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Applying to another PhD program during deferral VS as a PhD student
Recently, a previous student of mine consulted me the possibility of applying to other PhD programs while deferring a PhD offer. He was an undergrad at my institution; he got a PhD offer last year but decided to work an extra year before starting his PhD. We had a good relationship while he was working in my lab, so I hope to help him out by seeking some information on this.
SE (i.e., this platform) seems to have very mixed opinions on this. From the answers I've read, some say it's fine while others bring up ethical reasons against this behavior. However, almost all answers (some even from the same people who are against reapplying during deferral) support a current PhD student applying for another PhD program (at least nobody said this is unethical). This, to me, is very puzzling because in the 2nd case the student has already costed not only a seat but also actual funding from the program.
If reapplying is allowed for current PhD students, why are people against it for current deferees? To the best of my knowledge (including in my own program), students who choose to defer are rarely required to sign a binding contract. From my perspective, they are basically PhD students who are on leave.

You seem to be asking for opinions, which make the question off-topic.

@Buffy I think it's appropriate to ask when I notice how essentially the same things get handled so differently in academia. I can't find information on this anywhere else. I already encouraged the student to seek information elsewhere as well.

Not everything is ok to ask here. See: https://academia.stackexchange.com/help. I have an opinion on the question as do others. But none of us can give a definitive answer. This isn't just a chat room.

I'm asking this question because I thought (1) there might be legitimate/institutional reasons (beyond opinions) why people are against reapplication of deferees and (2) other schools (i.e., other than mine) might actually require students to sign binding contracts and penalize students for doing so. If the answers to both are no, we need to stop "scaring" students that the previous offer would be retracted, as discussed here: https://academia.stackexchange.com/questions/44885/deferring-admission-to-reapply-for-some-phd-programs-next-year?rq=1

I would suspect that most departments have some reasonable idea of the percentage of deferrals who do not end up attending, for whatever reason.

Ethical dilemmas are so called because they force us to choose among competing values. In the case of your student, there's the value of keeping one's word (a value universally lauded) vs what is customary. For example, where I live there's a stretch of highway where most drivers exceed the speed limit, but I never see a line at the police station of people confessing to their crime. I also don't know of anybody who keeps track of all internet purchases and then sends the required state tax at the end of the year. I am sure that they all consider themselves law-abiding citizens, even though they all break the law (ie perform unethical acts) every day.
So yes, your student should keep their word and attend the university they were admitted to, but also yes, it is customary and normal for students to keep looking and to change their mind regarding attending the place they promised to. This is so common that graduate admissions offices have names for these situations, names like "yield" and "attrition". Yield is the number of admitted students who actually enroll in the program, and attrition is the number of students lost between accepting the admissions offer and actually showing up at the start of the semester (or the following semester). Your student needs to do his/her own value ranking and decided which one is more important. My opinion is that this falls in the "customary" type of ethical breach, and that the student, the one in the vulnerable position against the university, is the one who should be allowed the slack. They should keep looking. I say this even though I'm usually the one arguing against the "customary" type of ethical breach, and thus the only car doing 55mph on that stretch of highway. But there's too much at stake when choosing a graduate program, and the student is the one in the vulnerable position.


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Harvard referencing: same year, same last name, same initials
This is a question about the Harvard referencing system.
I've written a paper and cited two publications, each with a single author, both published in the same year. These authors are unrelated - one is a man and the other is a woman - but they have the same surname and the same two initials. They do have different first and middle names, but neither has a second middle name. So it's as it were Alan Brian Smith, 2012 and Alice Beatrice Smith, 2012.
How do I handle this? I'm guessing my inline citations should be either (Smith, Alice, 2012) or (Smith, 2012a), but can't work out which. Or maybe it's something else. Plus in the bibliography, should they be listed by alphabetical order of author first name? Chronologically?
Many thanks for any help.

Men and women can be related? Sometimes they're even married.

