text:
Is it worth getting a master if I am not enjoying it
After getting rejected by all of my applications for master and Phd, I am now doing a theoretical physics master in my home country. Reason why I hate it;

Most of the courses are the same as in undergraduate level. And the quality of the courses aren't good either.
Half of the professors aren't doing research anymore.
I even got a fail in my quantum mechanic course, which is nonsense because the lecturer did not grade my exercises for the reason that they were not worth grading. This will make me spend an extra semester for this 2 years master.
I have just had a summer internship at Cern and am now continue to work on another project after returning home. So I am now running low on time to do anything.
Half of the time wasted to unrelated courses.
I am broke, course fee is an issues and currently relying on my family.

Reason why to:

My supervisor is really really supportive, and he says that a master degree will make it easier for me to get a PhD?. I want to work on my thesis with him. I really enjoy the project.
I enjoy studying with my friends, which are also hating on the department.
My mom keep getting worried if I don't make any money or not keep on study.
I don't have any other choice but to do this master, it help to guarentee my science career??
There is NO opportunity to do science in my country without a PhD.
There is NO opportunity to do a PhD in particle physics in my country.

My question is: Is it worth getting this master degree. If I were to continue to do this master, is it worth spending substaintial amount of time to get good grades(For PhD applications).
You might say: If you don't enjoy it, then don't do it. But I am affraid that I might make a great mistake in my career path.
I am not that an extra ordinary student, just someone who is curious and want to learn while can earn enough to sustain my self and my needs. All of the scholarships' requirements make me feel uneased

"he says that a master degree will make it easier for me to get a PhD"  Have any students from your program gotten PhDs?  If so, ask them about this.

What exactly is your goal?

To me, describing yourself as “just someone who is curious and want to learn” would suggest that the piece of paper (the diploma, the degree) is unimportant. And if you’re not enjoying or learning from the program, then why continue?  But these are questions that only you can answer. Nobody else’s answer can be right for you.

There are plenty of PhDs that require a master degree. Maybe it is easier in the sense of having more chances (statistically speaking).

It seems that you are stuck in a shitty department. And that's not unusual. Plenty of shitty departments out there in this world. Not your fault.

I am not that an extra ordinary student, just someone who is curious and want to learn while can earn enough to sustain my self and my needs.

In my book, that puts you above 80% of the PhD students I know. Most graduate students will have an elevator speech of why they are pursuing the PhD, something that sounds laudable and good to academics' ears. But most are in fact doing PhDs because they didn't know what else to do with their lives, so decided to extend their undergrad in a graduate program.
Wanting to learn, fulfill your curiosity, and to make a living are all 100% legitimate reasons for going on to graduate school and getting a PhD. Some academics talk about graduate school like it's preparation for the monastery. It's just a job. A job that can be nice to have, but still a job.
Based on the description of your country's resources for students of Physics, it seems that you will have to emigrate to a country that does have the resources. Are you willing to do that? If you are, then evaluate finishing the master's in the context of if this will help you emigrate. I can't tell you if getting a master's will help you emigrate, because it depends on your country and the country you want to move to, your citizenship status, etc.

What I need is just grants, funding. I can move when ever I wish if I had the financial capability. Thanks for your comment!


text:
Proper citation of equations in scientific papers - terminology
Most scientific papers refer to almost any formula that contains the "=" sign by the word "equation". Consider this case:
Let value = function(input) (1) where input is a known input value and value is the result of the function computation. In this situation, there are no effective unknowns (we are guaranteed that no unknowns are hidden in the function expression either).
Most papers (if not all) often refer to expression (1) in sentences like "equation (1) is equivalent to", "referring to equation (1), we see that..".
Some pedantic referees, however, suggest the use of a more proper word (e.g. formula (1) instead of equation (1)).
Is there a grammar reference that solves this seemingly insignificant issue?
Further clarification
An  example of an expression not considered an equation by a referee:
(a+b)^2 = a^2 + 2ab + b^2 (1).

Can you make a real example of a formula that you do not consider to be an equation?

@FedericoPoloni I have to mention that a referee made this observation. To me, from my actual experience, this is close to nitpicking or even outright incorrect since almost all journals use the term equation with a broader semantic spectrum (which encompasses both formulae and strict equations). To me it seems unnatural to use formulations such as "We deduce from formula (1)..".

In addition, what would be a good example where the term formula actually is the better and necessary choice? We all know of Einsten's equation. Technically, it's also a formula in its own right, but people don't call it so.

Strictly speaking the referee is right: the example expression is an equality, rather than an equation.

@MassimoOrtolano Maybe you mean an identity? All these subtly different words are quickly getting out of hand...

@FedericoPoloni Oops, yes of course...

I'm not sure that the last line is really an "expression", because it incorporates the equal sign.

Recent question on Math Educators about the meaning of the word "equation" (albeit one with an accepted answer with which I disagree): http://matheducators.stackexchange.com/questions/11203/definition-of-the-term-equation

From Higham, Handbook of writing for the mathematical sciences (emphasis mine):

Referencing Equations
When you reference an earlier equation it helps
the reader if you add a word or phrase describing the nature of that
equation. The aim is to save the reader the trouble of turning back to
look at the earlier equation. For example, "From the definition (6.2)
of dual norm" is more helpful than "From (6.2)"; and "Combining the
recurrence (3.14) with inequality (2.9)" is more helpful than
"Combining (3.14) and (2.9)". Mermin [200] calls this advice the "Good
Samaritan Rule". As in these examples, the word added should be something more informative than just "equation" (or the ugly abbreviation "Eq."), and inequalities, implications and lone
expressions should not be referred to as equations.

Pro-tip: arguing with a referee on such trivialities is rarely worth your time. Just do what they suggest.

While I agree with everything there, it doesn't answer the poster's question, which is in regards to the word "formula".

Mathematically, one could say that a formula is an equation that defines one side (typically the left-hand side) in terms of the other side. An equation on the other hand states that two expressions in terms of previously defined quantities are equal.
For example, Pythagoras' theorem a^2 + b^2 = c^2 I would call a typical example of an equation: a,b,c are predefined lengths of a rectangular triangle, and it makes a non-trivial statement on how they are related.
On the other hand, if you simply assign a function value, y = f(x), then it makes sense to call that a formula, since you define y in terms of the right-hand side.
Edit: Federico makes a fair point.
Let me just add that "Mathematics into Type" by Ellen Swanson, published by the AMS recommends, somewhat similar to Higham referenced by Federico:

6.4.2 Equations
Do not capitalize. An author is apt to refer to the same display as equation (3), property (3), or definition (3); it can
  become rather confusing if the word is treated as a proper noun when
  references is made to it in so many ways.

which implies that at least alternative names are possible.

I'd say your referee is right.
When you have variables on both sides of an equality, i.e. when you show some relationship between variables, we tend to say this is a formula.
E.g. x + 2y = 3z is a formula.
If, however, one of the sides of your equality contains no variables, just value(s), then we say it's an equation.
E.g. x + 2y = 3 is an equation.
Edit: The "equation" environment in LaTeX can be quite confusing this way, as it is often used for formulas, rather than equations...

Sorry, but from a mathematical viewpoint I think this is nonsense: if in x+2y=3z you move 3z to the other side, then at once x+2y-3z=0 becomes an equation??

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


text:
What to do when the claims in a paper are proven to be wrong?
What can be done to correct an error that might be hiding a certain author's sole purpose of publishing a paper, no matter the soundness of their method?
In a nutshell, the particular case that spawned this question can be summarized in a few sentences:

a paper presents a mathematical construction and proposes a numerical solution for the resulting nonlinear optimization problem
the problem has many local solutions that are not numerically distinguishable
it is impossible to ensure convergence to the real solution without actually starting near it
there are too many local solutions (an infinite set in some cases) to simply test the best sample
the authors claim unconditional convergence to the true solution, regardless the parameters
their results are consistent with their goal, but the mathematical formulation is in contradiction with the conclusions simply judging by the properties of the objective equations.
Hence, such results are, at best, a stroke of luck, if not part of a probably much different approach.

After spending almost one month trying to understand not one, but a series of three inter-linked articles on a scientific subject, I have mathematically proven that the central assumptions and claims in that series of papers were wrong and/or incomplete. As the papers were peer reviewed and even published in reputed journals or conferences, I feel there is a need of saving other people the trouble of wasting valuable time trying to reproduce a falsely advertised behaviour. What is the proper action to take in this situation (for example, writing to the editors of the journal)?

You might be right but you might be wrong as well. If we are talking about 3 articles, one or more authors and at least six reviewers already disagree with you. Are you 100% sure the result is wrong? Can you be 100% sure for that? Are there previous works that you can base your proof on? Because " I have mathematically proven that the central assumptions and claims in that series of papers were wrong and/or incomplete" sounds like a contradiction, since wrong <> incomplete.

