used to pay your stipend. There is no guarantee that your prof can secure that funding or afford to allocate it to support you. As a result, it behooves you to apply to funding agencies to get studentships that fund you.
Another note is that it is also a prestige thing. Getting grants as a graduate student makes you way more competitive when applying for PDF/PhD positions.
Many advisors are not sane. Many will definitely not tolerate multiple leaves of absences (i.e. vacations) due to stress. People lie and make up family emergencies to get the time off.
Yeah, that's one of the things I was looking for in this game. A friend of mine had an absolutely bonkers advisor who stopped answering my friend's emails. For a while they basically had to stalk their advisor, who would come in at erratic hours and quickly lock their office door, just ignoring any knocking. It was so wild to me, as my friend was just incredibly nice. My friend only graduated because other faculty sort of clubbed together as unofficial advisors.
I get that if you select only for smarts, you're going to get some odd ducks. But I've heard so many stories from PhD-seeking friends about the level of dysfunction that gets visited upon grad students.
A PhD is one of those rare periods of life where you are completely on your own, navigating unknown territories without anybody telling you what you should or should not do, where your professional success depends entirely on your own ideas and decisions. The reason to try a PhD is that you are truly free to test your limits. It can be liberating, but also daunting. And definitely humbling.
In some ways, it is not so different from being an entrepreneur, as in both cases you are forging your own path trying to do something new that a certain community likes.
I really love what you said, and this is why I did it too.
The journey is long and hard and there are a ton of bumps along the way to complain about. But the overall journey is worthwhile.
I think it is similar to marriage. If you meet someone who's been married for 50 years, and you ask them how it has been they will say it was wonderful and then immediately start telling you about all the tough times them and their partner went through. THey might tell you how hard it was when they both lost their jobs or when they almost broke up 10 years in, but they still love the other person and are happy to have had them.
To an outsider it feels like these aren't compelling reasons to get married, but the married person has other feelings that are hard to quantify like the joy of being next to their partner during the hard times, the ability to share in the joys of that new job, the ability to offload some of their stress, or even the joy of waking up next to them each morning. Those outweigh the shitty things, but the shitty things often get mentioned the most because they stand out.
I think the same thing is true for the PhD. It takes most people 3-7 years (averaging around 4.5) to get a PhD. This is a significant journey that will have ups and downs. You hear all the shitty things on here. But there are joys of learning something you truly love at a detail of focus that is not possible with any other degree. There is the joy of breaking new ground with research and the satisfaction of being the shoulders that future generations will stand on with their own research. The joy of having a paper published or the networking that you get to be a part of. The journey is worth it. It is unique for everyone and you are in control. Its a ~5 year journey that will inheritly have ups and downs. Do you need a PhD to succeed in life? Certainly not. But can it be one of the core pillars of your life if you choose to do it? 100% Yes.
Interesting that you point out the symmetry between pursuing education and entrepreneurship.
One of the tough things about the education route is that winning at entrepreneurship can result in huge tangible life changes, but it seems like the effects of winning at education is harder to visualize.
I actually really like the analogy. You are running a "business" of ideas. You are competing against a lot of other very smart people who are also trying to start their own ideas business and competing for a very limited pool of support (funding, postdocs, tenure-track jobs, etc.). The professors you are trying to impress in grad school are "investors" and having their imprimatur on your business will help in both advice and in obtaining more funding and convincing others that your business is worth supporting.
If you can run a successful ideas business for 10+ years in multiple locations and convince several gauntlets of committees to keep supporting you, then there's a great deal at the end for choosing this education route--your business gets a significant degree of permanent support and protection (tenure)! But to get to that point, you have to sell your ideas and develop a product that will get buy-in and support from others in your field.
There are no limits on how hard or how much you can work. There are also no guarantees that working hard will pay off either. There's a lot of luck and sometimes the market just isn't buying what you're selling at that time, even if your product is great.
Sometimes hotels and airlines mistake PhDs for medical doctors and give out upgrades... just keep your fingers crossed that there won't be an in-flight medical emergency.
Very much on point. Where else can you get payed for doing essentially whatever you like for a few years?
At least for me, that was actually worth the hardship. Although there was a lot of hardship. It was still an incredible, and ultimately empowering, experience.
