PhD Simulator
research.wmz.ninja
research.wmz.ninja
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
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!
Also, random catalysmic events, like in year 4 your advisor accepts a job at a different university in another state.
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.
nearly half of my year didn't get this and had to master out when we got to quals.
Or failed quals?
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.
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.
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.
If they do not make the grading lenient - it’s for a reason.
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"
Then again, knowing that that @£&$€¥ would drop you might make it a good plan.
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.
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.
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.
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?
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.
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.
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!
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!
PhD is granted for novelty, not practicality.
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.
Computer science is applied math.
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.
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.
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.
any advice for people aiming for teaching instead of all the publishing stuff?
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).
Not completely true. UC Berkeley at least has tenure-track lecturers, now apparently mostly referred to as "Teaching Professors" (https://apo.berkeley.edu/sites/default/files/teaching_profes...)
A random (old) job post for this: https://gsso.ce.gatech.edu/2022/01/12/tenure-track-teaching-...
> 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).
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.
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.
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.
Oh ... I felt that one :-/
Then give you the option a year later to congratulate him on the startup’s multi-billion exit.
In the game it pretty much continously went up.
n) Your old college friends have secured their material needs while you barely make rent.
n) a PhD student that joined the program after you just surpassed your number of publications.
n) your thesis supervisor just bumped you off primary author to contributor in your own paper.
I mean, woah. Even that's a little too far for phd-land
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."
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.
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've seen people attempt suicide and had to drop out of their programs.
Doctoral programs are a vicious and cruel system to exploit high-achieving young adults.
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.
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.
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.
I guess that's an even funnier commentary on how it's pretty much entirely luck based.
I wonder if there are other issues you can get e.g. if you slack off too much but your hope is still low, it just stops working.
I thought that was a trap, and I was surprised my initial strategy of "say no but then slack off" didn't work
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.
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.
[1] https://www.hepi.ac.uk/wp-content/uploads/2020/06/PhD-Life_T...
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.
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.
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.
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.
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.
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.
Yes, definitely, but maybe(?) in a different research group.
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.
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.
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.
Highly dependent on the advisor.
Thanks for the flashbacks. At least we didn't have any qualifying exams.
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
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!
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.
This one reads like a bitter joke :/ not sure where you live for this to sound true to you! But the rest are good takes.
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.
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.
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 get to put PhD after my name, but what else?
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.
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.
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.
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.
Depends on whether you won federal grants though, although most of those end up thrown at PHD students from Ivys and Stanford (sadly?).
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.
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.
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.
Cheers!
I was surprised that writing the thesis was an immediate success. I've seen many PhD students struggle at this point, taking > 12mo to submit.
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.
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.
I completed my PhD in 4 years and 11 months, which feels quite reasonable. My "hope" never dropped below 45, and by the end, hope was 76.
If anything, this simulation just made me think getting a PhD would be a fun opportunity to do a lot of study, and didn't put me off at all.
EDIT: Why downvote? haha I'm just sharing my experience.
Which is a bummer. I was hoping I could just chill.
Most PhDs aren't so lucky, regrettably.
I finally beat it in 6 years, 2 months, with 71 hope, 3 conference papers, 3 papers, an idea, some cloud storage, and some late year anxiety lol.
>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.
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"?!
that said, the game is fun! Thank you.
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.
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.
# idea -> prelim -> major -> 2 figures -> submitted paper
interesting to see the hypothesis about reading more papers being borne out:
# increase the success rate as the player reads more papers probability: 0.60 + player.readPapers / 100 - itemCount('idea') / 20
Also interesting to see that passing the qualification exam provides the largest player.hope boost (+10)
Was fun to see the TooManyIdeas random event - now to actually get it to trigger.
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.
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.
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.
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.
Feeling personally attacked.
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.
that explains low hp stats
Not sure I want that much stress in my life anymore!
This is a trap!
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(less like Jones in the Fast Lane)
Maybe an endless generation of MUD + LLM are actually the future of gaming
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.