@Alexandros to be fair, reviewers don't check correctness. (Maybe in some fields, but not all.) In my experience, in high-energy physics, reviewers check that the paper is internally consistent and that the authors demonstrate awareness of the current state of the field, and they also evaluate the paper on its originality, relevance, and suitability for the journal. They may also pick out some obvious errors. But, assuming that the main result is either plausible or well-justified, they tend to take the authors' word on its correctness.

@Alexandros I agree with David Z on the matter, myself having spotted a mistake in a reviewed paper of mine and corrected it in a revision. Reviewers do not have the time to redo the mathematics (unless they're really skilled in that field and care for that particular problem or if it's obvious enough). While redoing the derivations myself, I corrected a few minor mistakes, probably type-os. These are very common and usually do not change the outcome unless they were used in the authors' implementation. A reader is almost always responsible for redoing the maths.

To sum up: the problem was discussed with 3 of my research colleagues already and we found the same problem, but couldn't fix it ourselves as it's obviously from a category where convergence to a solution is never guaranteed. The proof to this fact can be found in nonlinear optimization textbooks, once the problem is proven to be part of a particular family of such functions (which it is). It's more a matter of whether discussing this error in a paper might be interesting enough for the community, while a short proof could simply be posted on arXiV in no time, but have less "impact".

Even after the update, it's not at all clear to me what "an error that might be hiding a certain author's sole purpose of publishing" means. And, although I don't know what it means, it sounds a lot like you're alleging deliberate misconduct. If that is what you are alleging, you need a heck of a lot more evidence than "the paper contains errors".

Write a paper explaining what the errors are and how they invalidate the results of the papers in question, then submit it to a journal with good visibility and get it published. Writing directly to the journal editors is appropriate only if you have good evidence that the errors in question are deliberate (e.g., the authors have fabricated data in order to obtain the results they wanted).

The only evidence for fabricated results I have is the fact that those results are part of a practical, funded research project that required a concise and reliable solution. I suspect the authors to have actually used a workaround or a different method since their published materials contain mathematical fallacies.

Addendum: you need to keep in mind that a large majority of the errors you encounter in primary research are not deliberate. Authors and referees are not infallible, and sometimes errors simply get through the system without nobody noticing until after they are published.

Accusations of fabrication are a very serious matter, and if they turn out to be unfounded, your reputation will suffer a lot. Unless you have hard evidence that fabrication really did happen (i.e., someone from that group comes out to you and confesses that it did happen), it is better to treat the errors as unintentional errors. It wouldn't be the first time that astounding howlers get past the reviewers.

I agree. Although, in this case, reproducing those results is simply mathematically impossible and can be argumented against. That's why I presume this is not an honest mistake, but might be explained by some sort of imoral conduct: either falsified results, incomplete and incorrect methodology description.

Alright then, since accusing the authors of misconduct is not the focus, then I'll go for trying to publish the proof that their method is incorrect, leaving other authorities to decide what is best to do. Thanks a lot for the pointers!

@teodron Math is hard.  Math errors are easy.  Don't attribute malice where mistake can explain the observed behavior.

@jakebeal I agree. My pledge was somewhat more justified (I don't want to be a "hater" :) ): if you present a mathematical method and claim to obtain certain results with it, then the process involves a practical verification of that mathematical apparatus. It's more improbable that a minor error could have caused the right results, although the published material is not leading to the correct solution. Nevertheless, any constructive points are taken.

@teodron It's more improbable that a minor error could have caused the right results You'd be surprised, especially because there's often a lot of back-and-forth between analysis and simulation.  Having a theoretical mistake and an empirical bug come into coherence most certainly happens, even though it's much rarer than either happening alone.

I think this answer is the best. If you think those three papers are wrong, write your own to prove your point.

I have to accept this as an answer, but, judging by the debate, it's hard to have a panacea for this broad topic. In my specific case, things are somewhat simpler: given a recipe you obtain some results, but the issue is within the recipe itself. Hence the conclusion that it cannot be possible to reach the results once you run into a mathematical fact preventing you practically and theoretically from getting there.

I have mathematically proven that the central assumptions and claims in that series of papers were wrong and/or incomplete.

This is a very complicated statement and it is important to understand it in order to know what to do. The two issues are assumptions and claim.
People often make assumptions to solve difficult research problems under the assumed conditions. If your assumptions are too extreme, or worse known to be wrong, then no one will care about your solution.  The key issue, however, is that if someone later proves that your assumptions were wrong this does not make your results wrong. It just means that the conditions for which you solved the problem are uninteresting.
Given a set of assumptions, regardless of if they are true or untrue, claims based on those assumptions can be correct, incorrect or incomplete. If in a further investigation you realize that the claims are incorrect or incomplete, or the assumptions needed to obtain the claims are either incomplete (i.e., you need additional assumptions) or incorrect (i.e., the wrong assumption was made not an assumption that was wrong). In these cases there is an issue with the research that should be corrected. Most journals have mechanisms for correcting errors or at least alerting readers to errors.
The concept of proving an assumption to be wrong is a strange idea. An assumption is an idea that you take to be true while an idea that will be subjected to testing is generally called a hypothesis (or in mathematics I believe a conjecture). Taking someone else's assumption and hypothesizing that it is true (or false) and then testing that can be very valuable research. Proving that the assumed conditions do not occur reduces the importance of the previous research that assumes the conditions occur, but it does not change whether that previous research is correct or incorrect. In this case you need to decide if the proof that the conditions do not occur is interesting enough to publish.

I admit to have blurred the lines between hypotheses and assumptions. In all, the problem is like a recipe that is conceptually flawed, but still attains the goal. As you suggested, it's probably best to carefully write down the scientific proof of why certain claims are in contradiction with the used methods. It will all boil down to whether proving that a particular problem harbours a well-known case where there's no solution and there are insufficient bits of information to workaround that drawback. My hope is that anyone else who might be tempted to use it in practice will not attempt it.

Also, if their paper proves that P → Q, and you prove ¬P, then you've just proved their paper correct, not wrong! False implies anything.

Basically there's nothing you can do. I had exactly the same experience with a paper written by some Ivy League computer scientists whose algrotihm I was supposed to implement. Their papers contained no information about how they chose the starting points for their optimization, which was a serious problem because there were many local maxima. They had written a software package but it had been withdrawn from circulation.
I discussed my problems with other researchers in the field and was told that it's generally known that "there are problems with that paper." That's as far as it goes, really. It would be nice if there was some way of calling them to account for wasting peoples' time and making claims that they couldn't substantiate, but there's really nothing you can do.

Of course, you could write a paper proving the original work wrong and try to get it published. But experience shows that such papers tend to have a hard time in review, because they challenge a (more or less) widely accepted method. Just consider, even if the method is not guaranteed to yield the optimal result, it may still be "good enough" to be useful for many purposes. Simply refuting the method is thus only of limited use for the scientific community - in absence of a better method they will just keep on using it. Your paper may end up being simply ignored.
Ideally, you'd start from your proof that the method doesn't work and develop an improved method that avoids some of the shortcomings of the original method. If you can show that your new method really improves performance, you'll be in a good position to publish with good visibility. Such an approach would also be a lot more useful for the scientific community, because you don't simply refute the original, but improve on it.
And make sure you publish that code under an open source license in a persistent, public repository, so everyone can use and improve it.

Approach the authors to explain them the issues and ask them how to work together on publishing a rebuke of their own papers. If possible, do so with the help of someone you know who knows them.
Unless you are an authority in the field, in which case you can do whatever you want, it's much easier and more productive to "withdraw" published claims with the authors' collaboration. Also, you might earn a long-term collaboration with their research group.
Suggestion based on how a professor I know (having a h-index around 50) solved such an issue.

In case you didn't notice, there is a series of three inter-linked articles on a scientific subject, in this question.

@scaaahu: so? Are you assuming malice?

No, I wasn't assuming anything. The purpose of my comment was to point out that there are three papers. The complexity of the solution you proposed is quite a bit. BTW, I was not the one who downvoted this answer.

@scaaahu ok, I had not understood your point. IMHO that's all the more a reason to try a collaborative approach: three papers (possibly on different publications) may require three separate fronts of work (e.g. with the respective reviewers or journals), while the asker says they are from "a certain author", so working with said author can address all at once.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
Maximum/reasonable number of authors for a (conference) paper
What is a reasonable number of authors a small conference paper should have?
In my case, this is an interdisciplinary research paper and several people are linked to this work in one way or another. Currently, there are 8 authors and I feel this may seem too high.
Is there any common-sense consensus regarding this limit?
In case there is a field-specific dependence, the main field is Computer Science.
UPDATE: my justification for this question is the increasing buzz around the very issue: author inflation.

This may depend heavily on your field. Could you edit your question to add this info?

Added the field: Computer Science (although the paper is not 100% classifiable as a CS one).

I don't understand the question. The paper has as many authors as it has, no less and no more. (I am a coauthor on a few 10-author CS conference papers.)

