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I think different schools have different philosophies as far as that goes. There are schools that admit to the department and have students do very little research for their first two years, and there are schools that admit by advisor and you start research immediately.

My PhD was the latter, but for me it was actually one of the major selling points for me on the program. I had a pretty good idea of the area that I wanted to work in, and I was always bad at learning from classes as opposed to hands-on self-driven learning. By the end of two years, I'd already gotten a lot of research done and moving towards the end of my PhD I was able to branch out within my area and take my own path in a way I doubt I would have been able to do in a different style program, where I wouldn't have had the same depth of knowledge in my field.

All that to say, I think these are two different philosophies in designing a grad program, and each works better for a different style of student. To those that are still thinking about applying, its something that I think should be a serious consideration when looking at program fit.

With regard to your first paragraph, I don't think there are any American universities that admit students by advisor. As far as I'm aware, your admission is a decision made solely by the graduate admissions committee. Even if you have an advisor ready to take you on the most they can do is recommend you to the committee, not supplant it. When you're admitted there are still criteria aside from research to work on.

I think this is a fundamental difference between American and European universities. In European universities, you can hypothetically join a PhD program without any prior degree at all if an advisor chooses to take you on personally. No such sidestepping can happen in an American institution, and regardless you'll have to take some courses (even if you're only auditing them in effect) before you can begin research. Unsurprisingly, American PhD programs are longer.

I've been on the PhD admissions committee for the Berkeley CS PhD program. Students in many areas are, for all practical purposes, admitted by an advisor. It's not a formal arrangement in the same sense as European programs, but no one gets admitted unless at least one professor will commit to being willing to advise and fund you. For superstar students this is rarely an issue and you have your pick of advisors, but for many admits there is exactly one professor who's identified your background and interests as a good fit, so you're essentially admitted with the expectation you'll work with that professor.

Nothing you say is wrong; you're correct that everyone has to do course requirements. But culturally the course requirements are treated as a distraction from research, and students are expected to start working primarily on research from their first semester. I think this is more or less the case in all top American CS PhD programs, and there are reasons to set things up this way, but it's a very different environment from PhDs in most other fields.

Thank you for the insight. Would you be willing to elaborate a bit on finding a good match for advisor, and perhaps any thoughts on approaching someone about exploring an advisorship?

First step is to be acquainted with their previous research. Understand the direction they are taking and what their interests are. Find advisors whose work you think you can build on through your PhD. Write down what you are interested in working on and how it relates/expands/builds on your potential advisor's. Then contact them sharing just that and start having a conversation - they will surely have feedback and ideas for directions that your research could take.

I'm at an American university, and while technically this is true, an advisor going to the committee and saying "I want this person and I have the grant funding to support them" is profoundly influential, to the point that I would be shocked if the committee said no.

True, but:

1) It's still ultimately up to the graduate committee,

2) Once admitted, students will have requirements outside of research, for better or worse.

I'm not making an indictment of the American PhD system, I'm just pointing out that direct advisor admission and unilateral research focus are very uncommon (non-existant?) in the US.

This is about 180 degrees from what I advise anyone asking advice regarding PhDs in the US. Specifically, I tell them that it is best if they know before they even apply who they want to work with and in what capacity. This accomplishes a few things:

- Removes several potential surprises about what they end up researching. It is very sad to see someone expecting to do research on topic A (which they love) but end up doing research on topic B (one they care about much less) because that’s where the money is or that’s where the open advisor is.

- Helps admissions considerably, especially in competitive schools. If an admissions committee denies an applicant that the professor wants, there will be a lot of explaining to do. I assume that you are not talking about “professional” doctoral degrees like JDs or MDs — those are very different than academic-oriented degrees.

- Helps clarify funding. Will you be a research assistant (the answer should be yes if you want to be an academic), a TA, or what?

- Helps clarify what knowledge needs to be known or learned before entering so they can hit the ground running. This helps with course selection (when there are options), project selection, team selection, etc.

- Know the pluses and minuses of their advisor. The best grad students I have seen have read at least some of the research of all of the tenured professors in the department, and they know who is strong and who is weak. They will also have a feel for the politics. These folks are rare, but they are usually the future big time academics.

