Eigen

Also to note, you can be "fired" from a lab/by a PI, but not kicked out of the program. The two are not synonymous. I think the important thing is what the HR/hiring individuals would consider your dismissal, not the technical term. If your advisor will say he fired you and you don't list it, they will likely consider it unethical to not have put that you were fired. The technicalities of whether you were "fired" or not won't really matter in that case.

I actually started at my grad school a couple of months early, and really am glad I did. Was able to get all settled before most people arrived.

NIH and NSF also have searchable grant databases you can check- will show you total funding, per year, and how long the grant will last.

You're strongly conflating correlation and causation. The fact that average stats are high does not imply that they're weeding based on the stats. Rather, it implies that a number of the successful applicants had high stats. This is the main reason I'm arguing that schools posting stats from their accepted students on the website can be bad for applying students- it makes them think they need those stats to get accepted, when the chances are it was the rest of their materials that got them accepted, and they also had high grades and scores. You also say you don't mean to be condescending, but in your first paragraph, you assume that my experience as a current grad student isn't valid (accuratE) based off of a grad student you happen to know who didn't apply broadly and isn't familiar with other schools. As you say, she openly admits it. I'm more comfortable speaking broadly than she is, likely due to a broader range of experience. On the flip side, I'd argue that you seem to be speaking quite broadly with no experience past having applied to schools.I don't really feel I need to convince you of my experience, however. You're the one that keeps calling my opinion into question based on assumptions about my background and experience. Most people in academia have a very small "N". The average professor has been at 2-4 schools over their entire career. That said, you'd be amazed at how similar things are across disciplines and across schools within disciplines.

I was more assuming that after being in grad school for a while, I know more about the admissions process than you do applying. Stats are used to weed people out, yes. But focusing on that is pretty useless. There are, in my experience no hard and fast minimums that the rest of your application can't overcome. Schools weed out applicants, but it's rarely entirely based on stats. Your assumption that schools that don't state they weed out applicants based on some numbers that they don't post seems quite unfounded, and I have yet to see you base it off of anything. The selection process at most schools is the same- faculty roughly rank, and then pick out students who they think would be a good fit, and then the committee discusses those. It rarely goes the same year-to-year, and it's not a mechanical process that can be easily described, because what the school is looking for changes year-to-year, depending on their needs.

I'm actually fairly familiar with applications in Psychology as well, and I can assure you that it's not all about stats. I actually can't think of a field that *is* all about stats. But that was a quite condescending worded assumption, that I was only familiar with or talking about one field.

Because stats are the least important part of the application, and listing them just reinforces the impression that they matter. As evidenced in this post, here. The stats of the people accepted in the past (especially averages) are pretty pointless in the scheme of things. Your stats will effect things, sure, but good stats don't make up for bad SoP, references, research experience, and the rest of your package. And bad stats will only do so much to an otherwise outstanding applicant. And as to 1, a qualtrics system reinforces the view that stats are important. They really aren't. You can't reduce applicants to numbers, every bit of how they write, how they put together their CV, and what they say in their SoP actually does matter.

I didn't have as much of a problem with 10, I think 3 and 4, and potentially 1, are as damaging to applicants as they are helpful, perhaps more so. I think you also underestimate how much time it takes to deal with hundreds of emails from propsective students. I'm also clear as to what you think the admissions "game" is, other than trying to show that you're the best fit for a position?

I started with an untenured professor, about two years in. Since one of my worries was what would happen if I didn't get tenure, I asked both him and the department chair. In my case, the chair told me they don't hire people unless they plan on giving them support and tenure, and that the department would support me even if something happened and tenure wasn't granted.

There is always so much discussion on these boards of transparency and "standards". This isn't a numbers game. It's a fit game. Faculty are going over CVs and "hiring" the people they think will fit best in the department, and be the most successful both at that school and long-term. It's just like any other post-undergraduate position- everything about you matters. Companies don't hire you because you passed a set of bars that gave basic requirements- they hire you because something about you, your accomplishments, your history, or your personality made them feel you would be a really good fit at the company, and it would be mutually beneficial. The same is true for graduate school, and the same will be true when you finish graduate school and start looking for jobs. Graduate schools don't "owe" it to the applicants to be transparent in their process, or how they select applicants. They certainly don't need to justify it to anyone but the administration at their school. They have the right to choose the people they think would best fit their labs, their departments, and will do the best working with and for them. This process is really not significantly different than a job application, and has a great deal more communciation and transparency than any of those systems do.

The US is tricky on that. Federally, we're considered employees, but a special class of employees. Our state specifically says we can't be employees. The NLRB goes back and forth every time they hear a case for unionization- hence why UC grad students are under the UAW union.

Grad school in STEM (and even different areas of STEM) is very different from the social sciences, which can be very different from the humanities. It all depends on your school and advisor, but how much of a role your advisor and committee have in your everyday life is very largely discipline specific. Bench sciences in STEM are very lab-centric and operate more as small businesses- your boss (advisor) can have huge impacts on your life in and out of the lab, just like a boss can in any other job.