@JeffE I'll edit the question soon :(.. the answer xLeitix gave is pretty much hitting the nail on the head: there are many coauthors and some people don't see this with very good eyes - there's an "academic authorship inflation", as termed, that has some negative connotations in popular culture.

A paper with 8 coauthors = there are at least 8 people who have proofread it before it is submitted. The referees will love it!

Eight authors would be suspiciously few in the field of particle physics experiment.

In my field (software engineering), having papers with 6+ authors is uncommon but not unheard-of. Most often I see papers coming out of larger international research projects having many authors, presumably simply because in a large project more hands tend to touch any given piece of research outcome. Further, in larger studies, you sometimes need more manpower to actually carry out the study. If you have a chance to do an interview study with a large group of people, just having one or two interviewers might simply be infeasible because it would take too long.
If you are worried that your large author list will be considered a negative during the review process, this may happen if it is not clear how the large author list is warranted. That is, if you were to publish work coming more less directly out of the PhD thesis of the first author with 7 co-authors, one may ask what the remaining 7 people actually added. In such cases, it is not uncommon to drop subtle hints into the paper about the role of each author. For instance, when you describe your research methodology, you could mention that the first three authors conducted the study, while the remaining three authors were mostly involved with analysis, and the last two authors provided domain feedback and validation of  the achieved results  (if interdisciplinary).

There are some interesting statistics in this paper (possibly a bit out of date)

Thanks, then if it's ok to actually point what who did what (briefly) and if this helps the credibility, then it sounds like a must.

@teodron Yes, it is ok, but this should be approached with some caution. Try to not sound defensive, and make it flow with the paper (strictly speaking, "meta" comments are discouraged in papers). The best way is usually to have a Methodology section, where the contribution of each author can be added rather naturally.

@xLeitix some journals require a specific list of what each one did. Example

@Davidmh Yes, but the OP specifically asked about conference papers (and I am not aware of any conference that does this).

@xLeitix do you perhaps know of any sample paragraph/formulation for this specific case? As far as I remember, I haven't read any paper that did it and I'm confused on how to actually make it sound formal and professional.

@teodron No specific example, but I have certainly written something like: "Interviews have been conducted and transcribed by the first author. Afterwards, the first and the second author have (independently) coded the transcripts using open coding, and produce a set of 14 hypotheses. In a second step, the first and third author have conducted a large-scale survey to validate those hypotheses."

@xLeitix alright, that makes it much clearer, many thanks!


text:
Recommendation Letter v.s. Ph.D. opportunity
Last year, I started collaborating with a high-level professor in the field in a good but not the best institute. Before leaving there, I discussed with her a possible opportunity to having her recommendation letter. Also, I asked about the possible opportunity to becoming her Ph.D. student. She seemed okay about this, however, she told me there will be an interview.
Now, I want to send an email to her letting her know that I want to be considered as her potential graduate student while having her recommendation letter because I do not know yet what options I will have. Her recommendation letter will really help me, but I do not want to lose the chance to be considered as her potential graduate student.
I worry that my asking her for a letter of recommendation, while at the same time asking to be considered for admission as her own graduate student, might look like I am too ambitious! How does it sound to a professor? What are the possible reaction of a natural professor to this? Is it mature and rational to send such an email? If I were the professor, I will definitely realize the student is looking for as many opportunities as feasible, however, I may not consider him as a potential student. Please help me to clarify my thoughts on this point.

Since you have already talked with her about a possibility of PhD, what is the issue in sending an email now?

@Peaceful because I do not know how to write such an email! In addition, I do not know how serious was she about that.

Related: https://academia.stackexchange.com/questions/80572/how-to-ask-for-rec-letter-for-another-program-after-verbal-commitment-to-stay-wi

I think there is a somewhat recent question like this, but I can't find it...

It is extremely common in my experience to ask a professor for a letter of recommendation while at the same time expressing interest in pursuing further work with that same said professor. I did it myself.
Professors realize that they might not be your only option. Placing their students in graduate programs (where ever they may be) always reflects positively on them.
You have actually done much of the hard work already. You have already talked with this professor about your future plans and sought to gauge her opinion on your becoming her student. If she seemed at all open to taking you on as a student, she will also be open to writing you a letter of recommendation.
I would say something like the following:

Hi Professor McGonagall,
You and I spoke briefly last year about some of my plans for graduate school. I am applying to several programs and I am in hopes that I could obtain a letter of recommendation from you. As one of my options, I am planning on applying to the program at [your university], with you as my potential advisor. Is there a time we could meet to discuss these items further? I am available any time next week on Wednesday or Thursday.
Thank you,
mathvc_

Any reasonable professor would be happy to discuss bringing you on as a graduate student and writing you a letter of recommendation for other options as well. My master's advisor did so for me; I have also done so for my own students. If this professor tells you that she will only write you a letter for her own program and is offended that you would look at other options, you do not want her as your advisor. It would be very worrisome to me if advisor was only willing to take me on as a student if I applied to no other programs. It signals an advisor who is a controlling advisor.

I will second the thought in the last paragraph. If this professor is offended that you are asking to potentially become her student, but also looking at other options.......she's likely not an advisor you want.

This depends greatly on both the place and the field. In some places admissions are controlled by individual professors who agree to take you or not. In such a place a recommendation letter wouldn't be needed, just her acceptance.
But in other places admissions are an administrative matter separate from advising/supervising. In such a place or field, both would be desirable, with the letter of recommendation more important for admission.
But if you do need both, just ask. Remind her of the earlier work. Let her know that you would be honored to be her student and ask for a letter of recommendation based on your past work. She will know the rules, of course, and will respond appropriately to the request.
One possible outcome might be the letter only, without an agreement to serve as your advisor. You might need to seek that later or be left working with another.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Mention a specific potential adviser and project in the PhD statement of purpose
I am writing my statement of purpose for my Ph.D. and I want to work in a specific field with a specific professor in the department that I am going to apply for and I have a very good experience in this field. I sent an email for that professor asking if he/she is accepting Ph.D. students and he/she did not respond. I built my whole statement of purpose based on my previous achievements and future plan for that specific area. I also mentioned that I am willing to work with that professor. My statement of purpose tells that I am very passionate about this field and I am only willing to work with that professor (if there were more than one professor working on the same area, I would mention all of them). if that professor doesn't accept new Ph.D. students, will I risk my admission to that school?
Will the committee response be something like this:  "the applicant really knows what he/she is going to do and there is a specific future plan and he/she also got a good experience in this field, but he/she sounds very strict to his plan and doesn't show any flexibility...REJECTED"?

I thought I'd mention a few related questions, like 1) Is it possibly considered weakness in my statement of purpose if I mention that I would like specific people to advise my PhD programme?, 2) Should I include name of potential advisor on my statement of purpose (SOP), 3) Can I mention professors' names in the statement of purpose?. Your use of "only" makes it a more restricted SOP than in any of those questions, however.

@hbak Is this in the United States?

Stating specific professors you want to work with can be a good idea usually I feel. It shows that you have researched the school individually and are not just sending out blanket applications. It also allows for the admissions committee to see a developed idea of what you plan on studying. Whenever I review applications for graduate school, I always like to see that an applicant has given some thought to what they actually want to specifically study. Even if their listed topic is not what they end up studying, I can at least see that they are capable of determining a specific research direction.
All of this being said, it can be a bit risky as an applicant to base your entire application on a single professor and topic. You ask the following question:

If that professor doesn't accept new Ph.D. students, will I risk my admission to that school?

The answer to that question is unequivocally "yes." An admissions committee is not likely to accept a student who is extremely rigid in their proposed plan of study if said plan of study will not be feasible. (E.g. saying "I will only work with Dr. McDonald because she is the expert in the field of rubber chickens. This is only topic I am interested in." when Dr. McDonald is not available to take on more students). Departments on the whole do not like students (or professors) who are inflexible in their research (and teaching) goals.
My advice would be to present your first choice professor as just that, your leading choice. I would then also present one or two other options as backup plans of sort.

I am quite interested in doing research on polymer composition of imitation foliage with Dr. Thomas York. His latest paper on the subject is exactly the type of project for which I want to develop a greater ability. Fake plastic trees is a field that I foresee myself enjoying immensely and I believe Dr. York to be one of the principal leaders on the topic. I am also intrigued by the work of Dr. Linda Petrovic and Dr. Ron Bobb on kettle drums. I have taken several classes using kettle drums and would enjoy pursuing research on the sociological implications of taking kettle drums to funerals. Dr Petrovic's work on the topic introduced me to several questions I had never considered before.

You will ultimately need to decide whether it would be better to be admitted to the school of your choice and potentially not study your chosen topic, or to be rejected from the school of your choice and maybe study your chosen topic elsewhere.

