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Re-reviewing a previously rejected article but some authors have changed from the previous submission. Should I mention that to the editor?
I recently accepted to review an article for a journal. I actually reviewed the very same article for another journal from where the submission was rejected. This is a rather common occurrence however, as I was looking at my notes from the previous review to see if the authors have addressed the previous issues, I noticed that the new submission has actually different authors. For example:

Initial Submission: Author1, Author2, Author3, Author4, Author5
New Submission: Author1, Author2, Author5, Author6, Author7

I will clearly mention in the review that I have reviewed the article before (actually the submission is in a different journal of the same publisher) but is the change of authors something that I should mention in my review?

Can you explain why you would feel the need to mention a change in authorship? What relevance is there to the manuscript in its current format? The new journal presumably won't care who the former authors were, only the current authors.

Well, if it is literally "the very same article", i.e. without changes, I would see it as indicative of something fishy going on. I would definitely mention it to the editor.

Was there a specific contribution attributed to Author3 and Author4 in the initial submission, or could you infer one? Is that contribution still present in the new submission? Can you identify a contribution of Author6 and Author7 in the new submission that was not present in the initial submission?

Is the order of authors relevant in your field?

@silvado What does that have to do with the question. Regardless of the convention for ordering authors, some authors have been added and others have been removed.

@DavidRicherby For Author5 I guess it might be a relevant change of the author list in that case.

@silvado The order of authors is not only field specific but also country specific. I have had "tough" collaborations were a supervisor of a student expected to be second author in a publication despite limited contribution to the presented work. I believe that this is the same case in this article that I am currently reviewing.

I don't see a reason not to mention it. @kmm

It's not particularly unusual for authors to be added during a revision of a paper, but for them to be removed is quite unusual and often linked with something improper going on.
Since this submission is a different publication than the original version that you saw, the editors do not have this history in front of them, and I think that it is indeed a good idea to flag this as a concern to the editors.
Moreover, if the article has not been significantly revised but the set of authors has changed, then that's a major red flag that the authors are doing something improper. If this is the case, then the editors absolutely must know, and should probably investigate wrongdoing.

It is of course possible that this is legitimate, but the editor should ask for an explanation. I could see this happening if each of those authors was only responsible for 1-2 pieces of analysis and the previous review called he quality of those analyses into question and they are no longer included. So I think your last point about "not significantly revised" is spot on.

When we accept to review a paper we usually agree to keep it confidential. Shouldn't that confidentiality for the previous submission in principle be kept towards the other journal? Especially as long a no clear proofs of misbehavior come up.

@silvado Communication between reviewer and editor is generally confidential as well, so there is no concern about public exposure. As for the prior communications: in the case of possible unethical submission, a disclosure of the prior interaction is entirely reasonable and appropriate.

@silvado "Clear proof" isn't the issue at hand. The suggestion is that the referee share information with the editor; it is the editor who decides what to do with that information.

@DavidRicherby I'm just saying that in principle the reviewer shouldn't share information obtained from the first submission with a third party (editor of the second journal).

@jakebeal Do you mean that if someone shares information with me confidentially, it's ok to give that to someone else, again confidentially, without informing the first person, as long as I don't disclose it in public?

Note that I'm not suggesting that this information shouldn't be disclosed to the second journal. Just one should weigh cautiously the potentially unethical disclosure of confidential peer review information against the "whistle-blowing" for potentially unethical author behavior.

@silvado Different types of professional confidentiality come with different responsibilities and constraints. For example, a psychiatrist has to preserve patient confidentiality but also has a duty to report if they believe their patient to be a danger to themselves or others. Scientific peer review does not have a formal regulated system of this sort, but I believe a similar balancing of interests applies. A reviewer who believes an author is dishonest has a duty to the community to ask for investigation, balanced by a duty to the author to keep that investigation confidential.

Thank you all for the feedback. After carefully comparing the two submissions, they are effectively 99% identical and, worst of all, have not really addressed the comments from any of the reviewers of the previous submission. Besides the straightforward rejection recommendation, I did mention all of the above in the notes to the editor and I am quite interested to see how they will handle it.

One time removal of authors does happen if the paper has to have material cut: Consider a largely experimental journal with a strict page limit.  Either the initial submission had too much theory, or more detail was required on the experiment, meaning a lack of space for theory.  So the theorist(s) no longer contributed to the final paper (but will hopefully publush another paper of their own). I've seen something in a reviewing system about this; whether it was an option, an instruction, or an example, I can't remember.

I have been in a situation where a co-author's organization told us to remove them from a paper for inscrutable legal/security reasons.  The author gave us permission to remove them.  So this not necessarily unethical.  But it's a good idea to ask.  I would also check if there are changes in the acknowledgements.  I think the author would be obliged to thank them for their contributions even if they can't do it by name.
Our co-author's organization eventually let them be re-added to the paper.  But I can see how that might look sketchy to someone who didn't have the context.

This point about the acknowledgements is critical: I too have had a potential co-author need to be transferred to acknowledgements---but the trace of credit should still be quite clear.

Another possibility for a legitimate change is if somebody's name changed, but then its often just the first name (gender change) or last name (wedding) and not both parts - at least in western cultures. And yes I've seen both happen during publication preparation.

Seen the same thing. Drafts of the paper with different author lists are around, so I asked the omitted author how to cite the paper and learned this story.
But unlikely to be the case here:
https://academia.stackexchange.com/questions/90836/re-reviewing-a-previously-rejected-article-but-some-authors-have-changed-from-th#comment231598_90837

This seems like plagiarism: the authors of the new submission (namely, Author1, Author2, Author5, Author6 & Author7) are passing-off work from the initial submission as their own, yet that work belongs, in part, to others (namely, Author3 &  Author4).
Personally, I would write to the editor and explain this. I would expect the editor to immediately reject the article and take further action. I don't think there is any need for you to review the paper at this stage.

It could be other types of misconduct as well, like sale of authorships

@jakebeal, how does sale of authorship differ from plagiarism? And how does sale of authorship apply in this case?

Isn't it possible that the paper was edited such that the contributions of Authors 3 and 4 are no longer included (say, because they were included in  a different paper submitted elsewhere?

@user2768: good point, taking credit for a paper you paid someone else to write is a special case of plagiarism.  The work being copied was presumably never published anywhere else, though, which is usually part of what's implied by "plagiarism", isn't it?  So that would be the major difference, along with differences in motivation.

@user2768 It might be that only Author 1, 2, and 5 were ever involved in the paper, and they are giving false attribution to Author 3 and 4 the first time and 6 and 7 the second time.  That could be either a gift authorship for political reasons (e.g., to a department superior) or a sale of authorship. It is different than plagiarism as typically defined, however, in that it is addition of a non-existent attribution, rather than omission of an attribution that should be made.

@jakebeal I believe that your comment describes exactly what might be the case here but, also, unfortunately what is a rather common occurrence.

@jakebeal, maybe give your explanation as an answer? Or expand your original answer to include the reasoning.


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Multiple submission of same work for different audiences
I have research work that has been conducted and is at the stage where it is worth disseminating to the research community. It is somewhat cross-discipline in nature, and involves some technical contributions and is also of interest to a set of end users who are completely non-technical.
The problem is that, having attempted previous submissions, it has become painfully clear that neither community seems to appreciate quite the same issues as the other. Thus, a single paper aimed at addressing all the issues from both perspectives ends up being perhaps lacklustre, and apparently unappealing from both sides. This is partly due to constraints on paper length, which prevent adequate detail for all aspects of the paper, and also the fact that fundamentally large portions of the paper end up being targeted towards an audience that is not present for the given journal.
Therefore, I was wondering if I could adopt the approach whereby a high-level paper is written targeting the end users of the development and submitted to an appropriate journal, and a second paper which covers the technical aspects in detail without trying to cover the aspects necessary for the end-user audience. Considering that both papers will present the same results, is this an acceptable approach to publication?

I tried to create the tag "multiple-publication" - apparently it is not such a big issue but perhaps somebody would like to create this tag and add it to this question?

I don't believe that the tag is necessary. Using multidisciplinary and publications would adequately describe the situation as it is, and adding a third tag for a scenario where both are present seems redundant.

I think there are venues that deal with usability. I'm assuming that you have done some research that has other researchers (with a different background) as the audience. I understand you have two different types of results, depending on the perspective and the (base) state of the art that you consider. In that case there should be no problem in splitting them into two papers. Otherwise, I don't understand your question.

This is actually something my group also deals with extensively. A lot of the work we do is focused on improving existing computational methods to improve their efficiency or extend their range. A lot of the time, the actual work done is of very little interest to the end-user audience, but quite significant from a computer science perspective. So a lot of our recent work has been divided in exactly the manner you propose: we present the basics of the method and some end-user applications in papers geared toward the application community, and specialized papers for the methodology that are directed toward the CS community.
The main thing to remember is that the publications should stand independently of one another as much as possible. Some overlap will of course be inevitable here, but you should strive to make the "stories" they tell as distinct as possible.