As someone alluded to elsewhere in this thread, the biggest winners in the academic game hit the ground running for their phd. The folks who come in with an open mind and are looking to learn often will have extremely dim career prospects.

> I'm not making an indictment of the American PhD system, I'm just pointing out that direct advisor admission and unilateral research focus are very uncommon (non-existant?) in the US.

This might be true in schools or departments with very weak research programs. Even then, an advisor advocating for a specific applicant, even if it is a rare occurrence, would most likely be accommodated.

Note that highly talented (relatively speaking) doctoral students are rare. If a professor can get one that’s a great fit, s/he would not be wise to cross their fingers and hope that person gets in and gets assigned as their advisee. Just thinking of a professor leaving that much up to luck makes me laugh — it would never happen.

"Specifically, I tell them that it is best if they know before they even apply who they want to work with and in what capacity."

I append this with the advice that one should never go to a place where their prospective advisor is the only person they can imagine working with.

Primarily because:

"Know the pluses and minuses of their advisor. The best grad students I have seen have read at least some of the research of all of the tenured professors in the department, and they know who is strong and who is weak. They will also have a feel for the politics. These folks are rare, but they are usually the future big time academics."

Is often something that will only come out in time. You can try to figure these things out, and get a good idea, but there are subtle nuances to people that only comes by knowing them.

"This might be true in schools or departments with very weak research programs. Even then, an advisor advocating for a specific applicant, even if it is a rare occurrence, would most likely be accommodated."

My PhD department worked on the "No specific advisor when admitted, lots of coursework" model, and characterizing it as having a "very weak research program" would make you look like an idiot.

> My PhD department worked on the "No specific advisor when admitted, lots of coursework" model, and characterizing it as having a "very weak research program" would make you look like an idiot.

My comment was a reply to throwawaymath’s comment that US programs usually don’t allow professor admits and don’t have a research focus.

If you went to a good school (as you seem to claim), I am willing to bet that one or more admits were advocated for by a professor and (most likely) ended up as that professor’s advisee. You may not have been told about this, but I bet it happens. As I said elsewhere, strong doctoral students (relatively speaking) are extremely hard to find, and most good professors won’t leave a good fit to chance. Maybe your field is different, but I somehow doubt it.

I will also guess that your school has a strong research focus, since having a strong research focus is almost a defining characteristic of a strong program. Note that OP said “unilateral focus”, and maybe your program does not have a “unilateral focus” (I’m not sure exactly how that would be defined), but that largely seems to be a minor issue of semantics rather than the major issue of throwawaymath’s thesis that US programs don’t usually have a strong focus on research (“non-existent” was the word he used). I know of no good doctoral program that does not have a strong focus on research.

Lastly, note that I didn’t say anything about “lots of coursework” — this is common in US doctoral programs. The issue I commented on is that folks who come in with less focus (I think i said “expecting to be taught” or something similar) tend to have weaker career prospects. This doesn’t doom a less-focused person to failure (not at all), but it does make it tougher than someone who comes in with a more intense focus on research. Again, maybe it’s different in your field, but somehow I doubt it. If you have specific examples, I would genuinely love to hear about them — I personally know of a handful, and they are all due to the fortuitous hire of a new professor.

"If you went to a good school (as you seem to claim), I am willing to bet that one or more admits were advocated for by a professor and (most likely) ended up as that professor’s advisee. You may not have been told about this, but I bet it happens. As I said elsewhere, strong doctoral students (relatively speaking) are extremely hard to find, and most good professors won’t leave a good fit to chance. Maybe your field is different, but I somehow doubt it."

The program doesn't do direct admit like that - I know because I asked. Faculty can advocate, and everyone was matched with an advisor, but for the most part first year funding was not under someone's direct RA line, and a slim majority of students ended up switching advisors (myself included).

Ironically, one of the professors who did recruit the strong doctoral students did so in a way that was a very useful cautionary tale for my own recruiting - namely that it's very hard to actually determine that from an application.

This terribly punishes military servicemen who wish to return to normal life and attempt a phd

Note:just making an observation

Why?