If you tell a department that you only want to work with a specific individual professor and, for some reason, that opportunity does not present itself—perhaps the professor does not have funding for you, or is not looking to take on new students, or will be on sabbatical—then it is unlikely that you are going to gain admission, since you've already stated you only want to work with one individual in the program.
You have the right to be limited in what you want to work on—if that's all that you want to do as a graduate student, then make that clear. But you also have to accept that instituting limitations on what you want will have consequences on your ability to gain acceptance to do it.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Mental health issues and success in academia. Is it possible to be successful after multiple blocks in the early academic career?
So, is it possible to be successful in academia or demanding research fields with Mental health issues? I don't read anecdotes of successful academics with mental health issues. This makes me believe that I could never make it. What do you think?

An extreme example of a successful academic with mental illness is John Nash, who won the Nobel prize for economics and had schizophrenia. Speaking personally, I too struggled with anxiety and low self-confidence during my PhD, as did many of my friends. It's normal and you're doing the right thing by seeking professional help.

I don't know but I think a supportive mentor could make the difference!

It's definitely possible and there certainly are people in academia suffering mental health issues (I did and know many who did). As others have said, you are doing the right thing by seeking professional help. If I could give a piece of advice it would be to be kind to yourself. You managed to successfully complete several publications and complete a PhD in only 6 years while beating mental health issues! It sounds like you are tenacious and talented; this will carry you far.

https://academia.meta.stackexchange.com/questions/4700/how-can-we-better-react-to-askers-who-are-having-a-mental-health-crisis

Look into Imposter Syndrom, and you will see that severe self-doubts are no rarity amongst successful academics. You'll find discussion of coping strategies, etc.

My impression is that academia is a welcoming environment for a broad variety of mental health issues, provided you are on the high-functioning side. But opinions on this will vary.

Keep in mind that applying for academic positions and for grants almost always has abysmal success rates. This could be living hell for you, or the shock therapy that helps you overcome your paralyzing fear of failure.

The vast majority of recent PhD graduates contemplating a career in academia will not make it to a permanent faculty appointment. Numbers vary with discipline, but my extremely rough estimate would be that 1 out of 10 succeed. So with the extremely limited information I have about you, I would have to guess that you wouldn't make it to professor -- because that is my default guess, not because of mental health issues.

To get a better idea of what your personal chances are, discuss this with a trusted mentor who knows you, your track record and the job market in your academic niche. Also, contemplate how far you are willing to go: For example, the more restrictive you are in terms of where you might be willing to move to, the fewer your opportunities.

For almost everyone, there are other very rewarding careers besides an academic one, and for some of these alternatives, having a PhD is useful. If you go for something else, this is not a failure.


text:
Do PhD students at "prestigous" universities publish less as students?
I'm a 4th year PhD student in Education, and I'm noticing a trend that no one seems to be able to explain to me. I'm at a large state school (ranked ~30 in education, better in my discipline for whatever rankings are worth). I've started to stalk assistant professors at schools I'd be interested in applying to, and I've noticed there seems to be a stratification between "good" (i.e. state, UC schools not called Berkley or UCLA) and "elite" PhDs. Most elite students appear to publish almost exclusively in conference proceedings. In contrast, I see a lot of new graduates from "good" school who have 5+ journal publications, several of which are first-author publications. And not in crap journals or anything.
Is there something different about how students at Harvard, Stanford etc. are told to conduct their research. How does this play into hiring? If you went to a good school and have six publications, are you always going to loose out to a Harvard grad no questions asked? I know this is subjective, but I'd love opinions from those who have an idea of what might cause this, or perhaps what is wrong with my observation.
Edit: The field I'm looking in specifically is education.
Edit2: People wanted some examples. As a simple example, look at the assistant professors Utah State University Instructional Technology and Learning Science (a good program in it's field) vs. the assistant professors at Harvard school of Ed.
At Utah state, if you skim through their CVs they had between 1 - 10 (!) publications when they graduated from their PhDs. Harvard? 1-3. Maybe that isn't a full blown study, but let's call it a case study.
Additionally, you could look at the University of Utah Educational Psychology assistant professors, many of whom had no publications at graduation but tend to be from more prestigious school despite Utah State and University of Utah being a little more comparable. This may be a more applicable comparison to the Utah State group.

Sounds like you're talking about CS, do you want to specify a field?

Unless you present hard data, it seems to me you are just seeing confirmation of your bias. One anedocte is one anedocte, thirty anedoctes are 30 anedoctes, ... but n anedoctes are statistics!

Many mathematicians think that what matters is the importance of your best paper, not how many papers you have written.  (And, especially for a PhD student, that paper can be something still making its way through peer review or even still being written up.)  But different people have different opinions and different fields have different aggregate opinions.

EarlGrey (fellow Picard fan?) I've updated with a miniature example.

Knowing nothing about any of the programs, I perused several of their web sites. I think that the various programs have little in common (with respect to curriculum, goals, target audience) with each other, and serve very different needs. Therefore it would not surprise me if their CVs looked different.

Put simply, you’re asking whether it’s possible that hiring committees pick weaker graduates from “name brand” universities over stronger ones from less prestigious universities. Yes, they do sometimes, at least in CS.

Maybe there are some sub-discipline specific practices?  I'm in electrical engineering, and in some sub-fields, journals are very important, and in others, conference publications.  In some sub-fields, journal articles are 2-3 pages long, whilst in others 12-15 pages long.  So students in the former sub-fields will have many more journal articles the latter sub-fields.

Oh. No. I NOTICED the same exact thing. Ivy league goes first in the queue rest is on the back.


text:
Do I have a better chance for a PhD in a field I have research experience in or one I have had better courses on?
I'm applying for PhD programs in Computer Science, which allow a year of rotation and courses, before the student officially joins a lab for their thesis. I've had research experience in Computational Biology, but being a Math major, I've had a relatively (relative to average CS graduates) large number of courses on (or related to) Theory CS (I took quite a few advanced courses on topics closely related to Theory CS).
I have two questions:
1 - Do admissions committee generally view an applicant in my situation more qualified for doing a PhD in Theory, or in Comp bio?
2 - Assuming I'm considered more qualified for Comp Bio, is it a bad idea to express interest in working in CompBio, and claim I want to work with an advisor in that area, while I actually plan to do my PhD in TCS? I mean, given that once I get in I'll have the freedom to choose my advisor and I'll have enough time and opportunities to even gain research experience in a different area, could there be any negative consequences in expressing interest in CompBio (and even introduce some vague research ideas), and then if admitted, try to work on TCS?
(moral issues with doing this are of course a different story)

Apply for and do the PhD you actually want to do.
The skills gained by having research experience are generally subject transferable, so if you want to do theoretical computer science, explain what skills and knowledge your research experience in computational biology gave you that would be applicable to that field. It could even be something as simple as saying "my experience in researching x topic in computational biology got me interested in computer science as a field of research, which I want to explore further, focusing on theoretical topic y".
Don't try and game the system. Be honest about your interests and the experiences that have led you to them.

Assuming that computational biology and theoretical computer science are housed in the same department, I see no reason that you would not be able to later switch as you saw fit.
When I applied to PhD programs, I expressed interest in matrix theory and abstract algebra. I ended up moving to applied math relatively quickly. I was assigned a temporary advisor when I arrived. She helped me transition administratively to the other discipline. It was a matter of her signing a form confirming I had found a permanent advisor. Note that not all programs will even assign you a temporary advisor.
I have never heard of a program that retrospectively looks back at your application and confirms whether or not you actually studied the topic you had proposed when you applied.
Such a practice as you have described is actually somewhat common I would think. Interests change. There is nothing inherently immoral about changing your research interests. (I would avoid outright lying, however).
As for how qualified you are for either subject, that is impossible for me to say. Demonstrable experience in computational biology is not going to hurt your application. Neither are numerous classes in theoretical CS. Note that, based on the research interests of the faculty, one field may be favored over the other for admissions purposes. If they have one theoretical CS professor and 10 computational biology professors, you are betting against the odds to say you really want to study theoretical CS.

"Demonstrable experience in computational biology". How does one define demonstrable?

@NelsonGon Projects you have worked on, publications, Git Hub repositories, etc.


text:
Is it necessary that your partner (wife/husband) have English proficiency, when you are going to study abroad?
I decided to go study Ph.D. in the United States. Is it necessary that my wife be good at English?
I am expressly interested in legal and statutory requirements of English proficiency for a spouse if I am going to be studying in the United States.

It would certainly be a great opportunity to learn!

Isn't Spanish spoken by a greater number ?

I meant statute necessity.

I don't think this sort of question is on topic here but would be great at expats: https://expatriates.stackexchange.com/help/on-topic The U.S. has no legal official language. Many people live in the U.S. without English proficiency, whether that is a problem or not depends on whether they see it as a problem, what other language(s) they know, and where exactly they live.

@SolarMike, a large number of Spanish speakers, but not a majority. Also, in many places, Chinese, Korean, Russian, etc. But for other than Spanish, mostly in bigger cities.

@SolarMike What would give you that impression? English speakers outnumber Spanish by 180 million.

Are there countries in the world where local language proficiency is required for immigration? Genuinely curious, I've never really looked into it

@AzorAhai For permanent immigration yes certainly; for temporary visas I don't know of any specifically; I just checked Canada out of curiosity and it seems like some types of temporary visas do require language skills.