Yes - the style is determined by the publication venue.
As someone who works with a bibliographic database (Mathematical Reviews / MathSciNet), I find brief citations systems that use last name + initials "quaint" at best.  Yes, a human can possibly sort out whether A.B. Smith refers to Alan Brian Smith or Alice Beatrice Smith.  However, if both are occurring in the references of the same paper, there is a good chance that the two Smiths work in related areas, making the identification of author with paper not so easy. There are harder cases to separate. In our database, we have over 100 names of the form Li Li and over 300 of the form Wei Wang (not counting names such as Weifang Wang).  A favorite example of our catalogers are the two researchers named Angel Plastino and Angelo Plastino, both of whom work at Universidad Nacional Noroeste in Buenos Aires, who work in similar areas, and have coauthored at least 75 papers together.
I have very mixed feelings about bibliometrics, but many departments and deans do not.  Trying to match A.B. Smith to the correct author for an automated publication count is going to be a challenge.  Similarly, an automated match of the citation will be tough.  Some citation styles for journals are particularly brief, something I associate with physics journals, but they occur more broadly.  An example is the AIP "by number" style: initials and last names of the authors, the journal name, volume, first page number only, and year. AIP also allows a fuller style that uses the authors' initials, last names, title of the paper cited, journal name, volume, first and last page, and year.  The brief style coincides with listing references in the order they appear; the full style is for when the references are alphabetical.
As an author, you are at the mercy of the journal style.  If you have a choice, as with the AIP example, I recommend going with the longer version.  If you are a publisher of journals with minimalist reference style, I recommend that you give your authors a break and consider switching to a longer style.

The guidelines to the venue you are submitting to must be your guideline. After all, the title of the paper is what distinguishes one author from the other. And this information is present in the bibliography.
For the in text references, neither University of Leeds nor The University of Melbourne has any suggestion for such situation. However, both use the style (Smith, 2012a) and (Smith, 2012b) for same author, different publications. So, that is not correct.
Personally, I would go with adding a footnote at every page that the citation occurs, maybe with a Google Scholar or personal website page.
Writing the full name would not be a generic solution as there might be two different authors with same name and same surname.

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Can I map ISO standards to DOIs?
DOIs are specified in ISO 26324, but can I refer to that standard by DOI? In other words, is there a systematic mapping from ISO standard numbers (possibly including parts and release years) to DOI names? Ideally, this would work in a similar way for different standard bodies as well.
For international standard book numbers there is such a mapping, for instance: the DOI name 10.97812345/67890 and the 13-digit ISBN 978-12345-67890 have the same referent, just different syntax.

I am pretty sure that the published version of the standard will have an ISBN and thus you could use the corresponding DOI, but I am guessing that you are asking for a more direct way.

Indeed I am, since the PDFs I get from my library do not show any ISBN.

@mlk Both ISO website and standard pdf do not show ISBN or DOI.

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Number of Funded PhD Positions available to applicants
How can one find out how many funded PhD openings there are at a particular university in a particular discipline?
For example, MIT might have openings for 2,000 PhD students in all disciplines.  1,000 of these positions might be in the field of engineering.  But only 5 of positions might involve bioengineering.  And of these 5 positions, 4 might already be filled by PhD candidates in their second year of study; meaning only 1 position is available to applicants.
Any suggestions will be appreciated.

At US universities, it typically doesn't work that way.
The department usually doesn't think of having specific PhD positions that have to be filled.  Rather, admissions is done on a department-wide basis. Each year, the department sets a target for how many new students they want to admit, based on available resources.  Let's say for example that this number is 20.
Now, most applicants are applying to many different programs, so not every accepted applicant will actually come to study in this department.  Thus, if they want about 20 new students, they will offer admission (with or without funding) to some larger number, perhaps 40 or 45 (assuming there are at least that many qualified applicants).  This number would be chosen based on past experience as to what fraction of accepted students choose to attend, and can be varied if they have applicants whose applications suggest that they would be particularly likely or unlikely to attend.  A few additional applicants might be placed on a waiting list.
But it's entirely possible that the number of students who actually choose to attend is larger or smaller than 20.  If it's smaller, they could try to admit some more people from the waiting list, but that still may not bring them up to 20.  That's okay; they will just have a smaller cohort that year, and probably try to use a larger target number next year.  If more than 20 accept the offer of admission, then the department just has to come up with the funds to support them, and use a smaller target next year.
Also, seats aren't necessarily restricted by research area.  In mathematics departments, for instance, departments won't typically break down their targets as "we want 5 students in algebra, and 3 in number theory, ...".  They'll just admit 40 good students and let them sort out their areas of study after they arrive.
So the number you are looking for may not exist.

The number of funded positions in a department is not really known until late in the process. The best way to find out is to ask the department. I am not sure if knowing this information is valuable. Maybe it can influence your decision of whether to apply or not, but it is not going to help your application.

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Will time off spent doing things not related to my research interests count against me when applying to PhD programs?
I recently finished my undergraduate degree in physics and I currently have a year-long research internship. My original plan was to apply to graduate school (physics PhD) in the fall. However, the more I think about it, the more I'd like to take additional time off to pursue non-physics related interests (think: traveling, creative writing) and also to spend time at home with family (I grew up in a small-ish city where I doubt I could get a job related to my research interests).
I have been told that I have a pretty decent shot at getting into top-tier graduate schools (4+ years research, honors thesis, > 3.9 GPA, etc.). As has been pointed out previously, there seems to be a consensus that taking time off and getting experience related to your field is viewed positively/not negatively. However, my question is, would taking additional time off for completely non-science related pursuits significantly decrease my chances of being accepted to competitive PhD programs?