If a qualified member (bachelors in physics, within UW Physics' normal acceptance criteria for grades/GRE/etc.) of the armed services stepped up and said to our research group, "I think gravity is the coolest thing in Physics, I'd like to spend the next 5-7 years measuring it, and here's why!", that person would have a big leg up in admissions to our department.

I've worked with a number of current and former military in our group. To a person, they've all been great and know how to get things done. Indeed, one of our research scientists is a former submariner.

Can you explain why you think this? I entered a PhD program at the start of the summer and I can't think of a way that veterans would be punished in the application process.

As some other commenters have stated, I'm not really following your logic.

They may not market it that way, but they definitely do. In my program, you are admitted by a specific professor behind the scenes. You may end up working for someone different during your first year, but there is a specific advisor who said "I think this person is good and I have money for them."

Sorry to be blunt throwawaymath, but that's just wrong. I am very familiar with several American universities (including Ivy League) where the advisor can admit directly.

I don't mind you being blunt at all, but do you mind naming those schools specifically? I'm still skeptical.

Not OP, but Harvard, Yale, and Penn are three that I can speak to with firsthand experience.

I will also say that, depending on the specifics of the applicant, you might be shocked by what admissions standards can be bent/broken based on the desire of a faculty member to have a specific student. It’s not common, but it happens.

For my PhD program, I specifically looked for advisors doing the type of simulations I was interested in. There weren't many (1989-1990 time frame). I found one who on paper looked great: lots of good recent publications, assistant prof (she was working on getting tenure, so she was hungry), she had reasonable grants for a theorist, and she needed an apprentice.

Having that helped my application. I started working for her before starting school.

I still had to take courses. I passed the PhD qual test on entry, and had 2 years worth of courses to take. Transferring in some of the masters courses helped some. I offered to test out of the courses, but it was explained to me that the physics department liked their revenue, even though most of the money coming in was research grant based. The BS I had to go through to take a chemistry course which would have been helpful was a side effect of their love of inbound revenue, and dislike of outbound payments.

Basically, I think the economic model at my alma mater was quite broken. This model generally governs behavior of schools, departments, etc. Having a group to start working with helped me clear some of this BS, but I still had to deal with other crap.

Strictly speaking, you're right, students aren't admitted by an advisor. However, often they are admitted to work with a specific advisor. That is, there are schools where an advisor cannot unilaterally get you in (its up to the grad admissions committee), but unless there's someone that's wants to take you as a grad student, you're not getting in.

It can vary by specialty. A friend applied to several schools for graduate work in geology; the admission process was explicitly admission into a designated professor's research group.

> But also because it makes the PhD not much different than working in industry.

I believe this is viewed as a feature, and not a bug. For the most part, academia serves as one of the few reliable ways to emigrate to the U.S., and exploits that fact to generate a large pool of inexpensive labor. In exchange, these students are rewarded with a US visa and a comparatively well-paying job.

Neither party expects these graduates to stay in academia, so the ability to follow orders, work to a deadline, and solve highly-abstract problems provide a much more tangible benefit than inculcating the creativity, communication skills, and bureaucratic know-how that differentiates successful professors.

In many ways, including these reasons, I think the PhD is starting to be viewed by some as a "super-Masters degree" that simply requires more work or takes longer, rather than as requiring a distinct, different skillset.

Note that this is based only on my observations of a top-50 US graduate program; this might be totally different in a top-4 program, for example. However, one data point I found particularly persuasive is that in our program with ~300 PhD students, we have fewer than 30 (and probably fewer than 10) students with US citizenship or green cards.

I've observed this myself and it's creating a weird dynamic in data science. More often, companies are requiring PhDs for their entry level data science positions. (Because there's a surplus of people who want to enter the field and it's difficult to tell who will ultimately be successful. Possessing a PhD is a good predictor of success.)

But there are very few American-born students going on to get PhDs who are interested in industry because, well, why would they waste another 5 years in school when they can get software engineering jobs with only a BS or MS? According to this study [1], 38% of all data scientists are non-US citizens and nearly half of early-career data scientist are non-US citizens. It's weird that we're pushing US citizens out of data science.

[1] http://burtchworks.com/wp-content/uploads/2018/05/Burtch-Wor...