There are (or were) countries where an immigration visa is dependent on having a useful skill...

@SolarMike https://en.wikipedia.org/wiki/Spanish_language_in_the_United_States

If you are in a large city or at a large university, then it probably isn't necessary. You will probably find a lot of people there, and their spouses, who speak your language, whatever it is.
In a small town, however, it would be a different story, and your spouse might be a bit isolated without some language skills.
There are many large State Universities throughout the country that have students and faculty from all around the world. When I was in grad school in such a place (long ago) I had neighbors from Iran, in fact. Some such large places have organizations for spouses of foreign faculty and students in which people can get together, though everyone tends to speak a different language.
Also, many places, even small ones, have programs in secondary (and other) schools for English as a Second Language (ESL). These are taught by specialists. So, I think that no matter where you are, there would be opportunities to learn even if you didn't find people who speak your own language.

As for the legalities, there is no requirement that a person be able to speak English. However, to become a citizen you need some minimal proficiency: http://pjclaw.net/uscitizenship/english-language-requirements-for-naturalization/. But you don't need proficiency on arrival and, since the process is long, there is an opportunity to learn.
For the requirements to get a visa, see this site: http://www.ustraveldocs.com. But I note that there is no information there about Iran. The best place to get information is to visit a US consulate or similar place where visas are issued and get current requirements.

The question seems to be whether it is legally required, e.g. in order to get a visa.  OP clarifies that they mean "statute necessity".

Disclaimer: I have not done a lot of work with immigration law, especially for education purpose visas.
Presumably you are obtaining an F-1 visa for your program. Your wife will also need to go through a very similar process I believe. She must also enroll in the Student and Exchange Visitor Information System (SEVIS), obtain a separate Form I-20s from your SEVP-approved school, and apply for an F-1 visa. Only you will need to pay the SEVIS fee I believe.
None of these visa applications require direct English proficiency. (Forms may be in English, but she is not required to fill out those forms without assistance).  You and your wife will need to pass visa interviews. This is often done in your home country (or a country you have travel access to). Because the interview is done "locally" at the US embassy or consulate, it can be done in a language you can speak. English is not necessary.
Your specific school could give you more guidance on the details of the process.

F-1 is if she's also a student, F-2 is for dependents. It is, however, a very limited visa - a spouse in F-2 status cannot study full time, or work. It might be better to go for a J-1 visa, since dependents in J-2 status can apply for work authorization.

@Anyon Yes, that is a good point. *-2 is a dependent visa.


text:
Can I get into a top school C.S. Ph.D. program with a Master's from a lower ranking university?
Is it possible, and what are the chances of doing so, to get into a Computer Science Ph.D. program at a top school like e.g. the U of Toronto with a Master's degree (say, with excellent academic record) from a lower-tier school?
My situation is as follows:

I am about to complete my Master's degree in math (GPA will be between 3.7 and 4.0) in a program with a high reputation (acceptance rate 40 out of 170). I have done mainly (functional) analysis and mathematical physics, and some differential geometry and probability theory. No computer science-related stuff. Also, no statistics (so far at least).
However, I am increasingly unhappy with my field, and I would like to go into machine learning. I know how to program and I have won some competitions as a high school student at federal state level (Germany), but I haven't taken any university courses in computer science so far.
This term I'm taking courses in databases, operating systems and machine learning. That will be enough to get admitted into the Applied Computer Science Master's degree at the University of Heidelberg (note that Master programs in Germany are two-years programs). Certainly not itself a bad university, but the computer science program doesn't really have a very high reputation (after all, there's a reason the admission requirements are so low). With virtually no formal education in computer science, I just don't have a lot of options at the moment.
Assuming that I will complete that Master's program with a very good GPA (and also additionally take the one and the other undergrad course like e.g. algorithm design to catch up), what would be my chances to be admitted e.g. into the Computer Science Ph.D. program at the University of Toronto or a similarly good school? At the moment, I would certainly have no chances to be admitted into their Master's program.

I have also considered doing a one-year computer science conversion Master at a better school, but I found the curricula of those programs rather basic and concluded that doing a 'real' Master's at a not-so-good school would be the better option. But maybe that's just my German way of thinking... Here in Germany the name of your schools means relatively little, but my impression is that things are somewhat different in the anglophone world (in particular the U.S. and the UK).

Would it increase my chances if I combine this degree with edX MOOCs from top-tier schools like MIT?

Decide what you want, then APPLY, we cannot say what any particular university wants or accepts on any particular day... Your application may help them achieve a diversity threshhold , who knows.

Are you sure that you are asking the right question? For me, it looks like the main problem is that you want to enter a C.S. PhD-program with an unrelated math degree. (Which I've seen happen, but usually  with a more c.s.-related focus in math courses.)

@mlk he says that he's going to do a Masters in Applied Computer Science first, but at a (perceived) lower-ranking institution.

There are some academic-cultural differences between US (where I live) and Canada, so take my answer with a grain of salt.
Top CS PhD programs in the US are looking primarily for concrete evidence of research potential in PhD applications.  This is especially true in machine learning, which is by far the single most popular research area for PhD appicants.  (At least a third of last year’s PhD applicants at Illinois listed ML or some close variant as their primary research interest.)  I cannot emphasize this enough—competition for PhD programs in ML is incredibly fierce.  ML has become the default area-of-interest for smart people who like CS but don’t really know what they want to do.  High grades and test scores might be enough to get a human being to look at your application, but they will not be enough to get you in; classes ain’t research.
In addition, since you’d be applying with a masters degree, you’ll be compared with other applicants with masters degrees, many of whom will already have ML publications. (Unlike Europe, most PhD programs in North America require only a bachelor’s degree to enroll, and most new PhD students in those programs do not have master’s degrees.)
On the other hand, a strong background in functional analysis, differential geometry, and probability theory is extremely rare among computer scientists, and could be a huge advantage, if you can leverage that expertise into concrete evidence of research potential.
Some specific things to aim for in a master’s program:

When you apply for PhD prorgams, you will need recommendation letters from well-known researchers researchers in your target research area.  Make sure the department where you get your master’s degree has those researchers!  You should be thinking in terms of potential faculty mentors/references, not departments.
In your PhD application, you must be able to talk about your research interests using the idiomatic language of a researcher, not just as an interested student.  Moreover, your recommendation letters must present concrete evidence of your research potential.  Make sure that your masters program gives you an opportunity to do research (or at least indepedent study projects) with those well-known researchers in your target research area.
A purely course-based master’s degree will work against you; classes ain’t research.  Similarly, using MOOCs as evidence of your expertise in ML will work against you, because we only have your word for how well you did, and MOOCs definitely ain’t research.  That doesn’t mean on-campus courses and MOOCs are useless, but you should use them to enable your research, not as end goals in themselves.
Leverage your strengths.  Look for MS programs that will help you develop research expertise that takes advantage of your particular skills.  In particular, look for potential faculty mentors who have, or at least appreciate, a similar mathematics background to your own.
Sadly, the name of your school does matter.  There are too many good applications; people apply all sorts of stupid filters to limit the number of applications they have to read.  (It might matter less coming from Germany, where there’s less variance in quality/reputation.)  Wherever you are offered admission, ask for data about PhD placement before deciding which offer to accept.

Yes, it is possible, but you're asking the wrong question.
A (paid) PhD track is more of a job of a junior researcher, with some studying involved, rather than a study program with a fancier title. You need to convince either a university, or an individual researcher that it's worth their while to employ you - that you have the potential to produce meaningful research and to help them advance their own overall research agenda.
In convincing them, the reputation of the institution you got your Master's at may have some influence - just like your grades, papers you've published, non-academic (e.g. industry) work, the identity of your Master's supervisor, the reputation of your research group/lab, and perhaps your online presence, scientific and otherwise. These all can factor on. Different individual researchers, departments and universities factor them in differently.
What I will say practically that it may be more important for you than for other people to engage a potential advisor personally, perhaps arrange a visit, offer to present a result of yours in a colloquium etc. - to create an impression beyond what can be assumed based on your "pedigree".

This is probably not the same in every country. It wouldn't be true in the US, for example. But doctoral study in EU seems to be quite different than in North America.

@Buffy: In (some/most) of Europe this is even clearer than in the US. In the Netherlands, for example, not only are Ph.D. students considered employees, they are also unionized together with the senior academic staff members; they have a collective labor agreement, pay scales and everything.

@Buffy Maybe not in CS, but this answer is exactly how I would describe the US in the biological sciences. What part of it are you saying is different in CS in the US?

@BryanKrause, in some fields a TA is not automatically part of the deal with doctoral study. In particular, if you have some other funding, then you don't need to have a "job" to study. Fellowships are like that. The sciences may be a bit different as there are labs that need to be staffed and the study is an integral part of the lab work (I think). In math and CS that isn't the case. The humanities also, don't normally have labs, but still have TAs. Just not as linked. OTOH, you probably can't be a TA if you aren't a student.

