
Thinking of Doing a PhD? Take this simple test - denzil_correa
http://blog.prof.so/2013/06/test.html
======
sblanton
Here's my two cents (I got my Ph.D. in physics from U. Chicago):

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

~~~
ebiester
Every day you're Capuling? :)

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?

~~~
sblanton
I'm pretty tenacious and don't give up easily in general, which has led me to
go down with several sinking ships (women and startups). I did realize I was
involved in something special - the hard part was getting accepted to the
program and for condensed matter physics, it was fairly straightforward to get
your ph.d. (not easy, straightforward). Pick an exotic material, do a
measurement no one has done and write about it.

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.

------
jdotjdot
I wish someone would post an article that actually provided a serious,
levelheaded view of the ups and downs of a PhD as well as what it's actually
like instead of the overly negative articles? I understand that it might not
be what it seems, but it's hard to figure out what's for real and what's just
somber humor for the uninitiated.

~~~
michaelochurch
There are plenty of those. Here's one:
[http://www.cs.unc.edu/~azuma/hitch4.html](http://www.cs.unc.edu/~azuma/hitch4.html)

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.

~~~
shardling
Probably worth pointing out that this particular poster has an extremely
negative view of many of their life experiences! (e.g., look for their
comments about working for Google.)

~~~
michaelochurch
Actually, my year of graduate school was pretty positive, as far as things go.
No complaints. I did look ahead and realize that academia was not the best
deal in the world.

Also, you're a douche for bringing up irrelevancies like that.

~~~
shardling
I think that, if someone asks for a level-headed analysis of grad school, it
is totally worth pointing out that an anecdotal response is from someone that
has highly charged and divisive opinions about many things, especially
institutional culture!

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.

------
graycat
Part I

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.

~~~
graycat
Part II

(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.

~~~
abrichr
Thanks for this.

One question: why "stay single"?

------
eugenesia
If you're able to make a living doing a PhD (from your stipend and being a
teaching assistant), it might help to tide you over till the economy improves.
But obviously, this article is just for fun!

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](http://careers.guardian.co.uk/phd-right-career-option)

------
tumanian
My best anecdote of thinking about going to PhD, was when I went to a prof I
knew( not my adviser, somebody who I took class from), and asked if I should
go for a PhD. The conversation went

    
    
      -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.
    

After that conversation I went for my summer internship at Microsoft Research,
where the creme de creme of computer science congregates, and yes, he was
right - the best scientists cannot even imagine having a job and not doing
research.

------
mekpro
My favorite choice is D) asleep. now I realized I should get my PhD now !

~~~
dnautics
if you're IN a PhD program, you definitely shouldn't be doing a PhD.

------
klt0825
I've been reading far too much about the downsides lately when trying to
decide if I want to do it, so this was a fun diversion. I'm 28, fresh out of a
CS MS program, work full time at a job doing computer security 'research' and
really still feel like I don't know as much I as I want too.

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.

------
ziko
The test might be perfectly adequate to decide whether you should do a PhD.

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.

------
rietta
It thinks I am already a PhD student; funny! Neat. I do daydream about
applying for the Computer Science PhD program at Stanford and moving out to
the bay area, but then I snap back to my senses and focus on building my
company.

------
tome
Funny, but not to be taken too seriously!

------
kirk21
Great article! We're creating a tool for PhD students: bohr.launchrock.com

~~~
jb17
I watched your video, but I feel like it didn't quite tell me what 'bohr'
actually does to help me write (or read?) papers.

------
gdonelli
Funny! Under no circumstances, avoid doing a PhD at all costs

------
Fomite
Answering as a newly minted PhD in Epidemiology in the US, with my thoughts
and commentary on the "Correct" answers.

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."

------
michaelochurch
I actually looked at this from a different perspective: the workplace. I was
only in a PhD program for one year (left to work on Wall Street) but have 7
years in the industry.

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).

------
mjhea0
lol

c, c, c, c, b, d, c, b, c, c, c