While I mostly agree with this, at least in the lab sciences there's a much more significant employer-employee relationship. I think that's the better working dynamic than master-apprentice. There's a reason my field rarely refers to advisors, and primarily refers to bosses. A number of labs in my field even have employment contracts- deliverables, salaries, allowed vacation time, salary, raises, required work hours per week, etc. And these are directly between the grad student and faculty member, without the input of the department or university. I think there's some leeway to sit down and discuss expectations (although ideally, I think that should happen when the person joins the lab), but in the end the professor (PI) is paying the student (employee) for their time in the lab, and there are specific expectations with relation to that. If a mutual agreement can't be reached, the student/employee is perfectly within their rights to quit/find another lab, and if the PI (employer) feels they are not getting their "moneys worth" out of a graduate student, they are perfectly within their rights to fire the graduate student. Hopefully, expectations are clear up front and there's good communication, but in the end it does come down to the employer having the power to (within reason) make demands of what is and is not reasonable time expenditure. The lines also blur a lot depending on funding (i.e., you're teaching and so funded by the department and not your advisor, or you have an external fellowship). That said, our original poster has not logged on in quite some time, so our discussion here is mostly academic. I think for those interested, the parallel post (and responses) to this exact same post on the CHE forums is illuminating.

In Chemistry, funding is generally full 12 mos, so summer funding isn't a big worry. Authorship is usually pretty set and straightforward- tenure requires last author publications with students, so you usually get good publication opportunities. Number of ours per grad student per year is good to check, but it will be highly subfield dependent. Per capita funding is important, because it's what will actually pay for your work. Having to shoestring together projects with ancient reagents and partially functioning equipment isn't a good experience. You want to make sure that PIs in the department are consistently winning large grants, as it indicates success of their research projects and goals, as well as money for you to work with. Stipends are important, and even with no research funding you can still get paid.... But it makes research awfully hard.

I'm not a fan of Atkins over either Levine or McQuarrie, personally.

I get that. I'd encourage going with your gut almost every time unless there's a really defined reason not to (obviously, what you're looking for here) . Per capita funding is one thing I would look for (research dollars per grad student in the department) Grad student access as a user to instrument facilities

It's board policy that once created, threads are permament.

You're approaching it from a very quantitative perspective.... I found qualitative more useful. Think of the PI's you're most interested in working for, and the department you found the most resource-heavy, and that had the best environment when you visited. Lots of people underestimate environment, and the mesh of your personality with the PI, but I think those factors drive more people out of grad school than anything else.

And unless they said explicitly that you had to attend the week to be accepted, that sounds like every visit everywhere. Some strong students will get accepted even if they can't visit for some reason, some more midline picks for the school might not get accepted after visiting. Visiting doesn't somehow gain you a leg up over everyone.

The fact that you spent a significant amount of money still doesn't mean the conclusions you're drawing are correct. You have no support for your bolded statement, or any of the other conclusions you draw. They were. Likely =/= guaranteed. Unless everyone who attended was not admitted, it's not a waste of time and money. Furthermore, had you been accepted (and as you are wait listed) the visit would (and does) give you bearing to make a decision. You have no support that the visit had no bearing on your acceptance. As mentioned, it might have had a negative effect. Or you might not have even been wait listed had you not visited, so it might have had a positive effect.

Also, from the data you've given, they invited their top candidates. That means they're considering, strongly considering, all of you. Of the people at the weekend, it seems like you just didn't make the cut? You've been wait listed, so you're still a top candidate, you just weren't one of the ones that got offered acceptance.

You're being very broad here. For most of the sciences, I would say research experience is absolutely required- I can't imagine us considering an applicant without it.

You say that, but there's no skill like speaking all of those langauges, and personally I don't think I'd survive professionally if I didn't. Being able to talk theory with a chemical physicist and talk delivery mechanisms or enzyme kinetics with a biochemist is a valuable skill, and I would argue that getting a PhD in Chemistry means you can pretty fluently read a paper from any journal in the spectrum, and analyze it pretty well. When it comes to papers, for that matter, you'd be surprised how far afield you'll be asked to review things. I've helped review papers from J Chem Phys and J Phys Chem through some electrial engineering and molecular biology stuff. I would also say in modern organic chemistry, outside of some of the most traditional labs, MatLAB is quite useful, to take an example from your post. You can say either case is useful, I'd say a well-trained chemist, regardless of subfield can run a TLC and explain the theory behind it as well as use MatLAB. And a biophysicist isn't going far if they don't keep up with current biochemistry publications, and a biochemist isn't going far if they don't keep up with current biophysics. Some of the journals may use different terminology, but you'd better know both pretty fluently. I just finished helping one of our chemical physics groups set up a shlenk line. They've got a need to synthesize some very specific things, and it's easier for them to set up and do it themselves rather than find a collaborator willing to devote the time to it. They have the basic skills necessary from a well rounded undergrad, and all they needed was google and a bit of help with the initial setup. I also spent a pretty interesting couple of months teaching one of our theoretical electrodynamics groups how to purify and analyze DNA... They were interested in getting some measurements to couple to their theoretical calculations for charge transfer. And again, they had the skills necessary to pretty quickly pick up the lab work, because they were well rounded. When our group is looking for someone, we'd prefer someone that can do syntheis, work with biological systems, has a solid stats background, and can do mathematical prediction and modeling. We really don't have a lot of interest in getting people that have specialized so much they can't easily branch out as the situation requires. That said, it may also be an age/time in degree thing. I notice our first and second years are much more insular in their interests, and it really seems to hurt them in terms of networking with the faculty and other researchers.

I feel like some of the articles on the collapse of MOOCs as a class model need to be linked here, lest they put us out of jobs. We also see the return of "I think I pay all of your tuition, so I'm a customer" when the reality is closer to tuition paying ~12-15% of a professor's salary, with those horrible research projects they neglect you for paying the rest.

So a bit more reading, and it seems like this was a pre-emptive move by the University, whereas if they waited it would have been legal. Cali, for instance, allows employers to access records of treatment that are otherwise confidential IF the persion suing them alleges issues with the treatment. Sounds like the University was preparing for that, and making sure their ass was covered. It's still a violation, and hopefully will be appropriately sanctioned.