I've had much the same experience.  This is very common in multidisciplinary work.  It's important to make sure that the publications reference one another and clearly distinguish their relationships, so that there is no possibility of being perceived as duplicate publishing.

I think it is a good decision to target your manuscript for a single audience if your experience has shown that presenting it in a broader fashion misses the mark. It is not unusual to write two different papers that advance the same prior work and present new results.
However, this shouldn't simply be a matter of repackaging the results of the first paper, it necessarily entails analysis and additional work to produce a substantially new result.
Another option that can work well is to divide your article into separate, directly related articles (Part I and Part II) published in the same journal. In my experience this ends up being a lot of work, but it relaxes the length constraints and allows you to section and adjust the presentation of the material in a unique way.

On the other hand, the answer to this question as it is stated is, unequivically, no.

Considering that both papers will present the same results, is this an
  acceptable approach to publication?

Quality journals nearly always stipulate that they will not accept work that has previously been published elsewhere--a practice known as redundant or duplicate publication. Unfortunately, it is not always possible for reviewers and editors to be aware of multiple simultaneous submissions and there seem to be a number examples of people abusing the system with few consequences.
What constitutes original work may vary to some degree in different fields, but the point of any paper is to communicate something noteworthy that isn't otherwise available.
"Results" need not be defined narrowly as new measurement data, but every article should be an honest attempt to contribute something original to the field.
For instance, good review papers are very much original contributions in the sense that they synthesize results and highlight connections that might otherwise go unnoticed. But if you set out with the premise to publish the same results in more than one article you are creating more noise for all of us trying to keep track of the literature. You may not always be called on it, but the practice is something that good reviewers and editors notice.

I feel that the second part of this answer is too black-and-white. No paper - certainly no good paper - is only about results; it's always about the story as well as the results, and in some cases even more about the story. I have myself published multiple papers with the same formal results, but different explanations, different language, and different motivations; and I strongly believe that, provided this is done well, it is not only acceptable but even the right thing to do.

@MarkPeletier my response to your comment was too long, please see the last two paragraphs of my answer. It may be that our disagreement is largely semantic; if you argue that the two articles are different that is another matter, but if you tell me they are the same work with nothing new then in my view it is very black-and-white situation.

I think we agree - of course, if the two papers are `the same work with nothing new' then there is little to be said.

But I do think your link to this page is a red herring - in that case there was obvious intent to mislead, while we're talking now about the situation where everything is in the open.

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How to finish Master's Thesis when my adviser is too busy to help me thoroughly edit what I have written?
I have finished my B.S. and I am now finishing my M.S. thesis (already finished M.S. classes). My original thesis topic was not getting me anywhere and I came to my adviser asking him to allow me to switch to a new topic that I have already started working on. The professor allowed such a change and I believe my new work is much better and more interesting. Unfortunately, the new thesis topic is not my adviser's area of expertise.
Moreover, I have been late in turning in my thesis for several semesters since I've also been working full time much of the time after I finished my B.S.. This makes it feel like my university does not really care about my success anymore and I am not even being pressured to finish writing my thesis as I would have been if I was a full-time student.
I will be finishing writing my thesis on this new topic, but much of the work I have done have not been checked by anyone with a Ph.D. This worries me. Should I just crowd-source some comments for editing my thesis from friends and try to just get it turned in and accepted so I can present? Or should I seek out more professors who are more familiar with this new topic and try to have them read it (it would take at least several hours to do this and, keep in mind, I am not a full-time or even part-time student right now)?
I think my work is good and I will pursue trying to get it published in a journal once my actual M.S. is done, so I am not too uncomfortable with the things I've written.

Have you expressed your concerns to your adviser, and if so, what has he/she said? If not, why not?

@waiwai933, I don't even feel comfortable discussing how busy my adviser is with my adviser. Moreover, I am living 2 hours away from my university right now.

It sounds like you have two major concerns about getting quality feedback from your advisor: (1) he's busy, and (2) he's not as familiar with your new topic. I'll address these separately.
Getting high-quality feedback from someone very busy
To get the best feedback possible from your advisor, make sure that whatever you send him to review is as polished as possible. If he's pointing out typos and areas where the writing has issues, he's not going to have as much time to evaluate the content, which is where his feedback is most valuable.
It will also help if you identify and tell him about the areas where you think you most need extra high-quality feedback: "Could you tell me what you think of the formulation in Section 3, I'm not so sure about that part."
Getting high-quality feedback from someone not an expert in the topic
Even though your advisor is not an expert in your new topic, he's an expert in something and he knows what good work looks like. He knows when an argument seems weak and "hand-wavy" and when the evidence on offer doesn't support the claim.  So he's still likely to have good advice even if he isn't as familiar with your topic as you would like.
In fact, for PhD students at least, it is generally assumed that the student knows more than the advisor about the thesis topic by the time the student is about midway through the program.
On crowdsourcing thesis feedback
Having said all that, it's still useful to get comments from others in addition to your advisor.
Ask your friends to read your thesis to (1) find typos and obvious mistakes, and (2) note areas where they think something is unclear, so you can improve the writing. This will help you make sure the version you send your advisor to review is as polished as possible, so you'll get better feedback from him.
If you know some professors who are expert in your topic, you can send them a copy, but follow the advice for getting feedback from someone very busy: Make sure what you send them is very polished, and identify where you want their help the most. If you don't know any professors who are expert in your topic, then after your advisor gives you his feedback, ask him: "Do you think we should also send this to an expert in the topic for review? If so, do you know anybody we could send it to?"

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Citing/Attaching unpublished papers in a Research Statement/Profile for a faculty job
I am a young academic and don't yet have any first author publications (several 2nd authors, though) but have several either submitted or very near being submitted. I am in a quantitative/scientific field.
My question is about whether it's OK to describe (and cite) finished research projects that are not yet published in a research statement for a faculty job. On a similar question, if the application requests copies of papers, can you attach "in process" papers?
Thanks for any opinion/experiences.

Yes!
Your task is to make the strongest possible case for your expertise as a researcher.  Your case would likely be stronger with a few first-author publications, but having compelling first-author work in the queue is certainly better than not having compelling first-author work in the queue.
In fact, even if you have first-author publications, your research statement must describe your ongoing research agenda, in specific, credible, and compelling detail.  Faculty hiring committees are just as interested in your future research plans as they are in your past research accomplishments.  Preprints and submitted papers that support that agenda are definitely appropriate.

Thank you (I don't yet have sufficient reputation to upvote). As a follow up, as a point of etiquette, should I tell the co-authors that I am sending the preprint as part of a job application?

@user9486: Yes, definitely discuss this with your coauthors.


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Lengths of review process of mathematical journals
Do you have any file containing the information of peer-review process lengths of mathematical journals?If yes, It will be very helpful for me.
Thanks for your helps.

The AMS maintains a list of the backlogs of research journals, which should give you some indication.
The most recent one (I think) can be found here: http://www.ams.org/notices/201310/rnoti-p1390.pdf


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What are predictors of the success of PhD students?
Every year we organize a competitive international call for PhD students (in the area of biology). What measurable criteria should we use to predict their academic success and award them research fellowships?
I realize that part of the question is ill-defined because it is not clear how to define “success” for a PhD student. But since I imagine that many of us have this problem and have potentially thought of a solution, I would love to read your thoughts on this question.

As a graduate student, I would say that important qualities include persistence, creativity, and of course hard work. It goes without saying that one should be able to learn well.

So you are looking for answers which will first define success and then show which indicators best predict that success for PhD students?

Ideally yes. But an answer addressing only one of those would be interesting.

Maybe this might help provide some insight? It's only on the course level but it would be a place to start. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3002135/

The major quantifiable predictor of success in research is... success in research. People who have done research successfully in the past are more likely than not to continue to do so.
For students that have not done research in the past, the best predictor I have seen for success (whatever that may be) is expressed in a quote from The Unwritten Rules of PhD Research, by Marian Petre & Gordon Rugg:

A willingness to learn for themselves and good judgement about when to stop and ask for feedback.*

It's not exactly quantifiable, but you can get a sense for it in an interview.
(Of course, this quality can be learned, so a lack of it doesn't necessarily predict an inability to succeed at research.)
* I took this quote completely out of context; the authors there are actually discussing the role of the PhD advisor, and they mention this quality in reference to a student "who can be pretty much left to get on with it, with supervisory meetings being something that both parties enjoy, and where each party learns from the other."