@Buffy In science, TAs are only a fraction of the support, it's mostly RAs - but the work and research are one and the same. At least at my institution that's pretty normal for PhD students in engineering too, and I sort of assumed CS would be similar to engineering, but it might depend on research area, with more funding in more applied areas. In any case, einpoklum specifically referred to a paid PhD program, which I take to be one with guaranteed funding. Humanities, social science, etc, of course is different.

No, it needn't be the same. The funding for TAs and RAs, might come from department funds rather than project of grant funds. You are paid (can be paid) by the department, not by the project. In other countries, there are paid programs as the writer noted. My note was just to suggest that it isn't always the same. Big world, this.

There is no way to know if you are acceptable at University X unless you actually make application there. Most top universities have students at the graduate level who attended not quite so prestigious schools (otherwise they'd have no students). Apply and make your best case. What are your strengths? What can you bring to the table that makes you a great candidate?
But you don't need to look at it as an either/or situation. While you are in the process of applying you can also start your transition to CS. It might not even need to be a formal program. While MOOCs might give you knowledge, I doubt that they would figure very highly in any decisions.
And of course, some parts of CS are very mathematical, so if you are intending to do something like that, then the transition between fields may be less of an issue.

If I was CS faculty and was tasked with reviewing your application, the question I would be asking first and foremost is "Why does this student think he can be successful in a CS doctoral program when he has next to no computer science experience?" As long as the institution you are getting your master's degree from is accredited and has at least a decent reputation (i.e. I know that the school exists and that it is not just a degree mill), where you are coming from will matter much less than how you plan on being a successful student in our program.

Here in Germany the name of your schools means relatively little, but my impression is that things are somewhat different in the anglophone world (in particular the U.S. and the UK).

This is indeed somewhat the case in the U.S., but only to a certain extent. Harvard is distinctly better than Polytechnic University of Northern Idaho. But is Colorado State better than University of Oklahoma? Is Clemson better than Tulane? Does it even matter?

"At the moment, I would certainly have no chances to be admitted into their [U of Toronto] Master's program."

Taking one or two classes is not likely to vault you to a position where you all of the sudden will be ready to enter U of Toronto's PhD program then.  MOOCs would be given next to no credence in the admissions process. (I work in "industry" in computational statistics and visualization; applicants whose entire "formal" programming experience is in a MOOC never even receive a glance when I get their resumes).
Based only on what you have said, I personally would find it hard to accept a student with your profile to a top-tier PhD in computer science. While doctoral work in CS is certainly more than just "programming," it would worry me that you have essentially zero background in the field generally. Even PhD students in theoretical CS need to understand the basics of computer architecture, object oriented programming, networking, etc. Students wanting to do "big data" and machine learning need to be even more experienced in these topics.
My overall suggestion is that you consider doing a PhD in statistics or a PhD in CS at a lower-tier university. You will have an easier time convincing an admissions committee that your profile is a good fit for their program.

What on earth does computer architecture have to do with machine learning? As far as I can tell, very little. And I know that top-ranked CS programs in the U.S. will admit students who don't any background in the areas of computer science unrelated to their intended research topics. (Although whether you can get into a top-ranked department in machine learning with no CS or statistics courses is a different question.)


text:
Just how important is university prestige when completing PhD?
I'm highly considering attending smaller, lesser known private university to pursue a PhD in cognitive psychology. The university gives full funding, I really mesh the with the professor I'd be working with, and the area is beautiful. The advisor I'd be working with came highly recommended to me by a professor I work with at my current university.
Compared to a lot of the other universities I've visited, the program is much smaller - with about 20 graduate students in total in the whole psychology department. This greatly appeals to me, as I just came from a tier 1 research university with over 60,000 students, and I've been really wanting a more close knit atmosphere.
Ultimately, I think I want to pursue academia, although I'm open to the possibility of industry. My concern is that while the university itself is touted as a "hidden ivy", it's not well renown for its psychology department. The university is not a tier 1 research facility, and the department isn't highly ranked. I'm worried I'm shooting myself in the foot in terms of job prospects later on. How important is the prestige of the program in the grand scheme of things?

The best indication of what the possibilities would be is the track record. You should ask detailed questions about where the past PhD students are now employed.

University prestige doesn't matter at all.  Department prestige definitely matters, but not as much as advisor prestige or your prestige.

Related questions: https://academia.stackexchange.com/q/90/65 https://academia.stackexchange.com/q/66215/65

The key factor is that 'prestige' translates to resources -- be it dollar or brain power or connections.  You are more likely to encounter very competent people, high performing or a talented people at these places.  All of these resources place you at a much higher operating platform or become more efficient, meaning you will achieve more than someone who goes to an institution with less resource or prestige.

I guess that if you want to teach at Princeton (or Oxford) then go to a place just like Princeton (or Oxford). Otherwise, I think that what you do and the work you complete will have a much bigger impact on your future than the prestige of your institution, which may be overrated. There are a number of R1/Ivy graduates in the news that I consider to have the intelligence of rocks.
Having an advisor with lots of ideas, wherever they are, is a big advantage. Being able to work closely with your advisor is a big advantage in doing good work, provided the advisor does good work.
And, your future may be determined as much by economic conditions as anything. You get no guarantees. In fact, even if you go to Princeton, expecting to teach there later, there is no guarantee that any suitable job will be available there (or at a similar place) at the time you need it.
Choose your institution on a more sophisticated set of criteria than it's perceived reputation.
I went to a big place with a lot of faculty and grad students. But the number of people doing anything that I was seriously interested in was very small. Three or four faculty and half a dozen students.

Actually, I should note that many universities (not all) have a policy of not hiring their own graduates. This is to make it more possible to bring in new ideas from the outside, as well as spread their own reputation more widely. Some will make exceptions, but only for the most exceptional candidate. As an aside, I recommended that my own BS and MS students go elsewhere for their next degree, just to be able to bump up against fresh ways of thinking.

I guess that if you want to teach at Princeton...then go to Princeton... — Careful.  At least in my field, many departments actively resist or even forbid hiring their own PhDs as faculty. (With good reason. It's much harder to evaluate your own former students objectively, both for hiring and for tenure, especially when you have to keep working with their advisor.)  If you want to teach at Princeton, you might be better off going to Harvard.

@JeffE, I noted this in my update, but I picked on Princeton specifically, since I don't think they have such a restriction.

I think they do. There are two assistant profs in the CS department at Princeton with PhDs from Princeton, but they both spent several years as faculty elsewhere (Michigan, USC) before they were hired back.

@JeffE, then I'm misremembering (a hazard these days). I softened the opening a bit. Better now?

Yes, much better.

Prestige does matter to a certain degree, especially for schools that are rich in tradition and prestige. (E.g. Harvard is not likely to hire someone with a PhD from North Dakota State). We fool ourselves if we believe that prestige has no impact on the hiring process in academia.
I will even admit, when I receive faculty applications to make reviews and suggestions on, I look at the university the applicant went to and make a judgement on a candidate based on how prestigious the institution they received their PhD from is. I do not use this as my only basis for making a decision on fitness for hiring of course.
However, all this being said, there are broad bands which universities fit into. A program ranked 105th in the nation is likely not going to be able to place their graduates at a program ranked 5th. But if you went to the 35th ranked school and have a good publication record and potential, getting a tenure-track position at the 20th best school is certainly within the realm of possibility.
Overall, someone who went to a smaller school, yet has published widely and influentially in the field, is much more likely to obtain a quality faculty position than someone who went to a top tier school and has no publications.
As for your personal situation, I feel that it is always better to go to a program that balances education and employment opportunities with program "likability" (if there is such a thing). You do not want to end up in a program you hate just because it is at a better known school.

Harvard is not likely to hire someone with a PhD from North Dakota State In my experience, the best departments are actually the ones who are least swayed by the prestige of someone's alma mater in hiring.  And incidentally, a quick glance through the CVs of Harvard's psychology faculty finds graduates of Ohio State, UC Santa Barbara, and the University of Illinois at Chicago.  All excellent schools, but not generally described as "prestigious".  (Though I must admit complete ignorance about the reputations of their psychology departments specifically.)

OSU, UCSB, UIC are all decently well regarded. They are not "elite" programs perhaps, but they are certainly quality programs.

@MarkMeckes Look at the Harvard math (my field) faculty as an example though. CalTech, MIT, U of Chicago, UC San Diego, Carnegie Mellon, University of Cambridge, NYU, ETH Zurich, Cornell, Michigan, Princeton all come up in just a fast linear search of math faculty. These are all highly regarded mathematics programs. Many of them would even be considered "elite." Moreover, these schools are not cherry-picked. The lowest ranked school I could find was CMU (#32 by US News). But this person specialized in logic, for which CMU is #6 in the US.

