Thinking of Doing a PhD? Take this simple test
blog.prof.so
blog.prof.so
I went to grad school because 1) Chicago physics was famously challenging and I wanted the challenge, 2) Everyone else I knew went to grad school - I didn't know how to look for a job, 3) Chicago was a big city with good live music and nice architecture.
All were wrong - the only acceptable answer I believe is "I love science so much, I want to be a scientist for the rest of my life and nothing is going to stand in my way."
What happened was: 1) The challenge was 100x more than I really wanted. I found out early I didn't want to be a scientist, but decided I would stick it out like a perversely beneficial jail sentence. 2) I'm a very, very, very social person. Oops - big mistake. You don't make enough money to date. The mental challenge of living a lifestyle in complete opposition to my core personality was the most difficult challenge (5 years in a dark basement trying to detect light from single semiconductor nanocrystals). But, I found out I could take loans and moved to the artist neighborhood - punk rock, dating and beer helped. (Wine-women-song? Sex-drugs-rock n' roll?) 3) I met some of the most interesting people I've ever met in my life and that made it all worth while. I did some cool things and in the middle of the financial crisis I was able to make a career change because the Chicago physics Ph.D. superficially let me get my foot in the door. 4) I went to a NATO physics conference in Turkey, met a non-scientist woman and married her. Now I'm a capulcu. 5) Having a Ph.D. is a great conversation topic at parties. 6) I did some really cool science, but was exposed to many carcinogens and high voltage equipment at a young age.
My Dad was a Marine and I feel like I went through a Mental Marine Corps, no disrespect to the real Marines. Boot camp is not fun, but it turns you into a man of a sort. The first 2 course years were like a boot camp.
The financial impact of not entering the job market hits you even for years after you finish your Ph.D. You'll be behind other people your age for awhile.
I should just turn this into a blog post! HTH
I have a real question about this: is there something in your head that prevented you from stopping? Is it just something that has always been a part of you, or did you just make a decision that for once in your life, you were going to stick with something?
I was unmarried, no mortgage or car payments and I had already completed 2 years out of an estimated 5.5. I just had to ignore my annoying advisor, focus and try to enjoy the cool, interesting parts of the science. I loved machining my own metal parts. And also I had to get away at times and try to have a life outside the lab. So, I decided to stick with it.
No regrets - I'm 44 now, and I admit I was fairly bitter about the experience for at least a decade after I finished.
The last thoughts are: Lot's and lot's of work. Can you be force-fed your favorite food 24x7 for 5 years and still like it? Like how Homer Simpson thwarted the devil force feeding him donuts?
I did have an office mate who worked 9-5, was a 6'2" former speed skating champion of Canada, wife and kid and was always planning to work for McKinsey and company, which he did after completing his Ph.D. in 4 years. Other people have different experiences. I was a hard worker, other people were brilliant.
There's also, I believe, a CMU computer science "guide to graduate school survival" out there.
I don't think that this (somewhat self-deprecating) graduate school literature is unrealistically negative. Academia is pretty awful.
Life-wise, graduate school is a pretty negative experience. If you enjoy the subject matter and have an almost obsessive need to dive into it, it's a great time in that regard (and you will be spending 60+ hours per week on your work) because you can really study without having to deal with the bullshit that professors have to fend off (committees, tenure politics, grant-writing). The rest of your life will be somewhere from mediocre (if you don't care about the academic game, already dead-set on leaving post-PhD) to awful (if you try to play for keeps); even successful and happy graduate students experience this.
The upshot of graduate school is that, except for the money and low status-- and those aren't issues for everyone-- it's actually better than being a professor. You don't have to serve on committees or sweat tenure decisions or disciplinary hearings for cheating undergraduates, and you have a 5- to 7-year period where geographic moves under adverse circumstances won't happen.
I don't think grad school is like that for everyone. My undergrad had such a huge workload that I rarely had time for any kind of fun. Grad school so far is like the college that I didn't have, except I also get to work on research that's really exciting to me. I'm also kind of young for a grad student so I can hang out with undergrads just fine. It's a win-win.
Also, you're a douche for bringing up irrelevancies like that.