When you say "data science" does that encompass traditionally educated statisticians and business intelligence folks? If you only count the practitioners out there who self-identify as data scientists you get a pretty incomplete sample of what the field actually is.

What you're describing as what you didn't expect is how PhDs were done traditionally. It's the more recent US model to have classes and exams.

I posed a question to my advisor in order to get onto the PhD, started researching immediately, and my 'general exam' half-way through was a presentation and viva. Obviously the question changed totally by the time I finished, but that's the nature of research and where it takes you.

I'm not sure why you'd expect to explore computer science as a whole on a PhD. The point of a PhD is to become an expert in one part of the field and to push it to expand what we know - not to gain general wide knowledge. I don't think that was ever the idea - that's what a bachelors is for.

I think it depends on the field. In mathematics I think the expectation is that students need to study for a few years to even understand what the open questions are, and only then can they begin the research.

I'm fully aware of what the point of a PhD is. I wasn't expecting to become a generalist, but I was expecting some time to study some recent results and come up with a tractable research proposal. Indeed, if the purpose of a PhD is to expand the totality of human knowledge, why was it expected that I would publish 3-4 conference papers to graduate? Wouldn't one significant result have been enough?

> Indeed, if the purpose of a PhD is to expand the totality of human knowledge, why was it expected that I would publish 3-4 conference papers to graduate?

This is a question that bothers me quite a bit with respect to EECS (electrical engineering and computer science). In mathematics, one's PhD thesis can often serve as one's first paper (once revised). Funnily enough, the same was true for EECS even at the top tier places in the 1980's - I know of a case at Caltech where the student did not have any publications prior to graduation, and yet went on to become a successful professor.

Is it really true that humanity is producing more knowledge in EECS today per student than it was in the 1980's? I seriously doubt this. In my experience, instead what has happened is that the average "delta" in a conference proceeding has gone down significantly, in spite of the vast increase of words like "novel" and "new" being used, and the ballooning of the average paper length.

In mathematics on the other hand, top quality authors freely admit that a lot of their work can be "implicitly" traced back to the "big names" of the past; indeed this has to be done for conceptual and historical clarity.

I see that you mention Peter Sarnak in your top comment. Peter Sarnak has a a wonderful article at the very end of "The Princeton Companion to Mathematics" on his advice for students. Among other things, he stresses the importance of the "history of ideas", and how it often brings clarity to an entire field.

Thanks for the pointer to Peter Sarnak's advice. I believe this is the history of ideas advice you were referring to on pg 1008 (1031 in pdf):

When learning an area, one should combine reading modern treatments with a study of the original papers, especially papers by the masters of our subject. One of the troubles with recent accounts of certain topics is that they can become too slick. As each new author finds cleverer proofs or treatments of a theory, the treatment evolves toward the one that contains the “shortest proofs.” Unfortunately, these are often in a form that causes the new student to ponder, “How did anyone think of this?” By going back to the original sources one can usually see the subject evolving naturally and understand how it has reached its modern form. (There will remain those unexpected and brilliant steps at which one can only marvel at the genius of the inventor, but there are far fewer of these than you might think.)

Often one "significant result" has to be serialized into 3-4 conference papers in order for it to be digestible and reviewable by the referees.

There are exceptions of course, like Gentry's fully homomorphic encryption, but those are increasingly rare.

> What you're describing as what you didn't expect is how PhDs were done traditionally. It's the more recent US model to have classes and exams.

Classes and exams in a PhD programme? I've never heard of this anywhere - I had no idea that was a thing in the US.

There is an ugly trend in the UK to having "credits" for attending workshops as part of your "personal development". You basically have to go and sit in a workshop pretending to listen to someone talking about academic writing so that some admin can tick a box. Considering even postdocs and RAs have to write reports on how their "personal development" is progressing I don't think the powers that be will be happy until everyone can be placed into a spreadsheet.

I think the UK thing is wrapped up in the idea of a CDT, which seems to be trying to make our PhD programme more like the American style.

I really don't like it!

I don't think PhD students should be sitting in a class or going through as a cohort. You're supposed to be a professional, independent researcher.

My first day of my PhD, I was shown my desk at 9 am and told 'get researching, mate'.