Physics isn't my field (Mathematics), but I can't imagine a program that would think less of you for taking time off.
The danger is that if it goes on too long you lose your "edge" and get "rusty" both at Physics and the academic life in general.
However, there is little worse than starting an intensive graduate program facing any sort of burn out. You want to start out with a maximum of energy and enthusiasm because the road ahead won't be easy. Your credentials are good, but the competition, if it exists, in grad school will be from people just like you - the best.
In my own case, I might have finished the doctorate earlier than I did had I taken a year to unwind from a very intense undergraduate program.
Finally, if you take time away and then apply, make sure you are ready with a good answer if asked why. Life is more important than Physics (for most, anyway).

It really does matter a bit what you do with the time off. So long as it isn’t the vague platitude of “finding yourself” (essentially, doing whatever the heck you feel like), it’s probably not bad if you want to volunteer somewhere or experience something different like an exchange program or even work a bit.

@aeismail, actually I thought "creative writing" was a pretty good reason. Stretch the mind however possible. But yes, not vague.


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How can I quit an internship before the agreed upon end date without burning bridges?
I'm a recent college graduate, and I'm currently four months into a research internship. My original plan was to take a year off before applying to graduate school (in physics) and use this internship as an interim job. The full story is complicated, and I don't want to go into especially much detail, but I've been dealing with mental health issues for several years now, and I've realized that I really need to take some more time and get professional help and actually put effort into dealing with this rather than going to grad school next year. I don't think that staying at this internship, in a city/state where I don't know anyone, and which it turns out isn't that related to my interests, is the most productive way to do that. So, what I would like to do is to quit at the end of this year, when my funding is up for review. I'm not really doing important work for the team, so I don't think my leaving early would actually be a significant hardship for anyone, and furthermore I am saving them the trouble of trying to find new funding to keep me here. But, I don't want to sound ungrateful to them for taking me on as an intern to begin with, or for the effort my mentor has put into helping me out with my projects so far, and I'd really like it if I could still get a rec letter from him when I do apply for grad school (my mentor has told me on several occasions that he is pleased with my work so far, so I'm pretty sure he would write me a good one).
So: how should I frame my conversation with my supervisor about leaving before the initially agreed upon end date? Should I talk about my interests not lining up with the group's work? Should I talk about my doubts about wanting to go to grad school immediately? This is not the sort of thing I've ever done before (quitting) and I wouldn't do it if I didn't feel like I had very compelling reasons to do so, but I don't necessarily think that it would be professional to share my actual reasons given general stigma against mental health problems, hence my need for advice.

When is the agreed-upon end date?

Next June (it was a year-long position, and I'd be quitting after six months).

Are you already getting professional help? And the advice of your doctor is to spend a year in more intensive therapy? Or have you decided upon this plan on your own? I am just asking because 1) It affects what you can honestly say and 2) It affects my recommendations on what steps to take in what order.

You haven't said where you are, but from your reference to living in an unfamiliar state, I'm going to assume you're in the US.
I honestly think your best course of action is to say you need to quit for medical reasons requiring treatment. You can stop there, any US employer should know better than to pry at that point.
This has the upsides of a) being entirely true; and b) doesn't leave your employer wondering if they did something wrong.

My advise would be to be honest. In fact the text describing your situation would be a very very good start for such a conversation: It values the support you had at the institution, it is honest towards your group, and it is clear that the reasons are personal and you are not just quitting because you are lazy.
I would rerecommend to make an appointment with your supervisor not later than beginning of november and explain the situation as above.


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How does score normalization among different graders work?
In my university, in a class with several hundred students, there are teaching assistants who are assigned a small fraction of the students for assignments which they grade. I have heard that they normalize scores among these teaching assistants to make it fair. How does that work?

Unless you know exactly how & what they do this is not answerable.