Also I'm pretty sure I've seen you say that you're proud of the fact that your perspective on life isn't typical -- so at least own that fact here.
FWIW, much as I get annoyed by Michael's constant negative comments about Google (experiences which are fairly foreign to my own experience there), they are still his experiences. Take them with a grain of salt, but take everyone's experiences from the Internet with a grain of salt.
Also FWIW, I have a number of friends who are generally shiny happy people who were basically ground down into dust in their Ph.D programs. They stayed for the whole time and not just the first year, but around year 4-6 even the most mentally stable and cheerful of them start saying things like "My life is miserable. I just want this to be over."
You also seem to have read a personal opinion into my post that simply isn't there!
Structure of this thread:
MOC: I spent a year in graduate school. Life-wise, graduate school is a pretty negative experience.
Shardling: Probably worth pointing out that MOC has an extremely negative view of many of their life experiences.
That's exactly the form of an ad-hominem argument: Person A makes a statement, person B brings up some fact about person A that would lead them to make that statement, ergo person A's statement is invalid. The problem here is logical, not personal: just because MOC has made negative statements about other things does not mean this negative statement is without basis.
I read no such personal opinion into your post: I'm attacking your logic, not your tone.
http://plover.net/~bonds/adhominem.html
In contrast, when someone offers an anecdote about their experiences, or in general offers their subjective judgement, then knowing something about them is damn important! For instance, if I knew MOC was a compulsive liar, that would certainly be relevant. Likewise, if MOC was in general an optimist who was loath to ever say anything negative, that would lend extra weight to their comments on grad school.
Even at the same school, one person reported to me that while he was in his second year his supervisor told him he probably had enough material to pass if he wrote it all up - while another person worked long hours and reported to me that his supervisor had shouted at him for not coming in to monitor his experiments on christmas day. One person went on to a research position in the private sector and feel it set them up for a good career; another hoped to enter humanities academia, but wasn't able to find any jobs and ended up doing office admin work that barely needed an undergraduate degree.
Even for the same student, some parts of the process will be enjoyable and fascinating, other parts will be frustrating and tiresome. If you had asked me two years in I'd have told you doing a PhD is pretty great - by the end, having gone through the process of writing up, my opinion pretty inverted. I decided a career in academia wouldn't suit me at all.
If you boil the experience of doing a PhD down to the essentials of the experience, there's very little left because the experience varies so much.
I didn't opt for a phd but I sometimes wish I did. I answered C to every one of these questions.
I will give an answer focused on STEM field Ph.D. programs in the US.
Pros:
Professor Career. A Ph.D. is nearly essential for a career as a professor. If you want such a career, then about have to get a Ph.D.
Learning. A Ph.D., both in your coursework and your independent study, can let you learn much more about your field. Some of what you learn might be quite powerful and valuable later in your career, especially if you want to be an entrepreneur and found a business where some powerful, valuable 'secret sauce' technology will be a big advantage for the business.
Jobs. Some employers will pay extra for a Ph.D. Jobs in US national security, working for the Federal Government directly or work in the 'military-industrial' complex are common examples.
Cons:
(A) With a Ph.D., working for someone without a Ph.D. can be awkward. Why? Because most organizations still want to have a hierarchy much like a Ford plant 100 years ago where the supervisor knew more and the subordinate was there mostly just to add muscle to the thoughts of the supervisor. Then a subordinate who knows more can be a threat to the career of the supervisor. Related phenomena include 'goal subordination' in organizational behavior and the Peter Principle.
(B) After the success of Google, some Silicon Valley venture partners concluded that for company founders they wanted graduate school dropouts. After the success of Facebook, they concluded they wanted college dropouts. After the success of Tumblr, they concluded that they wanted founders who never went to college, and we have to suspect that really they wanted high school dropouts. They are also big on recent immigrants who, necessarily, don't have a Ph.D. degree from a US research university.
Getting a Ph.D. Below I give some advice on getting a Ph.D. in 12 parts.
Qualifications: I hold a Ph.D. in Engineering from a world famous US research university where my research was on some applied math. I've been a college professor teaching applied math and computing, and I've worked in applied math and computing for problems in business and US national security. I've published peer-reviewed original research in applied math and computer science. Currently I'm a founder of a startup where the crucial, core 'secret sauce' is some applied math I created.