My impression is that the prestige of the program you go to matters a lot, more than anyone wants to admit.


text:
Review website for research groups
I was wondering if there is a website that allows you to rate research groups/professors that you've worked for. I know about 'http://www.ratemyprofessors.com', but I was thinking about a website specifically for academic reviews, and this example is more or less limited to lectures.
If my research is correct, there's currently no such options, it sounds like an idea to implement something similar. What do you guys think? Would you be interested in using something like this?
The goal of the project would be creating transparency in science, and the build could be similar to glassdoor. There are for sure some concerns about the sample size and anonymity, especially in the case of smaller research groups, but it might still be better than nothing.

I agree with you. Having a website is better than having none. There is more and more support of this idea. Professor Abuja Sharma from Iowa State University developed one: https://ratemygradadvisor.com

@scientist Could you provide a link to the webpage of this professor? I cannot find anyone of that name working at Iowa State.

There are unfortunately numerous issues that I see with this.

Many research groups are small enough that anonymity would be next to impossible.
Similarly, most professors only advise a few students at a time and it would take forever to build up any sort of meaningful amount of reviews on any one professor.
Most research groups are transient. As students graduate, the group will be changing on what is likely a yearly basis. Just because Jim and Jill were great to work with in the Bonsti Lab three years ago does not mean that Jim and Jill will still be there now.
RateMyProfessor is somewhat of a cesspool at times. It can certainly show overall trends (such as 23 reviews that mention that the professor cannot write a clear test or 19 reviews that all mention how messy a professor is), but such trends would be too subtle to notice over just a few students.

One is likely best served by just speaking to current graduate students in the lab of one's interest. Students usually know if there is an overall troublesome situation in a given lab.

The above comments are from a professor’s point of view. I disagree with the concerns.

@scientist Provide an answer of your own. My answer reflects my opinions as a general academic and has little to do with my profession (which is, in fact, not professorial).


text:
International Medical student who wants to do a math phd
I am a medical student at the number one ranked university in the MENA region (AUB). I have been interested in the mathematics of bio-imaging and a lot of my research deals with this field. I am keenly interested in applying for a mathematics PhD at a top research school in the US after I complete my MD. I am aware I may be an nontraditional applicant, especially that my undergrad preparation was in chemistry. I took all the calculus series courses, along with ODEs, real analysis, linear algebra, and abstract algebra. I scored above 90% in all of the classes, and our institution is known to have considerable grade deflation. Many of these courses I took while in medical school as well, so I had to juggle between a busy medical school curriculum and the additional coursework.
If I hopefully manage to do well on the math subject GRE, would this put me in a good position as an applicant to a PhD program (top 20)? My medical degree will obviously have no value in terms of assessing my readiness, but perhaps it speaks to my work ethic and ability to handle great volumes of work. I am also a US citizen if that makes any difference.

Much of this answer will depend on several variables that are currently not disclosed:

Where is your undergraduate degree from?

Have you taken classes in topology, analytic geometry, complex analysis, numerical analysis, computer programming, etc?

The rigor of the math classes you took during medical school.

A demonstrable capability to succeed in a U.S. top 20 math PhD program while having what would often constitute a minor in math at many universities in the U.S.

Why are you going to medical school, only to switch fields in a sense?

These are my thoughts on each of these points (as someone who has evaluated candidates for admission into graduate programs in mathematics):

If your degree is from a well regarded university in the U.S. or Europe, this will bode better in your favor. If your undergrad degree is from somewhere in the MENA region, your case will be harder. Right or wrong, many Top 20 programs in the U.S. would be hesitant to place great weight or significance on someone earning 90% in Calc II at a university in Morocco.  (I am perhaps overstating the situation here for emphasis).
I will be honest--when I get an application on my desk from the MENA region, especially if they do not have an undergrad degree in math, I tend to not place it on the top of my review stack. Applicants of this sort seem to rarely offer any reason for their attempt at admission beyond stating that they are "interested in math" and want to come to America to study it. (The MENA region is not the only area of the world that does this, mind you).

If you are interested in medical imaging, you will need to have a background in analytic geometry. My current area of research is in...yep...medical imaging from a mathematical standpoint. It is a field that requires abilities in graph theory, analytic geometry, statistics, computer programming (emphasis on computer programming). There would be absolutely no way that I would accept a student who could not program pretty well in an object oriented language (C++, Java, C#). Knowing some Python is usually not enough.

While I have not personally been to medical school, I have several associates who have. I must admit that I am rather dubious that one could take math courses while also succeeding in medical school. Maybe it is possible. I just know that there would have been no way that I could have pursued a second curriculum while I was working on a PhD.

One of my former institutions required (for admission) all of the classes you have listed, plus at least two other classes you have not. Exceptions were very rare. A minor in math was never enough for direct admission to the PhD program. A few exceptions were admitted provisionally (unfunded) to the master's program.

If I saw an applicant with a medical degree applying for a PhD program in mathematics, I would probably question the applicant's motivations (not how motivated they are, but WHY they are applying). A medical degree and a PhD in math are not usually seen in combination with one another (unlike an MBA/JD combo or something). I would question if the applicant had somehow been barred from practicing medicine or something. If you can explain your motivations clearly in an application, this would be wise.

I will say a few closing words on this subject.
Thinking math is "interesting" is likely never going to get you past the gates of a top 20 math program in the U.S. Nor will it be enough to sustain you through the 4 or 5 years it would take to obtain a PhD.
I have no idea what you finances are like, but it may be a wiser move to find actual employment in the medical imaging field with your medical degree itself. Obtaining a medical degree and then a PhD may complicate your ability to be placed in a residency as a physician.
Note that all of this is not to say that you cannot end up at a top 20 math program in the U.S. If you get a very high GRE score, maybe you can climb the wall and actually break in as a rather nontraditional student. Never say never I guess.
Best of luck.

Thank you very much for your thorough and detailed reply. I appreciate  you taking the time to help a stranger out. I have actually been torn between a deep rooted desire to study mathematics and medicine since highschool. My motivations extend beyond cursory interest, and the collaboration between the study of mathematical structure and systems biology is becoming more and more apparent. The university is the American Univsersity of Beirut, if that makes any difference.

@2eurokebab I feel you could have at least an okay chance of being accepted into a math graduate program. AUB is a school I would respect. It will never hurt to try I guess. Good luck.


text:
Thinking about taking another gap year for the study of physics but afraid how it would be perceived on my PhD application
Intended field of Research: Physics (Particle Physics or Quantum Physics) Country: India I became an undergrad in 2018 and my degree was supposed to be completed within 2021, but due to the pandemic and I having had backlogs, I took 5 academic years to complete it. Now, I have spent 5 years in this system, I now realise that I haven't learnt a thing and the whole bachelor's was a waste and did nothing but to provide me with a certificate which is frankly useless and the only use I see of it is that I can now pursue masters. I am not gonna lie, I had a lot of time to study, especially during the pandemic, but thanks to my anxiety issues, me being lazy and somewhat stupid, I didn't study. Now, I am aiming to get into one of the prestigious Indian Institutes of technology, but the competition is pretty hard and I might get into some lower tier IIT rather than a higher tier one, thus I am taking another drop year, I want to read Feynman's lectures, I want to read of lot of books which a physicist should read and I should have read but didn't. I want to be good at what I will do in the future. Now, the biggest problem I am facing is to whether to drop again and risk my application looking bad.
I intend to apply for a PhD abroad and certainly not in India, I have heard some terrible things about doing a PhD in India and I certainly don't want to make that mistake, plus, I don't intend to live or work in India because the state of R&D in here is utterly dire and I know I won't be able to get funds to do anything important and Indian bureaucracy is a Kafkaesque nightmare and I want to be as far away from it as possible.
My main goal is to relocate to a country with better infrastructure than India.
So, how would European/English PhD committees see two gap years (technically 3) in an application like mine? Would this be a deal breaker considering I want to pursue PhD in a European University which is in Top 100 QS World University Rankings?
PS: I have a good CGPA (7.1, good by Indian Standards) but my Physics marks are mediocre in Undergrad. I will be doing my Masters from some good IIT and most probably would have a good CGPA and paper there.

See https://academia.stackexchange.com/q/176908/75368, to see how doctoral admissions works in various places.

Does this answer your question? How does the admissions process work for Ph.D. programs in Country X?

I am sorry, they don't answer my question.

"I haven't learnt a thing and the whole bachelor's was a waste" - what makes you think you would do better in that gap year? You seem to be falling in a "study for the sake of study" trap, which is frankly more problematic than whatever the applications committees will see. "I want to be good at what I will do in the future" - you are past the core part of your education now. This "future" is already here. You will never have the perfect domain knowledge, perfect infrastructure, or no bureaucracy. What makes a good researcher is the ability to work with what you have.

Also, do examine this canonical question more closely - BSc->PhD track is (at least mostly) an American thing, European universities would require you to have your MSc completed first. But overall I'm more concerned with your overall perception of top-100 universities somehow being all glamorous and great and Indian R&D being terrible. At least some of the Indian universities have fairly strong research teams, and it is labs and people that matter, not how the university ranks as a whole. More opportunities, yes, but what good is it if you never come to actually use them?