As asked, it's not answerable, because we don't know how it is done in your university. You might turn this into a question that would work by asking whether there is a standard method (perhaps in your country) or what common methods are. There is a risk that it will then be seen as too broad.... ;-)

There are many possible systems and so it varies with each situation. One is to use some statistical analysis, which can actually be unfair. It needs to make an assumption, probably that each group of students is a fair sample, which it isn't.
Another is to have someone look at a sample question from different graders and make adjustments.
One method that I've seen used on final exams is to have each grader grade one question from everyone in the course. So that each student is graded by several people.
Another possible method is to have each paper graded twice.
You can probably come up with more possibilities.
Some of these might be combined with advising the graders who seem to be too easy or too hard.
Most of them probably start out with grading rubrics for each question that graders are supposed to adhere to.
For your own situation, you need to inquire locally. There may be someone in the department who is responsible for all TAs and who coordinates these things.
I'll also note that doing nothing at all to normalize scores is also a possibility. In fact, when different professors teach small sections of the same course (no common lectures), it is likely to be the case.

What exactly would the statistical analysis be?

@Trial Statistical analysis in this case would be to apply a curve, but control for the different graders' scores. This assumes that the distribution of students under the graders is random (which it might not be, for ex, if the grader was assigned by a discussion section).

@Tyzoid Okay, thank you!


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IEEE Access License on Arxiv
I would like to submit an article to IEEE Access. As per their requirements, I need to add a license statement on my corresponding ArXiv upload, which will look like this:

IEEE copyright notice. © 2020 IEEE. Personal use of this material is
  permitted. Permission from IEEE must be obtained for all other uses,
  in any current or future media, including reprinting/republishing this
  material for advertising or promotional purposes, creating new
  collective works, for resale or redistribution to servers or lists, or
  reuse of any copyrighted

My question is: Which copyright do I have to select on ArXiv?
They offer the following options:

arXiv.org perpetual, non-exclusive license to distribute this article
(Minimal rights required by arXiv.org)
Creative Commons Attribution
license (CC BY 4.0)
Creative Commons Attribution-ShareAlike license
(CC BY-SA 4.0)
Creative Commons Attribution-Noncommercial-ShareAlike
license (CC BY-NC-SA 4.0)
Creative Commons Public Domain Declaration
(CC0 1.0)
None of the above licenses apply

Thank you in advance!

Only the last option applies.
Once you assign all rights to the IEEE (or anyone), then you no longer have the right to license the work yourself.
And the IEEE statements is pretty clear that they retain almost all rights. It doesn't mean that they might not give a more permissive license at some point, but you no longer have that ability.

This. In addition, from what you're shown here it's not clear that you are allowed to put it on arXiv at all.

@Flyto, perhaps you are correct, but my interpretation was that IEEE wanted it put up, but with their copyright notice.

Ah, you may be right.


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Adding a short example after explaining the part of the method
I am writing my paper's (social science) methodology part and it consists of several steps that I express mathematically. However, I have a feeling that one of the steps might be better explained if I also add some kind of an example to it right after formulas.
How acceptable is it in academia? Generally, does it mean that I have to explain my methods in a way they do not need an extra explanation?
I intend to publish this paper (maybe this is irrelevant, adding as extra info)

Examples can be useful. How many examples should be in a formal paper varies from area to area, and even from journal to journal. For example, in pure math, I've had some papers where examples have been considered completely acceptable, and at least one paper where the editors took out ones they considered unhelpful or overly verbose. In general, if you think the examples would be helpful, then put them in. The worst that can happen is a referee or editor makes you take them out later.

How acceptable is it in academia?

There shouldn't be an issue with this. While I'm not from the social science field, I've seen numerous papers that add figures or short examples that illustrate the theoretical concepts discussed. These are really helpful when the way methods are described carries a little too much abstraction and the reader isn't comfortable with it. If you feel the way you described the concept is too abstract or if you feel an example would help the overall understanding of the concept, then go right ahead with adding an example.

Generally, does it mean that I have to explain my methods in a way they do not need an extra explanation?

Yes... and no. Yes because its good to aim for a way to explain your methods such that there is no need for extra explanation. I generally think this is something that should be sought after when writing about one's methods. However, no because I don't think you can always generalize how the community will understand your writing. Thinking about this too much (i.e. trying to achieve perfection) can lead you to a writer's block.
Its a good idea to keep in mind the venue which you plan to publish. If you're writing for a community / venue that's specific to your topic, then I don't think you need to keep this in mind so much. But if you're writing for a more general community, then maybe there should be more effort to scrutinize how your writing style might be interpreted by others not so familiar with your field.
At the end of the day, when you submit your paper for publication, the reviewers should be able to point out if something is too vague or if there is too much information. Write the way you feel comfortable expressing your ideas and base the amount of explanation off of other papers similar to yours (if there are any).