As painful as it can be at times, it is a truly beautiful phase of life during which your main obligations are to become an expert in something that interests you and to make enough money to not starve and have a place to live. If you are single, coming directly from the "broke college student" lifestyle, and end up at a university with a good stipend, it won't even feel like you are "poor" and the money is mostly enough. But the life of a grad student in a large public university can come with much more financial instability and heavier teaching loads from day one, with less time for slacking off and letting ideas marinate. Less so if you are in a field/have an advisor with good/consistent funding. The devil is in the details.
Wouldn't change it for the world though, and anecdotally most people I know who ended up finishing the PhD feel the same way.
Main shortcoming of the (American) grad school experience imo is lack of preparation to join the corporate workforce (in my field, there are easily >10x the graduating PhDs each year than there are available university jobs). Academia has done a terrible job preparing grad students for the harsh reality of a non-academic career. Keeping this in mind throughout grad school will help a lot -- you can see the difference in non-academic career trajectory between people who had a backup plan and those who didn't.
I have a book upstairs I authored that I can go to and be reminded there was a moment my mind was like a samurai sword for one very specific problem. I solved it by holding a thought in my brain consistently for ~3 years straight, and trying everything known and new tricks to solve it. I can barely read my thesis anymore, let alone understand it, the quality of what I did feels almost super human compared to what I've been asked of by the world outside academia. A lot of people who never spent any time post undergrad think its all nonsense, mostly because they meet slacker types. But if you really challenge yourself you will produce something singular and at the best of your ability. It's extremely rare you get that opportunity and support in time to do that anywhere else. Unless your PhD translates to commercial application directly! Perhaps artists with healthy commissions get to feel it. Startup life is similar I guess, but the pressure of commercial success is a very different driving force vs intellectual curiosity and understanding something new in the world. Post PhD I know that if I felt like it I can operate at an incredibly high level intellectually, that I choose not to post PhD is also the other confidence PhD gives you. Most people I know are pretty down to earth post PhD and leaving academia, its ultimately a humbling experience especially if you had fun with mental health during getting it done. You know you can do something, but you also know at what cost to yourself and people around you.
I wanted to go into academia to do research and teach, so I went for a Ph.D. and got it in 4 years in computer engineering without much burnout or issue. I was always cheerful and enjoyed my journey. I did have a great advisor and while I was at a top-100 university, it was outside the USA and maybe that makes a difference.
You should really only go into a Ph.D. because you really want to, which sounds tautological but basically you need to want to go into academia or get the kind of industry R&D job that requires one (several of my graduating colleagues). If you're on the fence about doing Ph.D. - don't. There's a very real opportunity cost.
1. If you manage to get through it, you will be a world expert in a niche that can be valuable. $$$$$$$$
2. You will develop the invaluable skill of not giving up even when all the odds are against you
3. You will be able to swim by yourself, parsing enormous amount of literature, identifying what is useful and useless and solve problems that no one else before you has solved.
4. Access to academic positions that offer stability
5. Access to academic network that provide infinite talent
> If you manage to get through it, you will be a world expert in a niche that can be valuable. $$$$$$$$
This depends highly upon your field, the current needs of industry, and your own work ethic. For example, if you want to write or architect software for a living, a PhD in computer science really doesn't get you much. Neither is it a good idea to go for a PhD just because you can't think of anything better to do to further your career. But if your goal is to make new discoveries in a field you are passionate about, then that would be a different story.
Also I have met a lot of PhDs who are absolutely not experts on anything at all, except for knowing how to thrive in the socio-political academic system by being "book smart," and writing bullshitty articles/papers.
> You will develop the invaluable skill of not giving up even when all the odds are against you
Are you saying people don't wash out of PhD programs all the time? Even if this was somehow true, you don't need to throw money at a PhD program to learn this!
doing a PhD for the earning potential is hilarious. you'd be better off getting a normal job, living frugally, and pumping as much into savings for the same amount of time
the long tail of profit in a startup is wildly higher than a PhD. To be clear, I say this as one who's gone through a math PhD; none of my fellow graduates make significantly more than they would've made bypassing the PhD for industry, especially when you consider the opportunity costs. Academia is very much for people who either prefer ideas or prestige to money.
Well I am bit biased because 2/14 of my PhD class, 10 years after defending, they are >50M worth, by leveraging their expertise.
I can accept the argument that a unicorn startup might have higher tail monetary benefit compared to a PhD. But a startup job will not open as many research job opportunities as a PhD. These are typically the highest paid individual contributor jobs in companies.