Short answer: You should not be looking at what people do or how they are, but how what they do looks like.
This is, how are they qualifications, specially considering consistency between them, it's not about the average, but the average and a small standard deviation. The greater the deviation, the less predictable they will be.
On a side note: you will probably reject geniuses.
Long answer:
"Success" is now defined as "publishing", it's pretty clear how to define it since people that have to define quality and metrics are focusing on this.
This may be wrong, some people say it's wrong to use P-values to test your hypotheses, some people say it's wrong to use h-indexes to measure the quality of researchers, but it's certainly becoming more and more common. These values provide a warm feeling of objectiveness and it's very hard to refuse to that. IMHO, they are here to stay, and without any doubt, they are here.
Having clarified that, I have a personal hypothesis (not verified at all, sorry) that people that get good grades are better at publishing. The reason is that we can consider that the corrections of an exam and the reviews of a paper are similar.
In my experience, in both cases is not about how much you know or how much you can do, but on the contrary it is about:

Conformity. Using the same language, terminology and not producing something shocking or hard to understand that will cause failing the exam or the paper being rejected.
Writing skills. Trying to predict (consciously or not) how the person reading your paper/exam is going to interpret it, avoid misinterpretations, show self-confidence, clear ideas, clear structure, etc.
Concision. This is more than a writing skill. Time is limited in exams, pages are usually limited in papers (and the less pages, the more papers, that's also good, in principle). But it's even more than that, because most of the time it's not about how much you know or how much you have done, but avoiding mistakes. An exam that replies perfectly to half of the questions (and only that) will look better than one that replies perfectly to 90% of them but then makes really stupid mistakes in the other 10%. A paper with a small contribution may get accepted (depending on how small it truly is), but a paper with an important contribution and then an important mistake will get rejected (even if the mistake is only in the mind of the reviewer because the terminology used does not conform to what is usual and this makes reviewers very confused).

So it's really about being compliant with the state of the art and moving step by step further, with small steps, baby steps, avoiding mistakes. How can you know whether someone can do this? Looking at their grades, and specially to the deviation of their grades from the average, it's not just about high grades, but consistent grades. It's not about how much they know, but about how often do they mess up, because if they do often, chances are they will do it at least once per paper, getting all rejected.
This is the case for me, from time to time I'd do something really "brilliant" in an exam, the teacher would not understand it and I would get a qualification of 0 in that exercise. I have never cared about qualifications, but learning, now publishing is just like any other qualification. Success is just like any other qualification.


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Correspondence articles, do you put them in the CV?
Some journals have correspondence articles that vary in size and format. More importantly, they can be peer-reviewed or not (even in the same journal, like Nature Genetics for instance).
Do you write these publications in the CV? If so, do you put them in a separate category or together with your regular academic publications?

I think the question as it stands is too broad (as you say, there are different kinds of Correspondence, and it would be easier to answer if you were a bit more detailed). To provide a vague answer, though, I would separate pieces that were peer reviewed from those that were not. I think anything peer reviewed should count as an academic publication and as always, you should never judge a CV without reading the papers; journal name is never a guarantee of good science, so anyone seriously reading your CV can then make their own judgements as to how to weigh the Correspondence you've written.

Could you please explain "correspondence articles" more? What are they exactly?

@Parsa, you can have a look at the guidelines of Nature or Nature genetics. Nature says "These items are 'letters to the Editor': short comments on topical issues of public and political interest, anecdotal material, or readers' reactions to informal material published in Nature (for example, Editorials, News, News Features, Books & Arts reviews and Comment pieces)."

The following assumes that you do not have to follow strict guidelines for your CV (in which case you would most probably have consulted them already).
You put stuff on a CV for a reason, usually to showcase your achievements or experience. When deciding what to put on a CV, this should be your main criterion, i.e., do you think that whoever reads your CV will be positively impressed reading this – in contrast to being annoyed by having to read about every tiny thing you ever published? Whether the article in question is sufficiently noteworthy, is something that only you and people who are familiar with your work (such as a supervisor) can decide.
It might help to ask yourself the following questions:

Are you at a stage where you list every publication, talk and poster on your CV or are you only listing “selected publications“?
Is the correspondence relevant and can you expect the reader to know or see this? Did you, e.g., find a serious flaw in a publication that was considered seminal until your correspondence? Has your correspondence been cited?
Did your correspondce require a noteworthy effort and can you expect the reader to know or see this?
Are you the main contributor to the correspondence?

Considering where to put this correspondence, I would try to avoid creating a new category for one item only, i.e., I would put it in some fitting category or choose the categories such that it fits in one of them. Either way, I would ensure that the correspondence cannot be mistaken for a regular publication. If your correspondence does not have a title like ”Reply to …“, which makes this obvious, you can, e.g., append “(correspondence)” to the entry.
Disclaimer: The above is based on thought only. I have no experience in putting correspondce on a CV.


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When does the co-authorship line end for a PI's data
As I understand it, in the engineering field, the person who has research money and/or a project that leads to the collection of data, is put on research papers that directly use that data.  I guess the most common of this is for PHD students whose advisors funding or project is the reason they have data.
I am curious about when this ends in regards to collaboration.  If one person gets a project and funding and collaborates with a different lab/department/professor/researcher and through this, gives a portion of the funding to that person or place, what is the convention for authorship?  Does the PI of the project go on all papers that use the data, or only papers they directly do with their own staff/students?

possible duplicate of Advisor's/University's rights in the PhD/MSc alumni's research projects and publications

Weird. I would expect direct use of someone's data to deserve a citation, not coauthorship.

sorry if the question is not that clear, but i am not talking about after publication of data.  I am talking about during the data collection, and the publications that directly use that data.  When there are more than one publication, such as, publication of methods for data collection and algorithms used for that data.  It is not a matter of how long to wait, but the collarboration limits

The German research foundation (DFG) has some guidelines on authorship for research publications (including an English translation towards the end) which put specific criteria for being named as an author. Among others, it says that those "who have made significant contributions to the conception of studies or experiments" should be listed as authors.
In my understanding, getting funding for a project requires describing the conception of the data collection in quite some detail, so anybody who contributed to that part of the proposal should be included as an author of the resulting publication. Importantly, the criterium is not having brought in the money, but having contributed (significantly) to the conception of the study.
The only exception to that rule would be if the paper under discussion does not "publish" the data, but "uses" it in some other way and can include a citation to the original publication of the data.

Could you be more specific as to where in that document those are listed? Because in your phrasing they seem to disagree with the Vancouver protocol, which has similar phrasing, but includes an "and", which means that the bit you picked out would not there be sufficient.

@TobiasKildetoft This is in Recommendation 12: Scientific Journals (page 83). To locate it quickly from the electronic document, search for e.g. 'significant contributions'.

@TobiasKildetoft The Vancouver protocol lists "conception and design", which might be meant as synonyms, the DFG just "conception" ("of studies or experiments"). There doesn't seem to be a significant difference in meaning here. Interestingly, the DFG mentions "generation of the data", which seems to lack in the Vancouver protocol.

The Vancouver protocol also lists other things. And all of those must be met, not just one of them.

If one person gets a project and funding and collaborates with a different lab/department/professor/researcher and through this, gives a portion of the funding to that person or place, what is the convention for authorship?

If you collaborate with someone, they usually get co-authorship on papers resulting from the collaboration. Not because money changed hands, but because they were involved in the work that the paper describes.
If two PIs on a funded proposal work independently on research described in the proposal, such that they are not collaborators, then they won't be author on one another's papers. Again, the reason they won't merit co-authorship is because they did not collaborate on the work.
For example, suppose I write a proposal together with a colleague to explore some problem domain both from a theoretical standpoint (his area of expertise) and through practical experimentation (mine). He develops the conception of the theoretical part, while I develop the experimental part. The proposal is funded. My colleague proceeds to develop a very nice theoretical framework, while I independently go ahead and do some experimental work. I didn't participate in his work and he didn't participate in mine. We are not going to be co-authors on one another's papers.
It's irrelevant whether money changed hands. It's also not relevant whether we are in the same lab/department/university or different ones.

But if those two researchers in your example publish one paper including both theoretical and experimental parts; they are assumed to be co-authors of a single paper.

Also, if each of the authors forms even a single idea of another paper and participates in some discussions of the paper, he should be assumed as a co-author of the paper; and if they have no discussions on another paper, they have no co-authorship relations. (I mean, one of the papers may be two authors and another with single writer as no collaborations and discussions about that specific paper is made between authors). I think participation in a paper is important in co-authorship; not anything else.

@Parsa yes, participation in the research described in a paper is grounds for co-authorship. Sharing funds, as the OP asks about, is not.

This also applies to the person's previous thesis advisor; even he has advised on the authors past thesis, if they have no direct participation in his current paper, he should not be assumed as a co-author. Just participation in that specific and current paper, nothing else. Am I right?

@Parsa this question is about whether sharing funding with another group is (by convention) grounds for co-authorship on their papers. My answer is that it is not. This is not the place to discuss standards for co-authorship in general.

Do you know any book or reference for ethics of paper publishing in which such standards are discussed?

@Parsa there are a lot of questions on authorship on this site, I suggest those as a reference.

Thanks. I am excited to take a deep look at those questions and answers.


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Writing a recommendation for highschool student
I am a full time researcher at a research institute, we are part of a university, but the institute does not have students, just researchers. I mostly have assistant researchers and interns that are undergrad. I am thinking of bringing on a final year highschool student who is really promising and has been winning some awards.
They are interested in me writing a recommendation letter (to US schools, but we are outside US). Is this advisable?
My main concerns are the appropriateness of a research based letter for undergrad admissions, as well as not being a Professor or Senior faculty as mentioned in questions specific for graduate school.  However when I think about myself, I am pretty sure I had high school teachers write my recommendations, non of which had a PHD nor, obviously, were professors.

