Do not pay for a Ph.D. Especially do not pay for a Ph.D or MA in the humanities. Any program that's worthwhile and wants you will provide full tuition and assistantship. Not offering you a full ride plus stipend, just means the program doesn't really want you but is happy to take your money if they can get away with it.
Professional programs with a clear non-academic career path, e.g. law and medicine, are a different story.
I have completed a PhD in theoretical physics (general relativity) several years ago. I don't know if you call it successful, since I am not working in academia (and there are no industry jobs in theoretical general relativity, save for a couple of people at NASA).
First, phdcomics is basically a documentary, if you take an average PhD student.
Second, unless you are very good and very lucky, at some point you will burn out and think of quitting daily or even hourly, the same way clinically depressed people think of suicide. There is an even chance that it will get better at some point later.
On the bright side, the feeling of discovery when you figure out something no one has before, rare though it is, is something else. And having it published and recognized as such is nice, too.
As for advice, one which is a bit late for you: pick an advisor who has a proven track record of seeing her grad students through and into a postdoc position, and the other is probably still relevant: on the bad days, just keep grinding and don't despair. Oh, and one universal advice: network.
First, phdcomics is basically a documentary, if you take an average PhD student.
I find it hit or miss sometimes. Lots of it is very much true but I have a much better relationship with my adviser, for example. This is coming from pure mathematics.
Second, unless you are very good and very lucky, at some point you will burn out and think of quitting daily or even hourly, the same way clinically depressed people think of suicide. There is an even chance that it will get better at some point later.
This is true; the only effective strategy I have for avoiding this is remembering how universal it is.
at some point you will burn out and think of quitting daily or even hourly, the same way clinically depressed people think of suicide.
Any specific advice on dealing with these situations or preventing them arising?
Do not apply to safety schools if you want an academic career.
Within any given field there are only about 5-50 top programs in the United States, and if you aren't sure where those are for your field, your undergraduate faculty can tell you. These are the only programs you should apply to. There is a huge oversupply of Ph.Ds in almost every field, and consequently it's a buyers market. Colleges hire fulltime faculty almost exclusively from a small percentage of the Ph.D programs. If you can't get into one of those top programs, it's better to reconsider your career choices now before you've invested several years of your life, than five years down the road when you have a degree that actually decreases your attractiveness to employers.
If you go to one of those top programs you have a much better chance of landing a tenure-track academic job at the other end. If you matriculate from a second rank program, you might be able to land a job at a third-rank or worse institution, if you're lucky. If you go to a third rank institution for your Ph.D, get ready to adjunct at a community college.
You may well have gone to a better high school than grammar school. You almost certainly went to a better college than high school. The move from college to graduate school is your last chance to move up the ladder of academic rankings. Doing well as an undergraduate at a lower-tier institution can still get you into a top program like MIT or the University of Chicago. But doing well as a newly minted PhD at a lower-tier institution will not even allow you to be considered for a faculty position at a top institution.
At my university, we have several professors who went here for their graduate studies. Maybe this circumstance is an exception.
It's sort of an exception that proves the existence of the rule. It is indeed common for second rank school A to hire PhD's from school A. My undergraduate institution (which I'd place in the second rank) did this too. However what doesn't happen with nearly as high a probability is for second rank school A to hire PhDs from second rank school B. They'll hire from Harvard or MIT instead.
Another confounder to watch out for is faculty age. Universities do change over time. When I was in graduate school, there were a number of tenured faculty in the department who would not have been considered as potential hires at that time, but who had been hired 20+ years earlier when there was not such a glut of PhDs, not quite so much emphasis on prestige, and when the university itself was not quite as prestigious as it had become.
Most of those folks have retired by now, though, and most departments I look at are even heavier with PhDs from the Harvard/Stanford/MIT/Chicago/etc. than they used to be.
Try out a industry job one summer to see if you'd like it or not. (Do this early on in grad school: it's usually easier then, and you won't have to worry about summer funding!) This gives you the context you need to decide whether to stay in academia or leave it, instead of going round wondering how green the grass really would be for you on the other side.
Background: did a PhD in math, did a 3-year postdoc, then decided to join a startup instead of take a tenure-track job or another postdoc (and yes, I had opportunities for the latter options). Relevant: I only noticed I had a career crisis while a postdoc, and fortunately was able to work at a startup for the summer between years 2 and 3 (math postdocs are academic-year-only jobs) to help me make this decision. But in retrospect, I should have tried out something non-academic many years ago.
How did you go about getting an industry job? I am in a similar position (well, mid-PhD) and have felt increasingly interested in leaving academia, but I'm not really sure how to taskify doing so. I can see where I might apply for jobs but it's not clear to me how to look for summer jobs, specifically. Should I just go on job websites and search for "summer," or some similar tactic?