Of course if managerial track is your thing, you should probably not waste your time doing a PhD.
Me? I just realized I'm not motivated to get up to work in industry. I just can't get up to chase and achieve goals that serve the needs of shareholders or any other stakeholders. In academia, I probably still won't care about the stakeholders, but I'll at least get to explore stuff that interest me. Well, that's the hope anyway! Haha!
Reminds me of how many entrepreneurs don't become entrepreneurs to become rich. They do it to become free from having bosses. Except for me, I'm not sure I'd be able to make it as an entrepreneur if I only chase what interests me instead of what a market wants. If I chase what the market wants instead of what interests me, my motivation drops. Been there, tried that. So... here I am. Even though it's painful right now.
Savor it while you can. As a former academic, for me the lack of intrinsic motivation to "create value for shareholders" is the hardest part of working in industry.
If you have a cool idea which is novel in your field, a PhD might allow you to work on it without selling out to VCs. There are still people to convince, but the time horizon for results is longer than with an average seed funding.
A PhD is one of the hardest, yet most rewarding time of my life. Its perhaps the only period where I have the opportunity to do nothing else, but "think"; where I can spend many months just reading papers, learning and attacking what seems like one little problem. It is very hard work, no doubt. Going back in time, I would still do it again. And in fact, I have seriously considered doing another PhD in an entirely different field.
But still I generally do not recommend people do it. You have to be in it, because you are very interested in the field. You have to feel rewarded by learning, and by solving problems. And also there is a lot a lot of luck involved: advisor, topic, ideas etc.
Because tenured faculty members at research universities often have lovely careers. The road there is long and challenging, but the result can be exceedingly rewarding.
Ah yes, the coup de grâce. Or you do find employment and then find that your major result paper is being challenged and have to submit a retraction. The fun is endless.
Hi everyone, I wrote this game 5 years ago when I was going to graduate from my PhD program. I did not expect to suddenly become popular in the middle of this week. Hope you enjoyed it (and thank you for stress testing my personal website)!
I wrote it to look back my PhD experience in a humorous way. However, each person may have a different experience and the game cannot simply capture all the scenarios. The road toward the PhD degree is full of challenges, and can be very stressful. I feel sometimes you also need a bit of luck like the randomness in the game. Thank you all for playing the game! Congratulations to those who already got their PhD, and best of luck for those who are still pursuing it!
You can find the source code of the game here: https://github.com/morriswmz/phd-game. I haven't touched it for years and probably already forgot how to build it. From my memory all events/items/status are customizable through YAML files so you can easily mod it if you want to.
I completed the game the same way I completed real life. I left early with a MS instead of a PhD.
Based on my experience, there needs to be a chance that your advisor is a narcissistic child who pushes you repeatedly to spend your entire PhD either fixing the mistakes in their own PhD thesis (without changing anything they did) or doing unpaid unpublishable production work for their half-assed startup. And hobbles your attempts to establish connections outside of their control. And also does a lot of things that could be termed "fraud" and "embezzlement" if the university cared to investigate when you and others before and after you complained about it. And probably some more mess involving petty politics with post-docs and competing professors.
I loved grad classes and research, but I hated academia.
> I loved grad classes and research but I hated Academia
Truer words have never been spoken.
I went back to get a PhD after a solid career where I was in a prominent leadership position at a respectable tech company (in my mid-thirties). I was bored, not motivated with work anymore, and wanted to do something that really pushed me and motivated me in ways that I hadn't felt in years. I also wanted to truly learn some advanced concepts through Grad classes.
I really loved the grad classes (although they were much much much easier than I expected). That is why I moved into research, to really stimulate myself and do something interesting to me in my specific area of expertise. I really enjoyed doing the research too. I was personally motivated and curious on the topics I was researching. It gave me a lot of new-found motivation in life and I really flourished.
But academia: the drama and games you need to engage in to do such simple (arguably trivial or non-important) tasks is ridiculous. I succeeded in my business career because it was results driven. If you produce results, people don't care how you got there exactly. But in academia I felt like it was a board game of "chutes and ladders", mixed with Risk and Monopoly where you had to own parts of the board that other people deem important, you hit chutes that set you back for no apparent reason, you were constantly collecting personal referrals and clout from other professors so you could get their blessing or IOUs. There's a lot of favors and ceremony around trivial tasks and the actual produced value often gets overlooked or forgotten about because you didn't march to the same drum as someone else.