This question seems to essentially be about undergraduate admissions, which is out of scope on this site (per the [help/on-topic]).

@ff524 but writing recommendation letters (for undergraduate admissions or otherwise) is a normal part of academic life.  Seems like a good question to me.

@Matthew the question isn't about how to write the letter, though; it's about how a letter would be perceived by undergraduate admissions committees. To me, it seems analogous to questions about how [something academic] is perceived by employers (also out of scope here).

@ff524 I see, OP asks us to speculate whether such a letter would work in the applicant's favor.  I get your point.  Still seems like a worthwhile question.

You're giving the student an extraordinary experience compared to her fellow applicants, so it's natural for her to ask you for a letter explaining that experience and your opinions of her work.  And I think it's very reasonable to provide one.

I would say you're expected to write letters for high school students who work for you.  Students usually do research to get into college, and in many cases, your letter is the whole reason the student chooses to join your lab.
When I applied to college the application asked for letters from a science and a humanities teacher, but also allowed us to submit an optional letter (which would presumably be yours).


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First time being asked to review a conference paper
I am a first year PhD student, and my adviser from undergrad asked me if I would like to review a paper for a conference. I was quite taken aback, as I have no publications, and feel somewhat unqualified. Granted, the topic of the paper is on something I have studied with this adviser in the past.

Is this something I can put on my CV? Given the anonymity of the reviewing process, will there even be a record of me having done this?
Isn't it strange for an unpublished student to review a paper?
What could I possibly gain from this? I suppose reading a paper critically is good experience, but I am already anxious about not having any publications yet, and it feels strange to be a reviewer without having any publications myself. I suppose this would put me in my old adviser's good graces, as I am interested in working with him again.

Yes. I don't know for conference paper, but with journal, they usually end the year with a thank you to all reviewers. This "thank you" is available online and is a proof you indeed reviewed. But I doubt that anyone will ever verify this.
I think it might be unusual, but it is a good thing. First, it means your undergraduate advisor think that you can do it (abilities but also he/she thinks you know this subject). Second, lots of people are talking about reviewer overload. Using qualified PhD student can reduce that overload.
Experience, increased self-confidence and yes, recognition from you ex-advisor...

I suggest you consult this great article to help you start:
Seals, D. R., & Tanaka, H. (2000). Manuscript peer review: A helpful checklist for students and novice referees. Adv Physiol Educ, 22, 52-58.
In my experience, doing my first review, I was a bit stressed but mostly excited. I wanted so much to do everything well. Thus, the authors got an honest and very complete review. If you try to be as thorough as you would like your own work to be revise, all should go well. Good luck.

Just to clarify: It is perfectly fine to list "I have acted as a referee for this conference" on a CV, one would not mention "I have acted as a referee for this paper".

In regards to 2, I don't think this is even unusual, as long the advisor reads and discusses the student's response. If not it, it's highly unethical.

@CliffAB I agree with the possibility of doing a "supervised" first review, but highly unethical seems a bit strong...

@Emilie: I don't think this is too strong. The journal contacts the researcher because they are an established expert in the field, and they are asking them to make a decision regarding a very large amount on behalf of the author. If the author's work is then judged by someone who is unqualified (which I would say most graduate students are not yet qualified, certainly not at the level of the advisor), this is extremely unfair to the author.

I would consider it unethical for the adviser to pass along an unread review as if it were his own. But in some conferences, that review would go to the program committee clearly marked as the work of the subreviewer, and in that case I see no ethical problem.


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Detailed navigator for UK Computer Science Master's?
I'm trying to choose the best university in the UK for a computer science master's course, leaning in a more theoretical direction. But sites like prospects.ac.uk are too broad, I don't want to filter 350 results which consist of basically the same buzzwordy text about carreer opportunities manually.
My current approach is checking out universities I've heard of in the field, trying to find the actual course listing and guessing from that the actual direction teaching might take (currently Glasgow is my first choice because it's the only one to list a "functional programming" course, which is at least a first step into the direction I want); but even the course descriptions in the listing are quite fuzzy…
The problem of looking at publications from areas I would like to work in and choosing a university from that (hoping that a master's there might set me on a PhD route) is that, at least in undergrad studies, there's little connection between the researcher's work and teaching. But I haven't nailed down an exact direction to go in either, so directly finding research groups I'm interested in and working backwards from there would be hard, too, since there would probably be more than 350 of those as well.
So, is there a specialised computer science master's course ranking website with a column for “philosophical direction” or some kind of “business vs academic career” weighting?

Not an answer, but if you're interested in functional programming and language theory, Edinburgh has some really cool stuff. Philip Wadler, one of the pioneers of Haskell's Monads, is a professor there, along with others.

Yeah I just noticed that on the second round through, I think I prematurely kicked it out because of the strong emphasis on applied "informatics", totally missing the part about an optional theoretical CS focus

There's a whole institute for Foundations of Computer Science there.

So, is there a specialised computer science master's course ranking
  website with a column for “philosophical direction” or some kind of
  “business vs academic career” weighting?

No. While it would be nice if there was a system that you could enter your definition of "best" and it would spit out the school for you, it just doesn't exist. While it probably is not a fair system, if you want the "best" according to your grandmother's definition, you probably want to limit yourself to the Russell group. You could also look at the 2008 RAE for what HEFCE thinks is the "best". You can also use league tables. The best approach would be to actually define what you mean by "best". Factors you may want to include are location, course size, research component, course work, faculty, and reputation.


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How much flexibility does one have in selecting their PhD coursework in the first year?
For instance, if someone is working as a Phd in computer-science, but on a neuroscience related topic, she might need to take some neuroscience related courses. And some CS courses might not be any help at all for the area she is interested in. Do universities put a lower/upper limit on the number of courses one can take?
Also, does this differ from university to university?

Every department is different.

It varies dramatically, by university, field, and country.
It can be any of:

There is a fixed curriculum that everyone takes
There are a few required courses and the student can choose the rest
The student has a committee which recommends courses to take
The student can take any courses but has exams to pass
No coursework at all (I understand this is common in Europe, where Ph.D. students come in with a Masters)

Usually there are upper and lower limits on the number of courses to take.  In the US, one usually has to take at least 3 or 4 courses to be considered a "full time student" and be eligible for funding.  (But one can often count research as one or more of these courses.)  And it is often not allowed to exceed 5 or 6 courses without special permission.

This is going to be school- and program-dependent.  In my Computer Engineering program, we had to take two 1-credit overview courses (not intensive) our first semester, and then my advisor told me the courses he expected me to take during that semeseter.  I ended up taking three full classes, which was probably excessive.  Of course, then I took three the next semester, too... After the first semester, I chose courses that fit in with my research, and also courses that were required for the degree.
Here are some pros and cons to taking multiple courses and courses outside your field:
Plusses:

If you take more courses when you haven't yet begun research, you will have more time for research when you're more advanced (if you fulfill any requirements early).

Taking courses tangentially related to your field or outside your field leads to a greater body of knowledge in which to find interesting problems.  This can lead to better research.

You'll meet more professors, and this can lead to other research opportunities.

Minuses:

You can easily become too busy to get research done, and research is what will get you the PhD.  One of my fellow student's advisor tells his students, "No A plusses!" and what he really means is, you can study too hard on a course with a detriment to the more important research.  During grad school, I only had one semester where I didn't take any courses (and it was nice, I'll admit).

You could lose focus entirely.  Remember, getting a PhD is all about focusing on a particular problem until you are the expert on that problem.  Spread yourself too thin, and you'll have a harder time reining in that one problem.  This really is a minor minus, though, especially during your first year.
The bottom line is that you need to tailor your schedule to account for a number of factors, including your own sanity and your ability to do research.  How your schedule is determined will largely be up to you, but each school will have its own individual requirements and policies.

You will likely piss people off at your major department if you take more courses outside than at the department itself. This will be viewed as lack of respect to them -- what kind of know-it-all are you??? One course is probably OK, especially if you "negotiated" that upfront by stating your multidisciplinary interests, but I wouldn't risk any more; not at least until you are done with the comprehensive exams, or whatever they may be called in your program. Passing them should be your top priority. You can also excuse yourself by declaring a Ph.D. minor in an additional field, or working towards an MA/MSc in that field. Again, that's something that needs to be discussed with your Director of Graduate Studies and adviser (which you may not have in the  first year).
In my program, I took about 15-18 courses in my main department (statistics), another 6 in a graduate certificate program, and a scattered number of 1-2 courses in four or so other departments (economics, biostatistics, sociology, taking their [whatever]metrics courses), and graduated with some 70+ credit hours instead of required 45 or 48. I don't think they liked it very much... but then my tuition coverage came from another research center on campus that appreciated my breadth. Do as I say, not as I do, though, as I now work in industry after having failed the tenure track.