I am writing for management community and my methods include the usage of combinatorics and dynamic programming. I guess in this case, it is better to try and make methodology part as understandable as possible

Illustrating your method with a brief example is perfectly acceptable, especially if you do it in a reader-friendly way. Indeed, paragraphs often start with a "topic sentence" (which introduce the main idea, e.g. a concise description of your method), followed by some "supporting sentences" (which substantiate your main idea, e.g. by providing examples), before ending with a "concluding sentence". Such a paragraph structure enhances readability - so go for it!


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Acknowledgements on a Masters thesis
Is it wrong or looked upon to acknowledge God on Master's thesis paper?

Maybe not if you field is Theology, but otherwise it will look weird, might even rub someone the wrong way.

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Unfair evaluation of written qualification
I recently took my Ph.D qualification exam. Out of the 4 exams I took, I passed 3 and I failed one. My professor failed me because I failed the written one and because of that, I failed the oral exam too. I asked my professor if I can see the written exam, and I found out that there were 2/3 questions I answered right, but he marked it wrong. I showed that to him and he said he is not going to change the score.
I do have a chance to retake the exam later, but now I am bit afraid, If I retake it, is he going to do the same again on the new exam. Any advice would help

Depending on country and institution, you may be able to appeal to your committee, department chair, graduate dean, ...

"there were 2/3 questions I answered right, but he marked it wrong" - objectively determined?

I asked to see my exam and discussed w/ the professor. The professor agreed i was right, but would not change the score.

It is your characterization that the evaluation is unfair. An alternate explanation is that it was a judgement call and that overall, the prof decided you weren't well enough prepared.
I can't make a judgement call here, of course, but in reality, you may not be very successful with an additional appeal - especially if it is confrontational.
My best advice is to study hard for the re-take and do well enough so that any judgement calls are in your favor. If you can arrange for an oral exam with more than one professor, however, you are at least partially protected from any bias. You might even be justified in asking for a different examiner.
If this were the last attempt at the exam, you might need to worry about appeals and such. But most of your faculty would probably suggest that you just do what it takes to pass. You aren't likely to get a pass when you have open the option of a retake.

It is not clear what you want advice for. You could try to rephrase your question.
Moreover, we can not really help you as we don't know the professor and also not the institution.
In some places, you could appeal the exam by going to higher ranked people, in other places, students appealing are always ignored.
It could be possible that you do the exam with another professor or not, that he does the same in the next exam or not, but we cannot say.
My advice: Talk to people which know both the professor and your institution. (For example, your student union.) Ask them if you can do something and if yes, what.
(For what it's worth, while I've met some blanantely unfair professors (women shall not pass the exam; after the exam no points will be added if there where errors in the marking), most professors listen to reason.)

Could you maybe explain how you know you answered right? Did the professor say, yes, your answers are right, but I don't feel like regrading?

How I know the answer is right, after the exam, I checked the answers with the professor and He told me couple of them were right when I asked about it. On one other question, I emailed him the source where I got the answer and He agreed I was right, but would not change the score.


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How to position myself to transition from doing wet lab research to doing computational work?
I am in the first quarter of the second year of my PhD. I learned to code as a hobby and have been quite passionate about analytical stuff. I got taken for a PhD basic research project which required a candidate with both wet lab and coding abilities, to be able to apply various programmatic tools to analyse various types of data. During the first year of my PhD I did an extensive analysis of single cell rna seq, bulk rna seq, microarray and Chipseq data for various endpoints. I mostly used already available programmatic tools. It was fun and my supervisor was higly impressed.
Now at the start of the second year of my PhD I discovered that my passion and motivation to perform wet lab activities are very weak. I seem to have lost many reflexes necessary for various wet lab activities. I am almost hating wet lab activities. I have to use some of my time to analyse data for my colleagues and I constantly find myself more passionate about the Bioinformatics stuff than with with wet lab activity. I am still familiar with Biological concepts.
I want  to ask my supervisor to modify my project such that I get completely exempted from wet lab activities and do only Bioinformatics. I wish is to focus on different types of analyses of genomics/transcriptomics/proteomic data within the context of the projects going on in our research group. I plan to apply available tools, modify methods in available tools or possibly develop my own methods to analyse various data. I last studied Mathematics in high school and I have never studied Computer Sciences. Online platforms including EDx and co offer basic courses in Mathematics and Computer Sciences. Could such online courses bring bring me up to date in Maths and Computer Sciences such that I can handle a purely Bioinformatics PhD project in this context? I have completed the Data Science Path from the Codecademy platform. So I have basic knowledge of statistics and basic concepts in machine learning. I am very familiar with self-learning especially online.
Thank you in advance for you highly cherished advice.