>Professors demand you do exactly what they want for your thesis.
Also, what qualifying exam? It seems like as long as I was worker for my professors, they couldn't give a crap. (Although I was quite credentialed, so maybe they didn't care)
If I do get a PhD, it will be on a topic I want. So far, I have done that better independently and have gotten a bunch of press on the topic without needing academia.
That's what I did (~17 years ago). I was registered as MPhil then transferred to PhD after submitting a mini-thesis after about 2 years. In the end the mini-thesis actually contained all the most significant results that formed the PhD thesis and the latter just explored some applications.
Holy cow, I just played the rules I used when I did my PhD (1/4 time slacking off, 1/3 on developing major ideas and collecting results to support it and resubmitting the rejected papers) and graduated in 7 years. Exactly like real life.
A very important part of the work of the advisor is to pick a subject that is not been researched by other group, so you can work on it without the fear of been sniped. It not foolproof, but if three or four ideas get sniped, it's probably better to kindly consider an advisor change.
Some time ago I watched this movie: https://www.imdb.com/title/tt0416675/ (Dark matter). I don't know how accurately captures the essence of getting a PhD, maybe someone who went through it can expand on that, but I've always wondered if it's actually how is depicted in the film.
This film is a fictionalized depiction of the real-life 1991 University of Iowa shooting. A PhD student murdered his advisors, VP of Academic Affairs, and a fellow student for being passed over for a prestigious prize. There were other geopolitical influences on this event that I'd say make it unique.
This is great! The ending phase really gives you the same feeling of “screw everything else, I need to finish this paper” rushing to get the final stuff out.
By that time I had already grinded so long and lost so much hope that I HAD to slack off but couldn’t because every time I tried, my advisor caught me and reminded me of my progress. Repeat until I lost all hope!
This is not exactly how it works in STEM, at least not around me. Ideas tend to come from working on real-world projects, which then shows the lack of understanding and need for research. The project forks to do the research and merge back to implement the findings. Thereafter, someone on the team will put it into a cohesive academic format, and use it for a PhD. Of course there is reading papers and such, but it is not the source of the idea.
edit: I am also curious, how many really stop research because a similar or tangential topic was explored? "There can be only one"?!
I'd say this is where more engineering approachable ideas come from or ideas that might be considered translational (or near translational). If you work near the bridge of theory and application, this is probably more the case. A lot of funding agencies are pressuring even theoretical or basic research to look at translational application anymore though (capitalism is all about immediate ROI) so I'd say this is increasingly shifting towards many research domains but in the past, there were a lot of pure theoretical areas you could work on where there are plenty of unexplored ideas you could build out and get paid to do the work.
Application is certainly a great driver though because you have a demand signal to look at vs throwing darts at the board in work that may never manifest to anything solid.
> This is not exactly how it works in STEM, at least not around me
You might want to take a different approach to reading papers then. No paper ever concludes by saying "yeah our method is perfect and no further work is needed" [1]. Instead, every solution has its quirks and questions which need to be explored further. Maybe their method has limitations which make it unusable for your applications, maybe they make somewhat faulty assumptions that don't always hold, maybe they wrongly ignore some technique. Seeing how other people approach a problem can often give you inspiration for how to take it another way.
The proportion of slackings off for which you are caught by your advisor is unrealistically high, but exactly as high as it feels. I definitely got my fair share of those emails...
This sounds less stressful than an average half a decade working at my current position. It is actually motivating. Whether or not that was the desired outcome, I don't know. At least I get to travel to half decent academic conferences and not large vendor marketing conferences.
I'm interested in how specific this PhD experience is to the US, certain subjects or recent times. My own experience doing a maths PhD in the UK in the mid-2000s was not like this at all (but had a different set of challenges for sure).
I'm a chilean maths grad student and save for the qualifying exam, it's quite accurate. So much so that I think I made a mistake clicking on this because as it progressed I started feeling dizzy. Other commenters here also have their relatable experiences, which doesn't make me feel so bad.
I'm about to wrap up my PhD in a few months here in the US, I find that while it's kind of close, it's a bit on the cynical side, as is most of the HN discussion about PhDs.