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What level of knowledge and expertise is usually expected from someone just entering a PhD in computer science?
If someone has bad grades and limited programming experience, can they afford to rely on their first year of coursework to come up to speed with the field? Or is it a better idea to take some time off before starting your PhD and improve your skills?

I would hope that someone with poor grades and limited programming experience would not consider a PhD in CS as a valid career option.

@DaveClarke Ahem.  Excuse me?

@JeffE: Except for you. ... Perhaps I should delete my comment.

I'm not sure if anyone should consider a PhD in CS as a "career". If anything, it's a stepping stone. A stepping stone to what is the big question. Also, as far as knowledge and expertise, do you have an undergraduate degree in computer science, computer engineering, or a similar, closely-related field?

if you have received the position already, go for it, you will learn the required stuff along the path. the learning curve will be hard for you, but you will have to put extra effort. If there is no offered position in sight, identify and improve your deficiencies in regard with the research area that you want to pursue in your phd. if you have no idea about what research area you want to work on, and you only like the acronym in front of your name, reconsider your decision

This is phrased as a question about first-year coursework, but it's actually a question about admissions.  Specifically, a department won't offer admission to someone they feel has inadequate preparation, so this situation should not arise (assuming the admissions process works well).
From this perspective, the reformulated question is: if you have bad grades and limited programming experience, is admission to a CS PhD program still possible, or do you need to take some time off to improve your skills?
At this level of detail, there's no way to say for sure.  If your application shows nothing but bad grades and lack of programming experience, then admission is presumably out of the question.  On the other hand, why would you even want to enter a PhD program without some other background that indicates it's a good idea?  In which case the admissions decision comes down to what that background is and whether it outweighs the grades and programming experience.  It would take something impressive, but it's possible in principle.

I came into my PhD in CS (JHU) with a solid background in mathematics (12+ graduate courses, 8 undergraduate courses) but little programming experience (I had data structures and theory of computation). I worked a few hours a day just on catching up. It was difficult my first year. If you feel confident about your ability to learn and are able to work extra hard (zero other responsibilities) then I would just begin.

Current CS PhD student here, I can at least speak to the content of coursework.  It does depends a lot on what sort of programming experience you have, and what field you are planning to go into - e.g., if all you've done is some web dev and you want to work on compilers, you're going to have a lot of catching up to do.  But if you wanted to do HCI and you can pick up new syntax relatively fast, you'd probably be fine.
Personally, while I had both decent grades and a fair amount of programming experience in undergrad, I was primarily a physics major and hadn't taken any courses on topics that everyone already seemed to know about, like parallel computing or crypto or even networking - starting out with grad courses on those topics was one of the hardest things for me, not learning a new language.  Classes move a lot faster and assume a lot more background knowledge at the graduate level vs. undergrad.  For example, in my programming language course, we spent two days on an introduction to OCaml, where the undergrad level course spent about two weeks.  It's certainly possible - and schools do admit people with limited CS experience but demonstrate promise in other ways! - but it will mean you have to work a little harder to catch up.  As an example, in my "advanced database manangement systems" course last semester, I was in a project group with two other CS PhD students, one of whom knew only MATLAB (he was going into theory), and the other had a some experience (an intro class or two) with Java.  However, they were both either planning to or taking undergrad-level programming courses.  So that is one option, although of course it'd be more work on top of your classes.  I would say the most important factor in deciding to take time off to "get up to speed" would be whether or not you feel you know enough about your desired field.  If it's just "wow [x] sounds so cool, I wanna work on that!", you might want to take time to get your feet wet and see if you really do like it before committing to a Ph.D. program.  But if you are sure enough, apply away, and be confident in knowing that an admission offer means they think you're ready to go!


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How long do PhD students typically take to come up with their research proposal?
Especially if you are someone who is entering a PhD with very broad interests and little depth of knowledge in your field.

I know students who arrived to graduate school with a research proposal in mind (and drafted during the first semester), and I've known students who wrote their proposal six months before graduation.

@ChrisGregg - ok, but aren't there deadlines set by the university for submission of project-proposal? Also, if someone writes their proposal six months before graduation, does that mean they have no idea what exactly they were working on throughout their PhD?

The rules depend on the university.  As for the student who wrote his proposal six months before graduation; no, he worked on a number of related projects and finally landed on way to tie them all together near the end.

Every department is different.  Moreover, every student is different.

"with very broad interests and little depth of knowledge in your field." - or in other words, almost every single entering student.

If you are talking about the writing of a formal proposal document, the rules vary from department to department. If you are talking about the idea for a project, then that needs to be developed very early on—the tentative idea should already be in place by the time work starts.
In my department, for instance, students had roughly one year from the completion of the qualifying examination to submit the research proposal. This was a fairly substantial document (25-30 pages). Other schools I considered required the submission as late as the third or fourth year (in what was nominally a five- to six-year program); in that case, the research proposal was almost a first draft of the thesis, as it was typically anywhere from 50 to 100 pages in length!
In my current department, students receive fellowships to work on projects with their advisors. In such cases, the advisor typically plans the basic outline of the project, and the start of the work plan. Later years are left for the student to devise.

For PhD in the United Kingdom:
It is not uncommon for students submit a PhD research proposal as part of their application for the PhD program. They can also find a supervisor to work on the research proposal together before submitting it as part of their application.
I have applied for a PhD in another field before and was able to write a proposal in 2 weeks that was good enough to get an interview for the program. This was with the help of a supervisor who gave me the research area, open problems he is interested in, relevant literature and he read several of my drafts.

In the department where I got my degree at, the proposal was expected in the third year, had to represent about 30% of dissertation work, and qualified as a Master's defense should the student drop out of the program and yet being able to walk away with something in hand. In the department where I worked, the proposal was expected half a year before the defense (i.e., in the fall of the fifth year), had to constitute about 80% of the work, and basically was a rehearsal for the job market talk (the winter of the fifth year). So yes, rules and traditions vary from department to department and from discipline to discipline. Ask your Director of Graduate studies (or chair if the department does not have a designated officer for this role) as to what the expectations are.


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Will not having a publication affect my PhD chances even though I have research experience?
By the time I apply for a PhD, I will have almost a year of experience as a Research Assistant, but I doubt I will have a paper published till then. The project is still in the data analysis stage, and it will most probably be in the review stage when I apply. Other than this job, I have no other research experience/papers/projects that are much relevant. Though I have 1.5 years of corporate experience in IT.
I think the above might be a common cause for concern, especially for people looking to switch fields, and thus hope the question is qualified enough for a general audience.
As for my particular case, I am looking for PhD programs at the intersection of Neuroscience and Computer Science (e.g. Cog Sci, Computational Neuroscience, Neural Engineering etc). I have a bachelors in Computer Science, but my grades are bad. My GRE score is quite good however, and I'm from a well-known college in my country.

Are you in a US-based system (applying with a bachelor's) or in a European system (applying with a master's)?

but my grades are bad — What you really need are glowing recommendation letters.

I think you are thinking about the problem in a wrong way. A PhD is more about working for your supervisor than studying in a program. If you know what you want to do, search for research groups doing that, speak with the professors there and see if any of them finds you useful and can pay you. Then there will be lots of bureaucracy, applications, lessons, courses, exams and whatnot. But the main point is in the research group, the supervisor and the funding, IMHO.

@Trylks - Thanks. I agree with your view, but I think this approach works best for applying to European Phd programs, where they hire on a per-project basis. So for people who already know the problem they want to work on, this is the best way. As for me, I have a very broad interest - I would like to explore the field first by taking a few courses and working on some small projects, before I decide on a narrow problem i want to work on. So how do I look for such programs that are open to applicants like me that are near newbies in the field?

@aeismail - I did my undergrad in India, and have an integrated dual degree - B.E. Computer science and M.Sc. Bio Sciences

@warmzombie I study my PhD in Europe, so I may be biased and wrong, but narrowing the topic is the only way I can think of making a decision based on "something": the matching of research groups/Universities with that topic (the narrower the better). It's easier to find out how to get "something" when that "something" is specific. Then, when applying, a few publications will definitively not hurt, but the safest option is to apply asap and then keep improving your CV and recommendation letters while applying iteratively (that way you minimize the work to do before your application is accepted)

This is a difficult question to answer and I know little about the intersection of CS and neuroscience. I do know a little bit about the intersection of CS and social sciences (i.e. HCI/information sciences) so I will write about that. In addition, I am the student representative on the admissions committee of our department so I have some limited experience with that process as well.
You do not need a publication to apply for PhD in the US. For other countries, it might be different and I do not have that information. Potentially, you will be more competitive if you have a publication. But remember, that all publications are not created equal. If you have a first author paper (or otherwise depending upon the publication standards in your field) in a top ranked journal/conference in your field, then you are competitive (assuming that other parts of your application pass muster).
If that publication is in a lesser known journal/conference, you still have displayed some knowledge about how to conduct and publish research - which in the end is better than nothing.
However, in my experience, I have seen that detailed letters of recommendation from authors known to members of the admissions committee are usually given way more weight than any published research.
Also, take my words with a pinch of salt. Everything varies from field to field and from year to year.