Can you make the title of your post not specific to biomed and bioinformatics? I think that would make it more broadly applicable and so it wouldn't be closed. Maybe: "How can I position myself to transition from doing wet lab research to doing computational work?" (but I don't know your field so I can't know how to rephrase it exactly)

Actually, I will make this edit. But if there is an even better title, do change it further.

Could you ask your supervisor?

@Anonymous Physicist. He is a medical doctor and knows very little about Bioinformatics. I want to convince him and myself that though I did not study Maths and C.S. in the university, I have the resources to succeed with a purely Bioinformatics project. I think contributions from experts in Bioinformatics could be helpful to me. –

Some online bioinformatics resources that I can recommend:

Bioinformatics ALgorithms
Rosalind bioinformatics problems
The Biostar Handbook


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MSc Dissertation - Model may have been flawed from the start, how do I deal with writing about it?
I'm currently writing my MSc dissertation for an MSc in Artificial Intelligence. My university allocates a 3-month period for the whole project.
At this point in the project, I realised my reasoning behind the model is somewhat flawed, but that is not a valid reason to request an extension. I am stuck in a loop of writing and re-writing my observations, but I can't seem to make any progress as I keep re-writing the same portions of the dissertation.
How should I approach writing the dissertation, given my reasoning was somewhat flawed from the start and I have no way of changing/re-implementing the model?
EDIT: I have spoken to my advisor, but as he is one of the two people marking my work, he can't really give me guidance on the topic outside of "explain your reasoning". I realised the issue quite recently and he said he would be unavailable until a couple of days before the deadline, so I can't currently contact him regarding my issues.

What led you to conclude that the original model was flawed? The chain of logic leading to that conclusion could be a fruitful discussion in your thesis. If it's because your analysis turned up inconsistencies or errors or failed validation tests, then your work has value in closing down non-productive paths to future researchers. Always remember that negative results are still results.

Related: https://academia.stackexchange.com/questions/30995/what-to-do-when-you-spend-several-months-working-on-an-idea-that-fails-in-a-mast/31082#31082

"my advisor [...] can't really give me guidance" This is a problem in the system wherever you're studying. The "advisor" should "advice", which is synonymous to "give guidance". If your advisor is not teaching you how to do research and how to write it down, they're not your advisor.

Assuming that you don't have the time anymore to change and correct things, you could explain the model and your reasoning that led to it, flawed or not, and then you do a Section "Critical Discussion" where you state arguments against it, and how you think it should be changed, and then you declare this as "future work".
Note that generally formal models are never perfect and can always be criticised, and one can find surprisingly bad flaws even in some publications. Of course some issues are more serious than others, but still, in my view, if an MSc student realises at some point that their model approach is flawed and the thesis shows that they understand this now and what the problem is, even without redoing things I'd think that's a good thing. Obviously it may depend a bit on how bad the problem is and whether I'd have expected the student to realise this earlier. But then as a supervisor I could see it as my own job to warn you in time about this, and if I didn't, I may have missed this myself, and so I can't blame you that much (even though I may not have taken that much time to think about it).
I can't know about the MSc thesis marking culture in your place, but as a supervisor I know that the time for doing an MSc project is very limited. It may well happen that a student goes for some time in a wrong direction, and time may not be enough to fix it even if eventually understood. So expectations are limited, and for me as a thesis marker it wouldn't be a big problem. (Of course it may depend a bit on what your ambitions are as it may cost you a few percent, but I wouldn't expect it to break anyone's neck.)
It's the scientific process that we try to solve a problem, go wrong, and then understand things better by learning from our mistakes.

So, as I've just found the issue, would it be sensible to describe the (flawed) reasoning in the methodologies, then describe the experiments I've performed (as a result of that flawed reasoning) in the results section, followed by the discussion about the flaws?
I'm worried that the experiments will seem like me just throwing things at the wall and seeing what sticks, given the inherent flaw in the reasoning and the fact that I was testing various scenarios to see how the model performed in those scenarios.

@AlessandroN. Ultimately you have to make the call yourself as what works "best" may depend on the specifics. My idea was to start off as normal, i.e., as if it were not flawed (although you can mention in the Introduction that there will be important criticism later), and then criticise it later. But how well that works in your exact situation and what your alternatives are I can't tell.

This is an MSc memoir, a compulsory step to your diploma (at least here in France, and generally in Europe).
Nobody cares about the MSc memoir and it is unlikely someone will read it if it is not really interesting.
Yours, according to you is not interesting because the idea is flawed. Your best approach is to say so and explain why it is flawed. And be done.
Your supervisor thinks the same so do not worry about writing a masterpiece.
There are thousands of MSc memoirs that have zero useful content, and they are still on the right side of the face, compared to those where there are lies added. Do not lie or hide anything - this is something that is not only immoral (YMMV) but also potentially a risk for you.