Yes, my advisor emphasizes papers a lot, but there aren't any requirements for number of papers for graduation. While there are extremely busy periods of forgoing sleep to work (eg right before a major deadline), my advisor also constantly reminds us to take breaks and enjoy life. There was also the anxiety about graduating on time, but that too was sorted out by just having a meeting with my advisor and understanding how things work.
On the other hand, the situation with the qualifying exam was the opposite, I had to constantly remind my advisor that I needed to get that done. It involved a 50 page report on the current status of my research and a thesis defense style presentation to my committee, so that was a bit of a challenge to make time for between normal research. Passing it didn't feel like much of a challenge, just meeting the 50 page requirement did. I had enough data, but it was still a lot of writing.
For some reason I found the font really hard to read. My brain has the impression that the text is vertically compressed, squished even. Just that no amount of resizing the window changed the strange effect. Is that only me?
It's been mostly like this for a long time, but it is slowly changing. Open data repositories and scientific software libraries/products are beginning to count more and more (at least many of us are pushing for this). It also depends on the target career past graduation. Papers matter a lot for tenure-track positions, and much less for science support (scientific software developers, data engineers, lab managers etc.) in academia, or most jobs in the industry.
The 3 paper requirement in the game is also not a formal requirement in most universities--it's more of an implied requirement by individual PhD advisors. FWIW, my first lead-author paper I published a year past my PhD. During my PhD, I produced two relatively large scientific software applications (one open and one closed source) and a few open datasets. I'm now 8 years past my PhD and relatively successful in my field, 90th or so percentile based on common metrics--papers, citations, and funds raised.
Bottom line, papers are important but not the only thing that counts. Outside of tenure-track careers where they are crucial, it's possible to establish yourself as a scientist and be respected by your peers by publishing software and data.
In what fields is 3 papers expected? In my field, Psychology, 3 first-author papers sounds like a reasonable lower bound, but that seems like it would be a lot to expect out of Biologists or hard scientists.
Current 4th year in Biology. Generally, 1 paper is expected, but it is not strictly necessary to graduate. Highly doubt that the PI will let you go without finishing your project though.
This is reasonably accurate as far as the average PhD experience goes. I do always encourage my PhD students to take some time off during holidays and after major deadlines, rather than berate them when "slacking off" (unless that's all they do).
Stuff missing: holidays and deciding whether to travel home or study / read papers (I missed holidays myself during my PhD), feeling envious of peers from pre-PhD living great lives, having kids during one's PhD (that would be hard mode), drama in authorship of collaborative papers, etc.
The last year anxiety is accurate for most. It is also missing the job search in the final years. For many disciplines, 3 strong papers is the minimum for graduating, but if one really wants to get a faculty position or even a job as a research scientist at more prestigious institutes, probably 6 papers is better.
This, and subsequent comments, are all experiences I’ve seen happen to my partner and three very close friends. I decided to pivot academic path ways and pursue a masters, so they all wound up ahead of me by a year. Watching their experiences, I decided I’d rather pursue financial security and independence before pursuing a PhD. I think I’ve made the right call. It may be harder to get into a programme this way, I’m not sure, but I fundamentally do not want the worst case scenarios of a PhD combined with needing it as a next step in my career or a source of income.
This is just brilliant. Brings back memories, some fond others less so. Only addition I'd suggest is a subplot involving teaching/TAing duties and/or money problems.
Good to be occasionally reminded that slacking off is a legitimately important part of the scientific process. Wish this view was more popular in the industry.
I took qualifying exam on the last semester after I finished the thesis. They [university officials] thought in their system I have left the program. I had only 4 weeks to study for the exam because my advisor gave me a ultimatum after he thought I took the exam already. I was working full-time at this time and couldn't take 4 weeks off. After so much praying, I got the highest score, and I ended up becoming a Christian because of all the praying. It worked out at the end.
I find one month per turn quite coarse: much more fine-grained misery could be added with variable-length activities, waiting anxiously for something, real life commitments, or randomly wasting time.
For example, 2d4 days to read some papers, 1d6+1 consecutive days to think about a new idea, a 50% chance per day of being busy teaching, resource contention with colleagues running their simulations, etc.
You could adapt the same game logic to a lot of things in life: Job Search, Career Success, Startup Founder, Stock Investor. In most life situations, it is possible--even likely--to "make no mistakes and still lose."