Thanks, this helps. I am working under someone who has a very good publication record, and I think his letter of recommendation would help a lot, going by what you say.

I am a PhD student of neuroinformatics in UK and my background is computer science. I think I know a bit about the intersection of neuroscience and CS.
Theoretical/computational neuroscience is a growing field and as far as I am aware people with physics/CS background are very much needed. Experimentalists have a whole wealth of data but they usually don't have skills or time to analyse the data, create models, run simulations and obtain predictions.
You don't need publications to be accepted to a PhD programme. There are actually some PhD students who didn't publish a paper during their programme at all... Having good grades and recommendation letters helps but I would risk to say that primarily you need to show a genuine interest in the field, show that you want to find answers to certain questions etc. You already have an experience as a Research Assistant and definitely it is your strength. Focus on what skills you already have and not what you are lacking. If, for example, you are a brilliant programmer in a couple of languages and handle huge databases well, try to sell that. There must be some labs where your skills are on high demand.
Another thing is what university/lab you would like to aim at. If you want to work for top researchers in the field, it might get very competitive and not having good grades and publications works against you. But of course there is a number of less known labs that work on interesting projects and have various collaborators around the world.
Finally, as already mentioned in comments - get in touch with the professors, find out about their research, read their papers, raise some questions. And remember that some labs might be interested in working with you but cannot offer you any funding. In that case it still might work OK as there is various ways to obtain individual grants.


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How should one choose a supervisor if they haven't yet narrowed down their research focus?
From what I know, every Phd student needs to choose a supervisor in the first year. For someone who is entering a  Phd with a broad interest in a field, this might be difficult since they don't immediately know what they want to work on. How do they go about choosing a supervisor in that case?

dont forget that you always have the chance to change supervisor.

But that can't be easy right? Most people I know seem to have had the same supervisor throughout their PhD. Please correct me if I'm wrong.

My advice will be similar to aeisimail's, and though I have not actually done exactly what I am suggesting, the main points are still based on personal experience.
(Also note that I come from the European setting (PhD in France currently) so the levels of education when you actually start looking for an adviser might differ, but I'll try to do my best to be general.)
In my opinion, there's three almost equally important parts to choosing what to do for PhD:

the subject (narrow field of focus, project you're taking on)
Even if you are not sure what exactly you want to do, if you don't see yourself getting at least a little bit excited about the subject, you will not be able to do it and enjoy it for the whole PhD duration. It also helps if you see the adviser being fascinated by what he does.

the adviser -- on both personal and professional level
Of course, you should read something about his previous works. Read some of his publications, something about ongoing projects. Ask around for information from other students. But also, if you have a chance, try and talk to the potential adviser, in person. Maybe some people can get a feel for an adviser from e-mail or other indirect communication, but for me, if I can hold an easy conversation with someone for 5-10 minutes, I'll probably be okay working with them.

the environment -- both for working and for living
If you can, try and get a feel for the research group and the lab you would potentially belong to. Depending on the type of person you are, you will prefer different environments. But, a friendly atmosphere is beneficial to everybody. Also, take a look at where you'll have to live (if you're moving for you PhD): a very extrovert person might suffer after moving to a small, quiet town. A big bustling town might overwhelm a shy and introvert person. Make sure you can be comfortable outside your PhD/job, because as much as you can't do a PhD if you don't love what you do, you won't be able to do it well if you don't like what your life is outside of that.

It might seem right now that you can survive with a good topic and adviser, in a bad environment, or some other way around, but think about it: those three things will be with you through the whole PhD. You can't do a PhD properly if you don't love what you do, who you do it with and where you are. All three of them are very important.

And some more specific advice that I collected over the years, which is probably not applicable in all the situations but is worth taking under consideration:

young advisers at the start of their career are more likely to pay more attention to their students. If you want to work with your adviser, it will probably be harder with somebody who's already made a name for themselves: you're more likely to end up just working under them.
the longer the people are in academia, the more they do administration instead of research. Know how to take advantage of what you have. If you end up with an adviser over his head in administration, keep research questions rare and to the point, when you need them. But know that these kind of people will be able to resolve some administrative problems for you that others might not be able to.
no matter what type of adviser you get, in the end it is your own PhD topic. The adviser does not hold the absolute truth, and does not have all the answers. He's good for directing you and helping you focus, sometimes discussing problems, but towards the end of your PhD, you are the one that will become the foremost expert on the topic. Prepare for that, so you don't end up disappointed the first time you see your adviser guessing and struggling around your problem just like you.
find what fascinated you about your own (potential) topic. Don't get all starry-eyed about what the output should be when looking for at a subject. If the output is all neat and useful and pretty, think about weather it has, for example, too much maths for you to be enjoying working on it. It's not just about what you are capable of doing, it's about what you enjoy doing.

Sorry for the short novel, I hope you find something that helps you.

"young advisers at the start of their career are more likely to pay more attention to their students" how did you arrive at that conclusion? (I've also met the opposite rumour: young professors who still need to "fight" for their position [standing in the faculty etc] need students (i.e. their results) they can use, whereas older professors who are settled at the top of their carreer can afford to support the professional development the student: putting the two trains of thought together it probably boils down to: see what the potential supervisor's group leading style and character are.

@cbeleites That's not my conclusion: that's advice from my Masters adviser, based on his experience, I'm just repeating. He says old, established professors will more likely be knee-deep in administration, have less time, and after a lot of successful PhD students behind them, will not care as much for just one students' success. On the other hand, if you are among the first few students of a professor, it is very much in his interest to not have his first (or one out of 4) PhD students fail miserably. Also, apparently, less administration and more time for research for starting professors.

@penelope - Thanks a ton for your answer, it answers a lot of my worries.

@warmzombie glad I could help

Most research groups have seminars or weekly meetings. If you're not sure about a particular supervisor, but have a set of interests, try attending research group meetings for faculty in those areas. Faculty are quite used to this and will usually welcome the attendance (but do check with them first)

As it happens, your case was similar to mine—I didn't have a clue about exactly what I wanted to do, other than being interested in simulations rather than experiment. And, unlike JeffE's advice, in my field (chemical engineering), we don't get the option of working with multiple advisors for extended periods of time, because of the way project funding works.
What makes things easier for us? All of the faculty give presentations to the first-year graduate students, and all of the first-year students were required to meet with a number of potential advisors before ranking our preferences. This makes it easier, because we had to be active in seeking out advisors. Talking with graduate students in the group was also very helpful, because it allowed me to learn more about the advisors' styles, as well as the people that are in the groups. (Some of the groups were very cordial, others were not nearly so civil in their interactions—made a big difference in making my decision.)

The ideal PhD supervisor has/provides:

A good track record of successful PhD students
Expert Knowledge and High Reputation
Sufficient Time for your PhD supervision
Opportunities for collaborations
A permanent and stable position
Sufficient, Secure, and Flexible Funding
Good office space
A position at a reputable university
Additional Mentorship Skills

More in my blog: https://www.scss.tcd.ie/joeran.beel/blog/2018/03/20/how-to-find-a-good-phd-supervisor-for-recommender-systems-and-machine-learning-research/

Pick someone at random.  (Use your research interests and experience, and the available faculty's research interests and experience, to bias your probability distribution.)  Work with them for a semester.  If you both like the work that you're doing together, and they're willing to take you on as a student, you're done.  Otherwise, repeat.
No, I'm not joking.

That advice doesn't work in some disciplines.


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How is a Masters different from the first two years of a PhD in the same field?
I'm interested in Neuroscience research but haven't quite made up my mind about what sub-field I want to specialize in. I think taking courses from various sub-fields will help me take a decision. Should I go for a Masters first or a PhD directly? If I go for a PhD, will I have enough time at the beginning of my PhD to explore different areas and then choose a supervisor, say after around 2 years into the program?

possibly, but there people gave quite generalized answers, whereas I think warmzombie is looking for a more specialized answer in Neuroscience

I agree with @EnergyNumbers. The merit of that question is exactly the same as this one.

There are two different types of Masters - taught masters and research masters.
In England, a research masters allows you to work, on rotation, around 3 labs in the year, and you can pick and choose from different sub-fields. This is hugely beneficial because it exposes you to different sub-fields, but more importantly because it exposes you to different work dynamics and environments, allow you to cope better in your PhD; furthermore, you'll make more contacts (which is all that matters in research - reputation and recommendations) and learn from different people. It'll give you the confidence to know, during your PhD, whether you are right or wrong.
The downside is that it takes you one more year and there is no guarantee you'll get a PhD after, and there is also the extra cost - most funding bodies do not fund a one year masters. However, if you apply for a 4-year Masters with PhD, funding options are more generous.
I can only speak for England, unsure about other countries, but the same principles apply. (my own opinion is that MRes is good if you can afford it)

The question on the other page asks about Mathematics, and this is on life sciences?
Anyways, I've answered it and if the question is a duplicate, not my problem.