It's still the same in the UK as it always was, just plus this credit thing. If you're maverick enough you can dodge it by being a good enough researcher that they aren't going to kick you out for not attending workshops, but that's probably going to get harder. Most people cram enough workshops into one week at the end of each year to get the necessary credits to "progress".

You can also get credits for publications and attending conferences, but the credits you can get like that are capped at about 20% of what you need. So you can have 10 publications in a year and still need to attend workshops.

> It's still the same in the UK as it always was, just plus this credit thing.

CDTs are also causing centralised admissions and making all students start at the same time in a year.

In the US, this is the case because most US PhD programs do not require a master's degree. From my understanding, you are expected to come in with a master's in many European countries.

Also, many first year students do productive research in the US. It very much depends on you're relationship with your advisor and your familiarity with the subject matter.

I think the two subjects are very different. Math has a much longer history. To get to the edge of knowledge you need to know a lot more because people have built proofs upon proofs for much longer. You need an undergrad plus a year or two of grad to get both the depth a breadth of what’s been done in the past.

In CS the edge of the field isn’t as far away. New knowledge invalidates more of the old, and you don’t even need a CS undergrad degree to be near some of the edges.

It's pretty rare that PhD programs let you truly explore what you want to do. PIs (generally profs) get the vast majority of outside funding so you pretty much have to find a way to align yourself with a prof from day one.

In general a professor is an entrepreneur. They are running a small business where they sell their product ("knowledge") to customers (business and industry) by means of sales and marketing (conferences and papers). Grad students are employees of this business, and of course the prof's incentive is to keep the good ones and fire (graduate) the bad ones, thus the reward for the student working hard is more hard work.

Two notes:

1) I am evaluated on the progress of my students. While bad ones will actually be fired, good ones are more useful to me if they go off and get postdocs etc. Some of the most powerful "businesses" in the field are created by the network of people who all trained with the same PI and then went on to found their own labs.

2) A burnt out, trapped graduate student is not actually one that produces good work, in my experience.

3) Several grants, which are how I fund my lab, will look very poorly on trainees making no progress. There's very little exploitation that's worth a program officer at the NSF wondering if I'm worth there time.

Are there bad, exploitative PIs? Absolutely. But these people are assholes, not the only logical outcome of the system.

But no good student who approaches the grad school process in a sane manner is going to work for a professor whose students stay there for 12 years and don't graduate. A common thing for deciding if you want to work with someone is seeing how long their students took to graduate, where they ended up, emailing them, etc.

My experience does not agree with what you wrote in your last paragraph. Writing code as a computer scientist is equivalent to doing lab work as a biologist or to building instruments as an experimental physicist. You can't do research in CS if you don't get your hands dirty, unless your research in theoretical computer science. In exchange for this, many doors open to you after you finish your PhD that would otherwise be closed (unless you did your research in theoretical computer science). And among the best and the brightest that I met in industry, many are in fact PhDs.

As someone who's also pursuing a PhD in CS, I feel your comment doesn't reflect my situation, or my colleagues'. It's true that I started working on one of my advisor's projects, but the difference between the industry and academia is that I can discuss whatever I want about the project with him, and he will care about it. I am in lead of the project and my advisor acts as an advisor, not a boss.

Of course it all depends on many factors, just my personal experience here.

I remember in undergrad I took a class and the topic of the day was the concept of an inflection point. The way the professor demonstrated it was like this:

Based on time spent and potential earnings forgone, a Bachelor's degree is a good investment. A Master's is a good investment. The inflection point happens, and a Phd is not as good of an investment.

That's all the information I needed to decide to stop after a Master's. Have only regretted it once, when I worked at a company that was owned by someone with a Phd in Economics and with many Phd Economists working there. I felt like a second class citizen and in a moment of irrationality, when the entire employment universe seemed to consist of only this company and ones like it, I thought about going and getting a Phd in my late 30s.

Thank God I didn't. Making about 2.5x as much as I was making then, two jobs later, no further education needed (other than Cloud Guru courses).

Part of this difference is due to how departments are funded: math departments teach a lot of "service" courses for non-math majors. So there are enough TAships to fund most students who want them. Most other programs do not have enough TA positions to support all the students they have.