Personal connections are the easiest way, whether it's a startup or a bigger company. Anyone who personally knows you as a smart and reasonably sane person can pass along your application on the inside track, even if they know nothing of your domain-specific expertise.
Other than that, I don't know; personal connections were enough for my job-seeking process.
This is what I see as one of the major weaknesses of doing a PhD in math, I don't find myself able to network with many people in industry. I do know some people from undergrad though so maybe I will look into that.
Like I said, they don't need to know your domain expertise to know you're capable and sane. My personal connections were people I'd met through Less Wrong meetups, board game nights, and swing dancing in the Bay Area.
My university has an active online jobs board, and I've seen a lot of positions posted as summer internships for graduate students. If yours has similar career resources, you could try that, or try talking to the career office personally about it.
My university has a similar thing, but I see very few positions posted as internships for graduate students. Partly this is because the online jobs board is really poorly designed.
I've been "planning" to talk to the career center about this sort of thing for a while. It would be nice to have some kind of external impetus for this...
Start planning your career early. Find out what it takes to succeed, whether you have it, and how/whether you can get it. Work with your advisor, other professors, career placement. Join orgs and make contacts. In tech work, programming and data manipulation skills are extremely valuable.
Your classes are largely irrelevant to your future. Your research, skills, and contacts are what counts.
Here's a piece of advice I am confident of: some graduate programs focus on getting everyone through to a terminal degree and don't admit anyone who they don't think is capable. They tend to admit a small number of students relative to faculty size. Some programs admit too many people and plan on washing out 50-90% of students on the qualifying exams or by other means. It is usually easy to figure out which is which simply by asking existing grad students about this.
Do not apply to any program that has a high washout rate. While some attrition is to be expected as students decide the career they thought they wanted is not for them, any program that gets less than 50% of its attendees through to a terminal degree should be avoided. Any program that washes out students on qualifying exams or by other means should be avoided. Some qualifying exams are legitimately difficult, but that should be compensated for by unlimited retakes.
Morale is your hit points in grad school. Morale management is very important, many dropouts are due to morale issues, not actual lack of ability.
In the early stages, be prepared to triage what you thought was going to be your thesis analysis. Sometimes the experimental resolution is just not good enough; don't spend six months trying one "maybe this will work" after another. Six weeks, ok; not months. Write it up as "we couldn't do this" and then find a different topic.
Only do a PhD if
If all these are true, go for it! You can live the student life and have fun becoming the best in the world in something.
Background: I did a PhD in Harvard and am now working in something else. All four conditions are true for me. As far as I can, I would have done no worse or better in this career if I had gone straight into it from my BA.
All of these are true for me (or could be true if I applied to grad school again, and this time accepted offers like ones I rejected this time), but I am not going to get a PhD, because an MS in my field (computer engineering) is sufficient to get the high paying jobs I want, so I can start making lots of money for effective altruism sooner.
Your experience isn't just true "for me", it's true statistically. A Master's degree in most STEM fields (IIRC) is an investment, and a better investment than you can find in the market if you're smart enough. A doctorate in most (all?) fields is partly a consumable - it leads to higher expected starting salaries, and even higher salaries than one would have had by spending those PhD years accumulating job experience, but not enough higher to make up for the lost income during those years.
Of course, a PhD is valuable in more ways than just income, and I don't regret mine despite some delays which make the above economics worse. But everyone should know what they're getting into.
Sure, the PhD is on the whole an income-reducer, whether because of the opportunity cost for those years, or because of the reduced income afterwards.
It's only worthwhile if you enjoy it enough that the reduced income doesn't bother you.
You see that you won't get stuck: that you'll finish relatively fast.
Do you know of a way for estimating this? Every research problem (and the entire PhD itself) might look much easier before you start working on it (you don't have an outside view perspective before starting).
Nothing is guaranteed, but a good adviser and good personal focus should allow you to finish it off.
might look much easier before you start working on it
Again, no guaranteed answers, but if a given problem is too big, you can redefine your thesis to a narrower part of the problem.
You have other career options available.
What do you do if you want to do a PhD, satisfy all the other criteria, and DON'T have other career options available?
I can't imagine that doing a PhD is worse than sitting on your ass unemployed, but if you have ideas about this I'd be interested to hear.
OK, assuming that those criteria are satisfied, then you can start the PhD and drop out with an MA -- which is paid for, unlike most MA's.
Where I got my PhD, you could drop out after one year, simply having completed the courses of that year, and you'd get the MA.
If you're in a top program in physics or similar hard sciences, you can use this approach as a stepping stone to finance jobs.
Where I got my PhD, you could drop out after one year, simply having completed the courses of that year, and you'd get the MA.
This is true for my program too, although one year wasn't enough time for me to figure out other things I wanted to do.
you can use this approach as a stepping stone to finance jobs.