Correct me if I am wrong, but I always imagine different fields having different course structures, and all I tried to do is answer it in the life sciences perspective, rather than say, computer science. If you don't like the answer, just vote it down.

My answer is pretty much specific to life sciences, if it turns out that it isn't and other fields share the same structure (the lab rotations) then I've learnt something new today. (I would appreciate it if you can tell me other fields that have lab rotations - because I honestly wouldn't have a clue)

In UK, would PhD students have lab rotation opportunity?

No, in the UK, you stick with one lab. There might be collaborations between labs, but there is no rotations.


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An outline slide in a lecture?
When giving research presentations, I don't use outline slides since I am normally telling a story and believe that it is a poor use of time (hopefully I'm not instigating a debate, I just wanted to see if my logic extends to lectures)
However, I'm tempted to start including them in lectures so that students know what to expect and have an idea of the concepts being presented. I'm also thinking about the style where you periodically recall the outline to help keep the big picture.
When doing chalkboard lectures, if the answer is "yes" to the above, I would assume the same holds there. Probably a good use of time at the beginning, right?

From a student's perspective, I've never liked outline slides/time from the really good lecturers, but I feel like they help when the lecturer isn't quite as good. Great lectures are stories and rarely feel like they need them, but outlines are good at keeping things organized in my mind when the lecture isn't quite as coherent.

When giving a talk, no matter how good a storyteller you are, some significant percentage of your audience will be distracted at any given time. Outline slides are extremely valuable for helping those people catch up and rejoin your presentation.
What you don't have to do, however, is have a dry list outline. Whenever possible, I like to use a diagram instead, which unites the whole thing graphically, and indicate which aspects of the diagram we are currently dealing with. Nicely, this works quite well in chalk talks too.

For some reason, I haven't been considering the graphical approach (though I've seen it many times). Definitely more work (for the slide use case), but seems like it would be worth it.

@user5872 Absolutely: a graphical version is more work and completely work the work.  In some cases, when if was clean and simple enough, I've even had the graphical outline on every slide.

This presentation has my favorite non-list outline slide ever. (See page 3)


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Database location for a paper to be indexed by google scholar
In some fields like architecture and design, repositories are setup for collecting the conference proceedings in one location.  Unfortunately these repositories are not always parsed well by google scholar.  Recently, the largest database in architecture began working with web of science conference proceedings database.  It seems that even with this, google scholar has not found these papers.  Are there examples of papers being indexed from the conference proceedings, or should we be looking for alternative repository methods.

Google provide guidelines on how to be included, e.g., https://scholar.google.com/intl/en/scholar/inclusion.html

Google Scholar just crawls the web. As Web of Science requires a login, it is not indexed by Google Scholar (source): "Nor do we include websites that require you to sign up for an account". Repositories are included, if they provide data in the way Google Scholar describes on the help page.


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Computer science framework software
Is there some standard software for creating framework diagrams for computer science such as this or this.
I know powerpoint can do some things like this, and I have been using illustrator.  However, I was wondering if there was something like the automatic python class diagram generators but for overall logic.  This is all in the context of making the diagram for a journal publication.

If you're using LaTeX (or some other flavor of TeX), try TikZ.

I'm voting to close this question as off-topic because questions about specific subjects should be asked elsewhere.

The standard at my university was to draw the diagram in LaTex.
You can pretty easily make a flow diagram with TikZ and PGF:
\documentclass{article}
\usepackage{tikz}
\usetikzlibrary{shapes,arrows}
\begin{document}
\pagestyle{empty}

% Define styles
\tikzstyle{block} = [rectangle, draw, fill=blue!20,
    text width=5em, text centered, rounded corners, minimum height=4em]
\tikzstyle{line} = [draw, -latex']
\tikzstyle{cloud} = [draw, ellipse,fill=red!20, node distance=3cm,
  minimum height=2em]
\begin{tikzpicture}[node distance = 2cm, auto]
    % Place nodes
    \node [block] (model) {Model};
    \node [block, below left of=model, node distance=4cm] (view) {View};
    \node [block, below right of=model, node distance=4cm] (controller) {Controller};
    \node [cloud, below right of=view] (user) {User};
    % Draw edges
    \path [line] (model) -| node [near start]  {Updates} (view);
    \path [line] (controller) |- node [near start] {Manipulates}  (model);
    \path [line] (view) -- node {Sees} (user);
    \path [line] (user) -- node {Uses} (controller);
\end{tikzpicture}

\end{document}

results in: .

I highly doubt this can be called a "standard", as—from my experience—the number of academics who know how to write tikz code is quite small.

@eykanal you could be right, but at my university Tikz code was pretty much the go to for drawing diagrams in latex. I'll edit my answer to reflect that.

In my undergraduate classes in computer science I've used a tool called  Lucidchart. It is free for academic use, and I was able to just Sign in using my Google account which, in turn, is linked to my .edu email without filling out any forms. You should be able to do same as well if you have an edu account linked to Google. The whole sign up process is described here.
I found it to be a great tool for creating UML's, flowcharts, etc: it is easy to use, it has a variety of options for exporting your diagrams, and it is definitely more precise than Word or PP. Hope this helps.

Unfortunately, in my experience, most1 academicians facing the same problem just use Word or PowerPoint or MSPaint or whatever they have on hand. There are a number of professional diagramming tools that you can find, most of which have an incredible range of symbols and templates that you can use, and some of which are free. Any of them should suffice for what you need to do.

1) source: I made this up


text:
What can happen to a paper submitted without co-author knowledge
Every answer in this related question has some phrasing about it being unethical or, as the first answer "does not have the right".  Does a supervisor have right to submit paper without consents of coauthor students?
Another similar question and answer states simply "No" to being 'allowed' to do this. Co-author blocking publication . Some comments suggest it is extremely rare and unlikely someone would do this.
This question is similar Paper submitted by co-author without authorization, but about how to handle the situation as they still wanted it to be accepted.
Yet, the one case I can find in COPE, the self-described Committee on Publication Ethics, does not seem to consider this a journal issue.

• The corresponding author submitted an article without the knowledge
  of all or some of his co-authors.
  • The corresponding author was under contract with research centre X at that time.
  • The scientific content of the article is correct. A minor error that occurred since publication can be corrected by an erratum.

The result/answer to this problem:

On a show of hands, half of the Forum suggested that the editor do
  nothing further, a few suggested publishing a correction or some form
  of note on the paper regarding the authorship dispute, and only two
  people suggested a retraction.

Are there any reasons, legal or society-wise (does IEEE or some groups have specific information related), that this is not the standard?  This is not a question on if someone is allowed to just publish, it is literally asking, so-what if they do? What can possibly happen (to a paper or person) if someone publishes a manuscript without their co-authors permission?

Usually, nothing happens, except damage to the submitting author's reputation.
Anything could happen.  It depends on the coauthor's feeling and the content of the paper.  If the content of the paper is objectionable, then this might lead to retraction.  Potentially the submitting author could be fired.  But most likely, if a coauthor complains, the submitting author just promises not to do it again and nothing else happens.
Don't do it.  Just because unethical conduct has no direct consequences doesn't mean it's okay.  Don't even do it if your coauthors tell you to do it.  Note that the coauthor's permission is needed in addition to their knowledge.

Complaints, however could result in an academic being fired or a student expelled. Not likely, but possible.

it seems a very strange line to me. if someone plagiarizes, just as having 'objectionable content', this would be grounds for retraction, no? So publishing without the co-authors knowledge, especially if they did the work, is just a loophole around plagiarism by putting the person as a co-author?  Or if it wasn't previously published its not plagiarism, so if you hack someones overleaf account and publish their paper its not a problem for the journal.

@user-2147482637 It's more like lying or impersonation than plagiarism.

If the co-author is fine with the content of the paper, then submitting it without his/her knowledge isn't that big a deal - (s)he's likely to approve anyway. I'm guessing that this (point 3 in the case listed by COPE) is a big part of the reason why half the Forum suggested the editor do nothing. Another big part could be that the paper has apparently already been accepted. Since review processes usually takes a long time, it's unusual for the co-author to not be aware (and raise a ruckus, if so inclined) that the paper's been submitted.
Much more concerning is the case where the co-author actively opposes publication and lets the journal know before the paper is accepted. This will come down to the journal's policies, if it has any written for this, and/or the discretion of the editor. I know of two such cases:
In the first case, the author submitted a paper without the co-author's approval, although presumably with his knowledge. The editor learned about this when one of the invited reviewers stated that he has personal knowledge of the situation. Apparently the lead author was a student of the co-author and their relationship had broken down. The student did something and thought it was publishable but the professor felt it wasn't strong enough. The student decided to submit anyway against the explicit instructions of the professor.
Once the editor learned about this he terminated the review process and rejected the paper.
In the second case, the author submitted a paper without the co-author's approval, although with his knowledge, because the co-author wrote in to tell the editor he didn't think the results were robust enough, and asked to remove his name from the paper. The paper had already been sent for review. My understanding is the editor chose not to terminate the review process, but is likely to reject the paper unless the reviews are really good (this is an example of when a "revise" review nonetheless leads to rejection).
As for the case where the co-author actively opposes publication but doesn't let the journal know until after the paper is published, I have no experience with this, but my guess would be that the journal will analyze the co-author's reasons, and probably retract the paper.