I was able to easily graduate in 5 years, only one false start because the simulation seriously overvalues preparing for the qualifying exam. Also, it doesn't consider that you usually get two attempts at such an exam, not just one.
one issue is overemphasis on qualifying exam. Most advisors, at least for experimental disciplines, value publishing papers much higher than jumping through these academic hoops, and make sure that either qualifying exams are easy to pass or can be retaken.
I'm doing it right now and I kind of envy my colleagues that are doing normal work. There are times when I enjoy the ability to focus on things that really interest me, but the paper writing and publishing processes really suck. Also, the random stuff from the university that I have to jump over sucks fun out of the process, for no gain to anyone.
lol at the downvotes, you know it's true. Most of the made up papers in the "Sokal squared" affair that made publication are considered PhD level within those fields and they're literal nonsense https://en.wikipedia.org/wiki/Grievance_studies_affair
lol I wish it was this easy. I got through the simulator in 6yrs 11mos on the second try. At no point was hope above 40%, except once early on (ended at 33%).
The funny thing is that I had 1 conf paper, 1 major result, and 1 figure left over. That's a good year extra, so I assume a perfect game would be to get the 3x papers and GTFO (which is the second best outcome, after not enrolling). There were a couple folks I knew that made it out in 5 years, but more that took 7+. Our lab was notorious for taking over 10, which I skirted by.
Like others said, this was lacking outside events (social/political junk). Hopefully version 2 will take into account: at least 1 family death and 1 additional tragedy, at least two months lost to helping or waiting for help from another grad student or post doc (they did have the lab equipment breaking, which was good to see, but missed the lobbying for every little purchase), at least one scope change, a half dozen favors to gain some political cache, a few experiments and/or rewrites to satisfy faculty members that just read about a technical issue they should have known, but didn't so they're highly sensitive to it, at least 6 months of arranging the data/results in a way that faculty can understand, 3 months of arguing that the lab standard procedure for some basic component is a decade out of date, a few months worth of preparing premature data for unnecessary meetings, one (and it better be just one) instance of an offer to help getting waaaay out of control, the hope boost after your first big conference and subsequent conference hope drops, the drops with each thesis defense from folks a year younger, etc. There's more, but that's off the top of my head. Oh, and that slight boost in hope when you hear someone else has a worse problem than your current one. That's a fun one.
Tip for those interviewing - ignore all the year 1-3 folks. 1 and 2 are basically undergrads plus some extra classes. 3 probably hasn't hit the first pile of bullshit yet. Find a year 5 or 6 in your field and talk to them alone. There's a reason they generally don't have senior grad students at recruiting events, and it isn't because they're too busy. Talk to them long enough to get to their exhausted attempts to rationalize some aspect of the experience. If their demeanor doesn't change, you might be safe. If they start hemming and hawing, that's a problem. They haven't even gotten to a specific, non-personal problem and they're having trouble keeping up the facade. The layers are: 1) Hey, social event, I get to take my mind off lab problems. 2) Getting a little boost by talking to someone still excited. 3) The quiet whisper, "Let me give you some advice." 4) The realization that there's nothing but lab to talk about. That's the threshold. 5) The rationalization alpha - The view from 30,000 feet isn't terrible. 6) The rationalization beta - The rundown of broad problems they're having. This is the point where they will probably, as if by magic, remember that thing they were going to do needs to be done now. (I've got some analysis running I need to check, I need to feed some lab animals, I promised my parents I would call, I told a lab mate I'd help them with this thing and will be up all night, etc.) 7) The rationalization gamma - Specific cases of major problems they're seen other have. 8) The rationalization delta - Specific problems they're having.
Some highlights:
> INBOX: Based on the reviewers' comments, we regret to inform you that your manuscript has been REJECTED for publication. One of the reviewers pointed out that there is no comparison with a state-of-art method.
> You came up with a bunch of ideas. However, upon further searching, you found that they have already been done before.
> You found the missing piece during a shower. You develop one of your preliminary results into a major result.
> You found one of your ideas appears in a recently published paper. You can no longer work on it.
> Three years passed. You have witnessed many graduations. You began to worry about whether your can graduate on time.
> The simulation took a much longer time than you expected. The results are not available yet.
What was missing:
1.) Growing feeling of getting too old
2.) Growing family obligations (marriage, kids, trying to write a thesis at 3am with a crying baby next room)
3.) Questions asked by friends and relatives regarding progress
4.) Teaching obligations