Gap years in and off themselves are not necessarily concerning. Many students take them, especially between a BSc and a PhD. It would be critical that you explain what you did during those gaps years. Did you work in a relevant field? Did you do any self study on relevant topics? It unfortunately sounds like you pretty much did nothing during a gap year. Taking one more gap year to build some meaningful experience or learning would be better than applying right now and having no such experience. I would look much more favorably on someone who took two years off, but had something to show for it, than someone who only took one year off and did nothing in that time.
I would avoid saying you did nothing because you are "lazy and stupid". There is no way that a potential advisor hears something like that and wants to bring you on as a student.
It would be concerning to me if I was on an admissions committee or was a potential advisor and received an application that pretty much amounted to "I'm not good enough to get into IIT programs and I am desperate to get out of India. Please admit me to your program." The harsh reality is this: If you cannot get into some decent programs in India, you are not likely to gain much traction in any decent programs in Europe. Your case essentially sounds like one of begging for pity because you do not like where you live.


text:
Pursuing a second masters in a more established school
Consider this situation,
I get accepted for a second masters degree at the University of Toronto, and just before that I graduate with a masters degree in a much less established university.
Both degrees are in the same field, Computer Science.
Further, UoT knows that I am completing my masters degree.
My plan would be: to use this opportunity to get into the PhD program at the University of Toronto, because this is what I applied for in the first place.
Would you pursue this second masters?
Thanks

Can you get into the PhD program without it?

Does Toronto know that you already have a masters?  In my experience many institutions will not accept a student to pursue a degree that they already have.

Yes it does know I have masters. @DaveClarke I apply for PhD and I get masters.

If I interpret this properly, they may have accepted you into the masters program as a kind of conditional entry into the PhD program, in order to screen you to see whether you are good enough. Maybe you should ask them.

Yes, exactly, that's what I gathered.

Contact the department and ask them directly "How many students who applied to the PhD program and were only accepted into the masters program end up graduating with a PhD?" If this number is very low, I'd advise against this. Some professors will discriminate against masters students when looking for students to do research with, and if this is the culture at UoT, you should know about it going in. The worst outcome is you end up paying for a second masters and leave with two masters degrees in computer science, which will look unusual in job interviews. I know of at least one interviewer at a company who said he automatically views two masters degrees in the same subject (or even a highly related subject) as a big red flag.
It might be better to enter a PhD program at a different university or get a job. You can always apply to PhD programs next year. I know of several students with less than stellar academic performance who enter good PhD programs with work experience. As someone who has read a fair amount of personal statements before, those who have been in industry for a few years tend to write better ones. They tend to know what they want and are not going into academia just because it is the "next step" without thinking about it.
Computer science has the advantage that often you don't need a university to do your own research. Start doing research in your spare time. If you find a question you are really interested in and have made some progress, contact professors who work in that area at various PhD programs. You have a much better shot of getting into a good PhD program if a professor has notified the admissions committee that they want to work with you.

If you can't get into the PhD program without it, I would ask them if it is a requirement or an opportunity to prove one's ability. I think that it is important to get a guarantee, or at least a good chance to get into the PhD program.
It has certain advantages to work there before:

Better contacts
Already acclimated
You know the software and equipment

I would pursue the second master but I think it would make more sense to apply directly to PhD programs.

Please note that not all Masters programs are created equally, especially if the degrees come from different countries. The University of Toronto would typically ask you to have your degree evaluated for equivalence.
Degrees in Pakistan for example have historically been exaggerated. A Pakistani bachelor's degree would be the equivalent of a high school leaving exam and it's Masters degrees would be the equivalent of bachelor's degrees. This is because people persuing academic studies in Pakistan had to spend a considerable time studying the Koran and other Islamic books before they could move on to the actual course they were interested in.
Perhaps the UoT does not recognise your Masters degree as equivalent of its own?


text:
Having caused a lab accident, how to mend my relationships with fellow students?
I accidentally caused a fire in my department laboratory. The fire was not big, and luckily no one was injured. However, it triggered the fire alarm and sprinkler system, which led to some of the common equipment being damaged.
After the incident, the department has enforced tighter control on lab safety. For example, all students need to submit a work flow before doing new experiments and complete numerous forms to buy new chemicals. It results in a lot of unnecessary administrative work and greatly slows down our research progress. Many research students are unhappy about that, and since I caused the accident, they have begun to ostracize me. Even some 'closer' students seem becoming less friendly to me.
I know it is totally my fault, but sadly, I already caused the accident and can do nothing to change the fact. Now the problem is, what should I do to mend my relationships with my colleagues?
EDIT: As some of the comments mentioned that it is not clear whether the additional rules actually should be enforced no matter there was the accident or not. Honestly, I don't know, but it is the extra work that annoy other students, and it is totally because of me. I guess my department should have complied to the laws before, otherwise they will be in trouble...

This is a reasonable question about interpersonal relationships (although I doubt there's much you can do beyond apologizing and demonstrating over time that the "stupid reasons" that caused the fire won't occur again).  I don't think it's on topic here, though: this sort of situation is no more likely to occur in academia than elsewhere, there are no special academic customs or traditions related to it, and the fact that it's taking place in academia plays no real role.

Every laboratory of a country should comply with a number of safety rules which are required by law. It is not clear from your question if the control that has been set after the accident is just the enforcement of safety rules which should be followed anyway, but were neglected before the event, or if it is stricter control that goes beyond the safety rules of your country.

I agree with @MassimoOrtolano. You could be very well describing the requirements of risk assessments and permits required here. Also, a sprinkler in a lab sounds like a not so good idea, but I have never actively looked at what they have.

I fully agree with @AnonymousMathematician and voted to close. You would likely get better answers at Workplace.SE.com.

@AnonymousMathematician I understand this sort of situation can happen outside academia, but the question is about research student's relationship. Just wonder if there is any thing that can be done under this situation in academia.

We shouldn't close this as off-topic. It is very specific to academia since it deals with students and not employers. Why in the world does anybody think it could be asked on Workplace.SE? It would be closed there as off-topic in no time.

@tohecz replace "students" with "co-workers" and I think the question is equally applicable to either forum. I don't think that it's a good habit to get obsessive about migrating questions just because they are equally on topic somewhere else. For example, does this affect student labs too, where you have to do set experiments within an allocated time?

It results in a lot of unnecessary administrative work and greatly slows down our research progress.

If you do something, intentional or unintentional, that causes more work for others, you are going to be resented. In my opinion, the best way to minimize the resentment is if you are seen as being proactive in taking on your share of the new work. I would suggest you step up and take on a significant portion of any new group work related to the fire. If labs need to be move/rearranged to comply with fire safety standards, it would be best if you came in on the weekends/nights to help people. If the department needs a fire safety officer or first aiders, it would be in your best interest to volunteer. If a new committee has been formed to deal with fire safety compliance, ask to be on it.

Beyond that: Respect all safety practices, let it be seen that you're doing so, and give folks time to conclude that the accident really was an accident, that you've learned from it, and that you're less likely than any of them to be the cause of the next disaster. (And there will eventually be a next disaster.) It's going to take time to live this down, but it will become less significant over time as long as you don't do anything to remind folks of it.


text:
Poster author added me as coauthor after abstract was submitted. Can I include it on CV?
Poster author added me as coauthor after its abstract has been submitted to a conference. As a result, on the conference website I'm not listed as an coauthor, but my name is on the actual poster.
Assuming that it's not possible to update poster authorship info on the conference website, should I still list this poster on my CV, or would it just create confusion or misunderstanding?

I do not list any posters or talks on my CV if I was not the first author.

A poster of which you're not the first author is such a minor thing I wouldn't worry about it (even if it is listed on the conference website).  I don't have a huge publication list but still only include posters I presented (aand only at major conferences).  They don't have anything like the CV impact of a peer-reviewed paper.
Either:

You were accidentally omitted and should be included. In this case the author should contact the conference organisers (but it's probably too late).
Or your contribution was rather minor -- perhaps it only became apparent that your work made it onto the poster at all at the last minute.  In this case while you're named as an author it's closer to an acknowledgement in practice.

Listing it as a publication, if the title can be searched for but you're not named, doesn't seem like a good idea.  Realistically no one is ever going to look.  But if you just happen to come up against someone who's interested in something very specific about the poster that you don't normally do, it isn't going to help you.

I don't support posters any longer for my personal academic career, but there are eminent examples of major breakthroughs which were presented as posters, for instance Gruntzig seminal invention of angioplasty (in particular, look at Gruentzig's Poster Exhibit at 1976 AHA), so we cannot discard their value altogether.
Regarding your question, I think you can add the poster details on your CV.
The best thing is however to also write an email to the publisher of the proceedings (putting in cc the corresponding author) to have the author list amended (this can be done in the online version). Finally, try to also obtain the final version of the poster (eg in pdf), and possibly a photo taken of the actual poster when and where it was hanged.