I hear this regularly, but I still don't understand how it works. Does this come from networking that happens at top schools, or are there finance companies actively recruiting PhDs? What qualifies as a "top program"? A department well respected in the field or a university famous for other reasons? Is a famous adviser at a poorly-known school better or worse than the reverse?
I am not familiar with the details myself, but I understand that the top schools would include MIT, Harvard, and maybe 4 or 5 more. Physics is apparently the top program for this, though math and others might qualify.
Also, I read that the demand for physicists etc. has gone down, now that Wall Street has realized what math is actually needed to be a quant. The math is pretty simple, and can be learned specifically for the purpose rather than in a PhD program.
Once you've passed the qualifying exams, the next big blocker for most people is the thesis. Don't let ABD be a terminal degree.
Outside the experimental sciences, budget one year for the initial draft of a thesis, no more. This includes all research. If your thesis topic is too big to research and write in a year, cut it down until you can get it done in a year. The goal of the thesis is to tick the checkbox on the list of PhD requirements, not to produce a world changing work of scholarship. You can always keep working on the subject after your PhD and publish a book for that.
Akrasia, procrastination, and writer's block are big problems for some students at this stage who've never had to be this self-directed before. There are plenty of posts here that address those issues. If this is happening to you, read those posts.
I recommend writing from the outside in. That is, start writing a very rough outline almost immediately. Fill it in and flesh it out every day. Write something, and if you aren't sure whether the something is true, write it anyway and put in a TODO comment to find out. Mix your research and writing. That is, do not plan on 6 or 12 or 18 months of research to be followed by actually writing. As you research, your thesis should be filling in and getting more complete day by day. When you're finished researching, you're finished writing.
If you discover that one chapter of your thesis is growing out of bounds, consider whether you can cut everything else and make that one chapter the entire thesis. E.g. if you discover that your thesis on the development of Ottoman Empire bureaucracy from 1718-1914 is bogging down in the Napoleonic era, maybe the thesis should instead be the bureaucracy of the Ottoman Empire in the Napeolonic Era. Or maybe it should be the development of the Ottoman Empire bureaucracy from 1718-1799. Either way, cut your topic down to size at every opportunity.
I have less experience with theses in experimental sciences; but my impression is that in experimental science, the real thesis is a pure-reviewed paper significant enough to be published in one of the major journals of the field. This paper is then expanded with a bunch of supporting details (tables of experimental data, computer code, etc.) that couldn't fit in the journal article. Once the research is done and the paper accepted for publication, producing the dissertation itself should be relatively easy. I don't know how long it should take to do the research. However, I do recommend aiming for the most obvious approach with the least risk of failure. E.g. rather than trying to develop a new experimental technique for measuring lipid profiles that may or may not work, prefer a thesis topic that involves using well-established techniques to measure the lipid profiles of some undersampled population. For instance, repeat an experiment that's already been done, so you know in advance how long it will take and how much it will cost, but this time do it on women instead of men, or senior citizens instead of college students.
The unifying theme here is that you need to limit your investment in the thesis and avoid procrastination. Find the shortest path to completion. Do not make the mistake of trying to fit a topic worthy of an entire career into one dissertation. Plan for a year from topic approval to completion. If that's unreasonable, find a smaller topic until it is reasonable. If your thesis takes longer than planned, that's OK provided you're making regular progress and the end is in sight. An extra year won't kill you; but if the end is more than a year in the future, something has gone wrong. Back up, reevaluate, and cut your topic down until you feel that you are likely to finish within a year.
Apply for fellowships. NSF, NDSEG, and Hertz are all open to anyone in the sciences, and there are some other fellowships that are more field-specific. In general, you should only really care about the fellowships that provide full tuition (as opposed to the many smaller fellowships that offer ~$5k-$10k per year).
Fellowships usually don't actually help your personal monetary situation that much, but dramatically increase your flexibility to do what you want in grad school.
Background: first year PhD student in machine learning at Stanford.
A collection of advice for graduate students I put together some time ago: http://www.cs.indiana.edu/mit.research.how.to.html
It was meant specifically for people at the MIT AI Lab, but much of it is applicable to other STEM fields.
A collection of collections of advice for graduate students! http://vlsicad.ucsd.edu/Research/Advice/
Relevant external advice: Should I Go to Graduate School in Philosophy?
This applies pretty much to any humanities field, and only somewhat less to the sciences.
If you are considering a Master's degree in some professional area to further your career, try to get your employer to pay for it. If they won't pay for it or contribute any money toward it, don't apply just yet.
When considering a professional MA, look at how long this program has existed. In recent years many schools have created near-worthless Master's programs because they are a source of cash for the university. For example, if the school is calling a business degree a "MA in Organizational Business Leadership," it may be worth less than their MBA.