Has the OP stated this somewhere? If it’s the thesis project of a UK taught masters (3 month project for a 12 month masters is typical), then it could be a third of the total credit, and might even determine the final classification by itself.

I feel strongly that you shouldn't be making that type of assumption, and you definitely shouldn't be trivialising something that OP has clearly put substantial effort into. However I agree with your "say so and explain why it is flawed": an exploration of why the incorrect assumptions were made and what the consequences were could lead to a very interesting thesis which would be of lasting use to others in the field.

@MarkMorganLloyd: this is not a trivialization but a constatation. I have read countless MSc theses from four universities (in France, Germany, Poland and Scotland) and in general they are worthless. This is not a critique of the authors but rather of the system - the students do what they have to do in order to get their diploma and we pretend that we care about how they write a memoir.

@MarkMorganLloyd (cont'd) They will never do that again in their life, except if they go to Academia. They are also very aware of how it works and I cannot blame them. Thousands and thousands of students do master thesis so there is no way we can expect anything valuable to be created and recreated and recreated again. One thing is certain: this is absolutely not what the industry expects form them once they join the workforce so this time could be better used to teach them useful stuff.

@MarkMorganLloyd: finally the point is to help OP so I clearly told them not to worry, put whatever that have and call it a day.

@MarkMorganLloyd Arguably, if the student's thesis advisor can't give them advice on the project because they'll be grading it, the institution isn't demonstrating much effort/expectation towards students producing influential work.

@Bryan Krause From what I understand the advisor can't give specific advice on the writing portion of the thesis, but I have received plenty of advice regarding the experimental portion of the project.

@AlessandroN. That's certainly better, but communicating results is a huge part of the academic research process. I think the point WoJ is making in this post is that you need only to write something suitable to your examiners, and it's probably more important that you understand and communicate flaws than it is that you produce work that is broadly useful (meaning useful besides your own learning and assessing your learning). If your goal was to produce work that is broadly useful, your advisor would be helping you write it up in a way that is broadly useful.


text:
What distinguishes top researchers from mediocre ones?
I am a PhD student studying theoretical physics at a US institution. I am now beginning my fourth year in the program, and struggling to solve my first research problem. I see PhD students around me keep writing papers while I am still struggling to write the first one.
My advisor suggested a research problem that I am now working on. He is not helping me with the technical details of the problem, haven't suggested papers to read etc., but he suggested that, since I have been struggling with such a simple problem for a long time, then this is a sign that research is not for me.
As far as I know, I am not stupid. I passed all the qualifying exams and got the highest grades in all grad physics classes. I am also fascinated by the subject, so I do not know why I cannot solve the problem. I spent a great deal of time reading and trying to understand the subject (which is quantum field theory). However, I can not solve problems.
My questions are:

how does one approach a research problem (say, in theoretical physics) and solve it in a reasonable amount of time while absorbing the prerequisite background knowledge along the way?

What distinguishes PhD students who are productive in their PhDs and how do top researchers approach a research problem and solve it? is it talent? breadth of knowledge? or time management skills?

Is my advisor correct that struggling with a basic project for a long time is a sign that I lack the research talent? I came to do a PhD in physics hoping that someday I will be a top researcher in my field, so I am trying to see how to improve and become more productive.

Comments have been moved to chat; please do not continue the discussion here. Before posting a comment below this one, please review the purposes of comments. Comments that do not request clarification or suggest improvements usually belong as an answer, on [meta], or in [chat]. Comments continuing discussion may be removed.

Does your advisor have a record of PhD students who successfully graduate rather than quit, and (even better) continue in academia? Are there other PhD students of your advisor who get the same feedback from him? If his other PhD students are also struggling, it is possible that your advisor tends to choose problems poorly for his students, then blames them when things go badly.

Top... men.

The moderators should reconsider their rules before closing this post as it has already garnered enough attention and answers.

I would recommend to re-open this question. In my opinion, it is well formulated and sufficiently focused. More importantly, it has ignited an interesting discussion.

To be successful in research, you need some combination of the following:

Background/breadth: You need to understand the problem(s) that are relevant to your field. Why are they worth solving? What makes them difficult to solve? What has been done before? The more problems you are familiar with, the more likely you are to find one that you can address.

Insight: Most problems are solved by applying existing ideas/techniques/tools/data/etc in new ways. Can you read papers from another field, understand the gist of what they do, and identify how that might translate to your area of interest?