(1) Research. In any of the better US research universities, very likely the main issue for getting a Ph.D. is your research. In simple terms, do some good research and find that your path is pleasant. Struggle with research and find your life not so good down to much worse.
So below I will give some ideas that can help you do sufficiently good research.
(2) Criteria. The main criteria for research is work that is "new, correct, and significant". Below I will give some ideas that can help you achieve each of these three criteria.
(3) Engineering. In the STEM fields, I'd concentrate on engineering. Of course the 'M' in STEM is for mathematics, so there I'd concentrate on some version of applied mathematics, e.g., 'mathematical sciences', hopefully in a school of engineering where your research can be some mathematics for a practical problem. For just why should concentrate on engineering, see below.
(4) Mathematize. For how to do good research in the STEM fields, my recommendation is to 'be wise, mathematize'. That is, quite broadly the most respected research, especially in the STEM fields, is to find mathematical solutions. Advantages of mathematization:
(A) If you present your mathematical solution as theorems and proofs, then it can be fairly easy for you to check that your work is correct and quite difficult for anyone else to argue that your work is not "correct".
(B) In fields of engineering, nearly everyone struggles with math. So, if you have a good math background, then you can have one heck of an advantage.
(C) Applied math is one astoundingly powerful way to get good solutions to practical problems. So, (I) start with a practical problem. (II) Find what mathematical assumptions are reasonable for that problem and make a faithful conversion of the real problem into a mathematical problem. (III) Using the assumptions, find a solid, powerful mathematical solution to the mathematical problem. (IV) Convert the mathematical solution to a real solution, e.g., via software. (V) Write a paper on the work (and/or start a business to deliver the results). So, in moving logically from the real problem to the real solution (as a paper and/or business), you have taken a detour through some mathematics; this detour can be a big advantage over slogging through just intuitive or empirical techniques.
(5) Achieving the Three Criteria. There is an advantage in being in engineering: You are likely permitted to start with a practical problem. If you start with a recent practical problem, then nearly any solution you find can be called "new" if only because your problem was new. Or, if you are working on a problem in large server farms, how the heck did von Neumann, Kolmogorov, Maxwell, or Newton have already solved it? If the practical problem is important and you make some solid, visible progress on it, then your work can be called "significant". If your solution is mostly mathematics, with theorems and proofs, then it's 'correct' essentially only from passing checks on the theorems and proofs.
It can help your solution be regarded as 'significant' if in some sense it is provably the best possible, that is, 'optimal'. So, maybe your solution is the least cost, least time, least mean square error, least type II error, etc.
(6) Background. A good way to win a 100 yard dash foot race is to start one foot from the finish line. Otherwise, get a head start. Or, get an 'unfair advantage'.
So, for the approach of 'mathematizing' engineering, start with a solid undergraduate degree in pure and applied math. Then get a Master's concentrating on selected topics in pure and applied math.
E.g., even if you want to get a Ph.D. in computer science, as an undergraduate, mostly just f'get about the undergraduate computer science courses and be a math major instead. The undergraduate computer science material won't much help you in computer science research, but the math can be an overwhelmingly strong advantage.
As a math major, after the usual undergraduate calculus sequence, take theorem proving courses in abstract algebra and linear algebra -- the first is useful at times, maybe more so in the future, and the easy place to learn to prove theorems, and the second is likely the most important material in mathematical analysis and applied math.
To continue, take a second course in linear algebra. A good start is the now classic P. Halmos, 'Finite Dimensional Vector Spaces'. It was written in 1942 when Halmos, a fresh Ph.D. from Doob at U. IL, was an assistant to von Neumann at the Institute in Princeton and is really a finite dimensional introduction to von Neumann's Hilbert space. For more, see the books by R. Bellman or R. Horn.
Work carefully through W. Rudin, 'Principles of Mathematical Analysis.' Supplement that with Fleming, 'Functions of Several Variables', Buck, 'Advanced Calculus', etc.
As a crucial start on optimization, work carefully through, say, Chvatal, 'Linear Programming'.