If they won't pay for it or contribute any money toward it, don't apply just yet.
And then what? Wait for them to change their minds? Switch employers?
Via the blog of Matt Might, Productivity tips, tricks and hacks for academics. The table of contents for his advice is:
I found most of this helpful for my current experiment in autodidacticism, but you could probably also get good results using it exactly as intended in academia.
I'm not sure whether this piece of advice is generally useful or not, and it's almost certainly variable depending on field; but I do wish I had followed this when I was in graduate school.
Fairly early on, choose a thesis topic or problem you're interested in, and pursue it. Don't get side-tracked into something just because it's what the department or your advisor is working on. In fact, I'd go so far to say you should pick your thesis topic before you apply. Use that to help you decide where to apply. If you don't have a thesis topic you're committed to, you're not ready for grad school; and should stay out.
If you can swing it, get informal approval for your topic and an agreement from a faculty member to serve as your advisor before you apply. This is easier if you're attending grad school the same place where you're an undergraduate, but it can be done as long as you have some notable research chops as an undergraduate.
I heard the opposite too: don't try to push your own research too hard, especially in the beginning, but try to find something the others in the lab group are working on, learn stuff from them, and after a while you'll end up with your own ideas anyway.
Pros and cons for both of the approaches exist, but "picking a thesis early on" might be hard as you don't necessarily know what the good problems are in your field. But that might depend on your field / advisor too.
Perhaps. All I can say is I was told that too; I tried that; and it really, really didn't work out. I think I might have been more successful had I focused on my own interests more. Certainly looking at my career in my adult life, almost all my biggest successes, with maybe one exception, were when I chose what to work on instead of agreeing to work on someone else's idea.
Of course you do need to adjust this for your field. If you're working in pure math or Roman history, it's not all that hard to do your own thing. In experimental high energy physics, maybe not so much. If you need a million dollar laboratory to get started in a field, then you may not have a lot of choice in what you work on. Though even in the experimental field I'm most familiar with, observational astronomy, it still appears to me as if the most successful people did their own thing. It probably does matter than in astronomy, it's standard practice to allot telescope time based on proposals rather than ownership.
Also, of course, if you can decide early on your area and aim at the program that does that well, then that's the best of both worlds. If you know you want to work on high temperature superconductivity, you're better off in a department that does a lot of work on solid state physics and better yet superconductivity specifically rather than one that specializes in string theory or experimental high energy physics.
In any case, however, I think it's pretty important to start doing some kind of research as early as possible. My own experience is with math grad school, where it's common to just focus on taking classes for the first year or two; but it's better to also be doing research during that time if you can.
Fairly early on, choose a thesis topic or problem you're interested in, and pursue it. Don't get side-tracked into something just because it's what the department or your advisor is working on. In fact, I'd go so far to say you should pick your thesis topic before you apply. Use that to help you decide where to apply. If you don't have a thesis topic you're committed to, you're not ready for grad school; and should stay out.
This may actually depend on the field. In PhD programs in linguistics in the US, you are usually expected to pick you thesis topic only in the third of five years, and you actually have to work on other topics, too. The programs are structured in a way that you wouldn't even have the time to focus on your thesis topic right from the beginning.
See also Deliberate Grad School for how to make best use of your energy and time as a graduate student.
Via the blog of Matt Might, Productivity tips, tricks and hacks for academics. The table of contents for his advice is:
I found most of this helpful for my current experiment in autodidacticism, but you could probably also get good results using it exactly as intended in academia.
This is good advice. Strive for real understanding rather than rote memorisation.
(is this too obvious to be worth mentioning? Probably. Unfortunately I have seen several doctoral students fail and in hindsight it appears to me that this was part of the cause of that failure.)
There was some support for the idea of starting an advice repository for grad students much in the same tradition as the Boring Advice Repository and the Solved Problems Repository started earlier by Qiaochu_Yuan. So here goes.
Please share any advice, boring or otherwise, for succeeding at grad school. I realize that succeeding might mean different things to different people, but I believe most people largely agree with what it means in this context. Feel free to elaborate on what you believe it should mean, if you have views on the subject.
I am a theoretical physics grad student, so I'm personally more interested in advice for mathy disciplines (i.e. physics, math, CS), and I also suspect that there are many grad students from these disciplines on LessWrong; but advice for any discipline is welcome as well.
Advice is welcome from anyone, but please do mention your background for providing the advice so that people can weight the advice accordingly. For example, I would be more be open to listening to advice from someone who has completed a very successful PhD, than from someone who has simply interacted with a lot of grad students but has never been to grad school.
Also, feel free to link to advice from other sources, and maybe quote the most useful parts in what you read. Remember, this is meant to be a repository, so that people can come and find the advice, so don't worry if it seems to be something most people would've already read or known.
Thanks!