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


text:
Doctor of Design (or Other) as PhD Equivalent, Future Risk
From another question regarding Doctorate equivalency, I found the link to this wiki article: https://en.wikipedia.org/wiki/List_of_doctoral_degrees_in_the_US
I have a few questions that are interlinked.  I'm sure someone will have a different opinion, but it seems to me these questions are clearer within the context of eachother, which is why I am not making multiple posts.  For one:

For the purposes of this survey, a research doctorate is defined as "a
  doctoral degree that (1) requires completion of an original
  intellectual contribution in the form of a dissertation or an
  equivalent culminating project (e.g., musical composition) and (2) is
  not primarily intended as a degree for the practice of a profession."

The quote above is categorizing doctoral degrees by their intention.  However, it is not clear how this intention is defined.  One school may consider a doctorate as a specialized version of a PhD, while another refers to it for industry.  Case in point, from the Doctor of Design at Harvard:

Thesis topics investigate more specific issues within individual or
  combined research areas, and do not necessarily correspond to
  individual academic disciplines. Instead, they are often
  interdisciplinary in nature, involving faculty and resources from
  other graduate schools at Harvard and contribute to expanding the
  intellectual range of design research.

This states there is a thesis, research, and contribution to the field.
On the other hand, NCSU states their Doctorate of design as:

Established in 2016-17, the professional Doctor of Design (DDes)
  program is an advanced degree program for established design
  practitioners, which complements the existing PhD in Design.

Which seems to fall under the category defined as (2) in the wiki quote "is not primarily intended as a degree for the practice of a profession".  Maybe I am reading into it wrong, but it does seem to suggest there are differences in how a school interprets the role of one program over another.
1) So is the equivalency based on what type of program you went through, or based on an assessment of the supposed meaning, averaged over schools?
Second, based on either the assessment, or university specific approach to the degree purpose, it seems the NSF keeps changing equivalency. From the wiki article:

part of an ongoing program of assessment that saw the number of
  recognized research degrees reduced from the 52 recognized from 1994
  (the earliest report archived online) to 1998, falling to 48 from 1999
  to 2003 and to 24 in 2004.The number rose to 20
  in 2007, with the Doctor of Design and Doctor of Fine Arts being
  re-recognized after being removed from the 2006 list, before falling
  again to 18 in 2008 when the Doctor of Music and Doctor of Industrial
  Technology were dropped.

2) If the acceptance keeps changing, such as the case in Doctor of Design, is the year received connected to the recognition of it as a research degree?
And finally,
3) is it then risky to get a degree that does not specifically say Doctor of Philosophy, as one day NSF may decide it doesn't accept it anymore?  If there are any examples within the community that this has happened to, or schools/tenure committees that have run into this issue, those answers would help.

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


text:
Infrastructure Expectation of University
Some grants limit spending of funds, for example, on buying a computer. Others are a little more open.
I have heard from colleagues that some funding agencies want to see that the university supports the researcher, so offering grant matching or access to facilities is a way to demonstrate this.
At least in the U.S., are there any written expectations from agencies of support for researchers (otherwise, are there standard practices)?
For example, is it expected that researchers buy chairs and desks through their grant?  I can see an argument for large equipment, then possibly computer components, etc., and at some point it moves to furniture, light bulbs, window shades.

It is common practice in the US for grants to be managed by the university itself, usually through a special "Grants Office". The grant is charged a fraction of the grant, sometimes quite substantial, for something called "overhead". This is about keeping the lights on and providing space and maybe general clerical assistance. But it is unlikely that you would see "light bulbs" as a listed expense unless the grant accounting is extremely detailed.
But, you can normally expect that if you are awarded a billion dollars (we wish) that you will only, really, have any control over a part of that. Your own such office can probably provide guidance on their expectations and what they provide for the "charge" against the grant.
And, the funding agencies have something to say about the amount of the charge and have their own expectations. See, for example, https://www.nsf.gov/bfa/dias/caar/indirect.jsp

You just wrote quite substantial, afaik the overhead is often on the order of 50%. Some source with numbers would be helpful.

@quarague, The quoted source does that. It puts the max at 50%, in fact.

“If you were awarded a billion dollars (we wish)” Wouldn’t grants like that be plausible in certain fields like high-energy physics, or do scientists working at places like CERN not need to apply for grants?


text:
Listing acknowledgments on CV
I have yet to see this, but was wondering if others have or if it makes sense to list acknowledgments in published papers on a CV.
In some questions on this SE, it seems significant contributions to a paper can occur, yet for some reason (maybe not contributing to writing of the paper), the person is listed in acknowledgments and not co-author.  This seems like something that is of relevance/importance.
In the other case, acknowledgments can be 'thanks for the discussion' in which it may have been a brief conversation with one important realization through the talk.  This seems more like daily life.
Some people seem to list their contributions tot he academic community, such as being a reviewer for a journal.
What would you think if you saw acknowledgments on a CV, or, would it make more sense to categorize acknowledgments into other topics, such as, 'Non-co-authored project participation'.

I was somehow confused at first, but now I think you mean: listing papers of other people in which you are not a coauthor but are acknowledged?

@PeteL.Clark right

See http://academia.stackexchange.com/questions/1112/should-i-include-a-publication-where-im-only-acknowledged-and-not-one-of-the-a

@boscovich good reference.  This is a duplicate, so i suggest deleting it.

We generally keep duplicates (though they are closed as such) to help steer people to good answers.

I've never seen "mentioned in acknowledgements" on a CV, and wouldn't know how to evaluate them if I did see them on somebody's CV.  Acknowledgements are often pretty random and arbitrary in their threshold, and can often indicate a very small involvement indeed (e.g., "Mary was eating lunch with us one day when the project was being discussed, and happened to say something useful").  This is different than something like service (e.g., reviewing), which typically has fairly well-defined investment in time, and is a known burden that needs to be shouldered by volunteers across the community.

Exactly. At best the person reading the CV will ignore it (because he or she doesn't know how to evaluate it) and at worst it will come off as an obvious and ineffectual attempt to pad your CV. Non-standard items whose evaluation depends on context and circumstance is best included in your applications by asking a letter-of-reference writer who is familiar with your contributions to discuss it. Tangible contributions to your group (like those that may be listed under your tentative "non-coauthored project participation" banner) can be discussed by your direct superior, for example.

When it comes to a CV, as with most things in academia, it's best to stick to form. Education, awards, publications, conference papers given, invited talks, departmental service, teaching experience, and possibly references and professional affiliations are just about all you should need. Anything superfluous will likely be misconstrued, ignored, or be perceived as padding. If you're applying for an academic position, keep it simple with only your most significant achievements, as people who look at CVs generally have to look at tons of them, and you won't do yourself any favors by being obscure. They also aren't professional recruiters and don't tend to love poring over CVs, so a standard form helps the evaluators get through this work more efficiently.
If you find you don't have enough things to put on your CV, I think it might just barely be okay to include a kind of "other projects" section in which you briefly discuss your involvement in this other work. But you are largely going to be evaluated on the basis of your own work, so it's hard to say what difference it will make. The CV is part of a nexus of relationships, references, and affiliations and won't stand entirely on its own. So it depends. If you worked on some important projects, perhaps you could ask one of your recommendation writers to mention the degree and quality of your involvement. These sorts of things can at least indicate collegiality, which is important.
As I'm sure you've done, you should look at other people's CVs for guidance and also visit with someone trained to help academics translate their experience into an effective document. My own CV had all the right components, but a counselor on staff at my university suggested I change the order of the sections and reformat it according to a different principle of emphasis and priority. That helped me a lot.


text:
What metrics do universities use to evaluate their performance?
I am curious how different universities evaluate their performance.  I am curious to know if there is a standardized (or even just generally accepted) set of metrics that universities use to rate their performance or to determine if their college is succeeding ("succeed" being a very open term here and likely varying between institutions).

What does it mean for a university to perform well? (High graduation rates?  Low dropout rates?  High endowment?  High fill rates for their classes?)  Is this even a well defined question?
What sort of metrics do universities typically use to evaluate themselves?

I keep mentioning universities but knowing how two year colleges approach the problem is also interesting (I'm less interested in the primary/secondary schools).  The question is also not location specific and might even be more intriguing to see how non-US universities measure themselves.

The strategy of my UK university seems to be to improve on all available metrics that do not require them to spend more money. At our most recent faculty meeting we were told that we needed to simultaneously increase our student numbers, increase our admissions standards, increase the number of contact hours, and decrease our average class size. They also pointed out that we should also strive to increase our grant capture and publication rates.
I think from an inward facing perspective universities evaluate academic staff on on whatever makes them look the weakest, while from an outward facing perspective they evaluate themselves on whatever makes them look strongest.

Interesting.  I suspect many US universities are guilty of the same behavior.  Thank you for your answer.