Somewhere get a good theorem proving course in ordinary differential equations; that can be a good start in a lot in applied math and on deterministic optimal control theory.
At one of the first chances, take a careful pass through Royden, 'Real Analysis' and the real half of Rudin, 'Real and Complex Analysis' -- a good course would help weight the more and less important ideas there.
Then a long dessert buffet is Luenberger, 'Optimization by Vector Space Techniques'.
With that background, you can do probability and stochastic processes the serious way via the more serious authors, e.g., L. Breiman, D. Brillinger, K. Chung, E. Cinlar, J. Doob, E. Dynkin, I. Karatzas, M. Loeve, J. Neveu, S. Shreve, and more.
For more, attend research seminars: Don't often try to follow much of the content but just use the seminars as suggestions for new fields, problems, techniques, names, references, etc. Also you may meet some people or learn about career opportunities that could be helpful.
If after a Bachelor's or Master's want to drop out of school for a while, then do so, get a job, stay single, and outside of work lead a simple life and study some more pure and applied math from some of the best sources. Hopefully get some practice applying math to real problems.
Get a collection of real problems that might use for your Ph.D. research (remember, your Ph.D. is to be in engineering). Make some first cut progress on those problems. If you can get some solutions, then write them up as papers. If some of your papers look publishable, then try to publish them.
(7) Ph.D. Program. Now apply to a Ph.D. program. Include your papers, especially the published ones.
Your mathematical background can be a huge advantage. In particular, consider working in optimization and stochastic processes with a solid background in measure theory and functional analysis. Heck, nearly everything going on in a big application, a server farm, a large network, ..., the economy is a stochastic process where we want to optimize.
Do what the department insists on, and otherwise continue your research. Take your best research and submit it as your Ph.D. dissertation. If there is any question about the quality of that research, then publish it; or just submit work that you have already published. That the work was accepted for publication in a good journal tends quickly to settle all doubts about sufficient quality.
In particular, proceeding in your Ph.D. program as outlined here, you have (A) obtained your own background in pure and applied math, not depended on your department for that background, and have quite likely obtained a better background than any of your professors; (B) have selected your own research problems and not depended on your department or its professors for research problems; (C) have done the core of your research in applied math with theorems and proofs which are comparatively easy to show are correct and difficult to criticize; and (D) have used publication of your work preemptively to establish a respected, outside, objective proof of quality.
(8) How to Do the Research. Mostly the mathematics is just math and not very intuitive and is solid and not just guessing. But finding that math, that is, original math, can use quite a lot of intuition and guessing for finding what might be true and finding ways to prove it is true.
My view is that the most important work in math research is intuitive with a lot of guessing, a lot of simple models, and a lot of simple, intuitive, testing of intuitive guesses.
(9) University. Generally you are better off at the best research university you can get into. The less good universities can force you to jump through no end of silly hoops and be so insecure in their own expertise as to delay and delay saying that your work is good.
(10) Courses. At a really good university, it may be that the graduate courses are not much like undergraduate courses and, instead, are essentially just introductions to narrow parts of research by experts in those parts and, really, intended only for students wishing to pursue research in those parts.
(11) Done.
Accept your Ph.D. and go do something else.
Your professors may have helped you get a job, if so likely an academic job; thank them, and if that job is what you want, then take it; else proceed with your career along lines you've had in mind.
(12) Warning.
A Ph.D. program can be dangerous, harmful to you and your life and career and even fatal. If you are not well protected with your own background in, say, math, your own research problems, your own research, and your own publications, and hopefully your own financial means, then your education and much of your life can be in the hands of others who can be clumsy, competitive, nasty, arrogant, domineering, abusive, destructive, sadistic, incompetent, etc.
It can be that, really, your professors don't have any good research problems for you. E.g., even in an engineering school, they may have nearly no contact with real problems from off campus and, thus, little or no help in finding a real problem for your start. Your background in each of real problems, math, computing, and business can easily be much better than theirs. Each of your professors may have been beating their head against some hard problem for the last 15 years while you have some good insight into some good, new problems you have a good chance of solving. It is accepted that one of the keys to success in research is good problem selection.