Source: I'm on the math faculty at a large public research university.

Indeed. By way of comparison, my department has zero TA lines.

Too many CS postgraduate programs just feel like engineering ones. This is why chosing a proper advisor is so important as your intentions should be aligned. Even then, there are things you might need to do to satisfy your program requirements that aren't exactly what you want to do.

Anecdoctal experience: I was offered a somewhat decent scholarship for a Master's program backed by an Oil company, but I would work on specific projects chosen by the company. I sincerely prefered to go for a program/advisor that fit my goal (more on the theoretical CS research) and no grant (the program is free here). This meant that I have to work to pay my bills and study on 'free time'. This works for me personally because I make a more than any program scholarship would pay me while acquiring some industry experience. This can work while I am doing my masters, but It is borderline impossible for a PhD program.

i totally know how you feel since i have felt that way in the past as well :) here's something relevant: http://pgbovine.net/practical-reason-to-pursue-PhD.htm

my two cents: find something where the grants align with your interests, or find a brand-new faculty member who has startup money so isn't as bound by grants in the near term. and if things don't work out, simply leave and go to industry -- with a marketable skill set like what you get from being a CS major, there's no way for you to lose. go wherever has work that you like more.

I have experience with both mathematics and CS departments, and I have exactly the opposite opinion. I think the Old School Mathematics model is absolute garbage and often explicitly and intentionally exploitative.

1. It's not like those math Ph.D.s are sitting around reading textbooks with their advisors.

They are TA'ing service courses. A lot of TA'ing. In addition to TA'ing, they are prepping for a high-stakes exam.

The exam will wash out the 50-70% of people who are needed as temp TA labor but whom the department has no intention of advising through to a Ph.D.

After 2 or 3 years, you pass the exam. Yay! But wait. Reading textbooks with your advisor? No! you need to take a whole slew of courses. Why? Because course enrollment == money and easy/interesting teaching assignments. And good luck getting tons of research done in-between your TA'ing and courses...

Now you're done with courses! Yay! After TA duties, you can spend 100% of your time on research (aka 50% of a 40 hour work week aka 80% of a grad student work week). Except you only have 2 years left :-(

So now it's on to 1-3 postdocs so that you can start doing, after 5 years, what that CS phd student was doing when they "hit the ground running": build a research agenda that resonates with a large enough set of researchers that it translates into a research job.

--

Also, the "one singular result" style of research is unique not just to mathematics, but to a particular subset of mathematics. It's just not a good fit for most research problems, even in Mathematics. I've seen tons of well-composed dissertations focused on a singular, pointless problem.

The hodgepodge dissertations don't have a "beautiful singular result" feel, but almost invariably contribute at least one piece of useful, new knowledge.

Finally, worth noting that the best and brightest don't leave research; they might leave academia, but typically not research.

TL;DR: If you can find an advisor who isn't a slave driver (the majority of them at good places), the CS model is 1000% better than the Math model. You might be hired as a researcher for someone else's research agenda, but at least you don't spend the first 1/3rd of the phd as temp teaching labor stressing over high-stakes exams.

> The exam will wash out the 50-70% of people who are needed as temp TA labor but whom the department has no intention of advising through to a Ph.D.

At which department?

Speaking as a math professor in an American research university -- this is unusual. Pass rates at most places are reasonably high, and professors hope that as many people as possible pass.

It is true that grad students are expected to TA (if they want funding); usually grant funding is not available to support them. But generally the teaching burdens are relatively modest, around ~15 hours a week including grading and office hours.

> rates at most places are reasonably high

If you really believe this, pressure USC's department to start publishing their pass rates each year and pressure your peers at other institutions to do the same. IME departments outright lie on visit days and/or change their definition of "reasonable" any time they accidentally over-admit.

E.g., Berkeley -- one of the few places to actually reveal information of any sort on prelim pass rates -- describes their pass rate as "reasonable" and in the same sentence goes on to clarify that they typically pass 2/3rds of students but of course don't make any promises or anything.

Maybe us Ph.D.s are so damn battle-scarred we don't realize that a 1/3rd attrition rate on a poverty salary is actually really unacceptable and absolutely not normal? Can you name a single software company that works like that?