You can feel that you are in jail without being accused of a crime, with an indeterminate sentence, tortured by your professors as jailers, and with no chance of parole.
There is a special warning for students who made Valedictorian in high school and PBK, 'Summa Cum Laude', etc. in college. In the text version of D. Knuth's 'The TeXBook' is:
"The traditional way is to put off all creative aspects until the last part of graduate school. For seventeen or more years, a student is taught 'examsmanship', then suddenly after passing enough exams in graduate school he's told to do something original."
So, a student who has done really well based mostly on fantastic memory, pleasing the teachers, dotting i's and crossing t's, doing just what was requested, working desperately for praise and approval from others, terrified of any chance of criticism, out to 'change the world' in major ways or bust, can find themselves in a situation of inhuman stress, then depression, then incapacitation, then more stress, then clinical depression, then death. No joke.
One question: why "stay single"?
If you're looking for a more serious analysis about whether you should do a PhD, see here: http://careers.guardian.co.uk/phd-right-career-option
-Hey Dr.X, I wanted to ask your honest opinion if I should go for a phd?
-No.
-Why?
-If you were going to go for a PhD, you'd not be asking me. In fact, you wont be asking anyone.
Interesting, the question about family/friends is what peaked my interest. My girlfriend of 10 years is about ready to kill me if I commit 4-6 more years.
However, I can't stop thinking that tests where the outcome is based on Mostly A's (or B's or C's or ...) are designed for pre-teen pupils deciding whether they should break up with their this-week boyfriend or have a chocolate or vanilla ice cream.
1. When you finished your undergraduate degree, you ...
Worked for six months as a research assistant, and realized that while I liked the work a lot, I liked the idea of asking my own questions more, and knew there was no way I was really going to be able to do that without a PhD, regardless of how very supportive and generally awesome my work environment was.
2. You think that the hardest part of postgraduate study will be ... D. getting an appointment with your supervisor
Hard, but not the hardest. The hardest was when the "What am I doing with my life, is this all a mistake" changed frequency from once a semester to once a month, then once a week, then toward the very end essentially a rolling wave of panic and writing.
3. You like the idea of research, because ... D. you are wholly unemployable
This one made me roll my eyes a bit. I'm employable, and more employable now than when I started (whether or not going from an MS to a PhD changed much is up for debate). I like the idea of research because I like asking questions that haven't been asked. I like planning the approach, and seeing it come together, and ushering said idea to print.
4. When confronted with a difficult problem to solve you tend to be ...
Staring at the whiteboard I bought from an office liquidator. Usually with markers of about 10 colors.
5. If faced with a challenge requiring a wholly new solution you usually ...
Make sure it can't just be simulated first.
6. If asked to write up your work you ... D. spend a week configuring LaTex appropriately
Smirk at the math/physics/CS types who are convinced that their way is the only possible way science gets done, and go back to Powerpoint. Keynote if I'm feeling flashy.
7. Somebody criticises your discipline, you ... Since it's a fairly small number of specific criticisms, by now I've got a pretty well developed tier of questions to help guide the conversation. Did you read X? In X, did you notice Y, or read the companion article by Z?...
8. When it is suggested that that the solution to a particular challenge might be best found within another discipline you ...
I'm not at all surprised, considering my field as a discipline has kind of camped out at an intersection and shamelessly stolen from others.
9. You have told your family and partner that you are considering doing a PhD, they are ...
They were supportive at the time, and supportive still.
10. You will be part of a research team, this will allow you to ... Lab Happy Hour.
11. Your friends say you are ... "in my program, he's one of the infectious disease guys."
A is the disengaged MacLeod Loser, slightly motivated by social acceptability but averse to hard work and risk.
B is the slimy and superficially impressive but unoriginal executive (MacLeod Sociopath) alpha male.
C is the true Technocrat, the problem-solver who's an ideal student but generally "difficult to manage" in the workplace and usually gets fired a couple times before finding the right niche.
D is the terminal middle manager (MacLeod Clueless) whose self-deception prevents him from accepting the fact that he's actually checked-out (in practice, if not in mindset).
c, c, c, c, b, d, c, b, c, c, c