Logical reasoning: Can you systematically evaluate a problem and potential solutions? Are your arguments watertight and convincing?

Technical skills: Maybe you're good at taking rats apart. Maybe you're fluent in Ancient Sumerian. Or COBOL. Anything that lets you do something that others couldn't.

Tenacity: Sometimes, if you keep bashing your head against the wall after everyone else has gone home, you'll find the wall moves.

Communication skills: No matter how amazing your work is, if you can't convince other people that you've done something useful, was there any point?

Resources: Whether that's dead rats, compute time, library books or pencils.

Luck.

"7. Resources" Coffee, I've been told.

This is an excellent answer. But I'm going to say that 6, 7, and 8 account for most of it.

@Cheery: I would say that lots of 5 and picking the right wall are helpful, too.

Unfortunately I think #8 has more to do with it than you might like. Everybody talks about the people who solved some important problem. Nobody talks about all the people who failed to solve the same problem.

@A.R. It's even worse than that.  The Matthew effect is particularly punishing in academic research (which was the original context in which it was described).  Everybody talks about the people who solved an important problem and got a prestigious fellowship.  Nobody talks about all the people who also solved an important problem but didn't get the fellowship.

Wow, you really have it in for rats. Where did the bad rat hurt you? :)

None of these are as important as "passion for research".

@user1271772 I would categorize this under "tenacity".

@XanderHenderson but no one else that knows those words would.

@user1271772 "Passion for research" and $2.40 will get you a ride on the T.

+1, but resources should include human resources, as it's pretty much impossible to conduct research on one's own. I find it striking that you only list examples of animals or objects in resources.

I very well know a person who's quite strong in 1 to 5, but lacked 6, 7, 8 in a situation, where he had a research problem, a good idea how to solve it - good enough to file for a patent. Mere 5 days before another lab filed too, and had no precedent priority... but they did have more people, grants, and no comparable bureaucratic obstruction (most of the hard work of both sides proceeded in different countries eventually). So he had the patent. They did get the Nobel prize. Luck... Resources... Communications might be about convincing you ARE GOING to do something great (so gimme resources!)

Sometimes field selection depends on your goals for success. If you're gunning for a Nobel Prize, you're not going to win one in mechanical engineering even if you are really prestigious.

To move from a student to a successful researcher, requires insight. Insight into the nature of problems that is deep enough to suggest solutions that might be worth pursuing. Those solutions aren't obvious and the insight is built on a strong base that you develop as a student, but insight is of a different nature.
One way I developed insight (math analysis) was to solve, by hand, a very large number of similar problems. Eventually I could look at a formula and understand it without the computations. That was the start (only the start).
Insight gives you the power to think about things that "might" be true and the skill gives you the power to test them.
It took Einstein ten years of deep thought and discussion with a few other people to come up with Special Relativity. That development was one of insight building and constant return to the problem at hand.
You might talk to your advisor about this sort of thing. What is it that you are missing in your level of insight that is holding you back.

Note also that some problems are harder than they appear. Research is looking into the unknown and there are no guarantees about success or especially about timelines. Math, theoretical physics, and some parts of CS are like that. Probably the same in other fields as well.
If you talk to your advisor about what approaches you have taken to solving your problem, you can get feedback on whether those are naive or not. If they are, then you probably lack insight in some way. Otherwise, you are dealing with a problem that may be much harder than it seems. Hopefully you have an advisor sophisticated enough to help with this.

@Trunk, actually, I don't think that is "clear". Some students are passive and don't ask the right (or any) questions. So, they hear "comments" but not sufficient feedback.

some problems are harder than they appear - and sometimes professors/advisors who have not looked closely at the problem may well be misguided about how hard/simple the problem really is (say if tested across a large swath of PhD students in the area of interest).

I'm a fellow Ph.D. in theoretical physics that used to struggle with research, and occasionally still does, after two post-docs and one teaching position.
To succeed, I think you need to give yourself time and significantly change your mindset. As others have mentioned in the comments, part of the process is to become able to solve problems independently. And I mean textbook problems first. The only way to do so is to solve them on your own without looking at other people's solutions. Every little detail counts, every small derivation, every little disappointment. Often you need to sleep on problems and approach them again with a fresh mind, and, quite often, you need to ditch your approach for a new one worse comes to worst. But you need to fail a lot of times first.
What helped me realize these things was a teaching appointment that led me back to research after it was over. It helped me see myself through my students. Undergrad education is concerned with solvable, well-behaved problems for which even a closed-form solution often exists. Research is completely different. You often resort to unorthodox methods, new approaches, etc. After all, it's supposed to be new knowledge. And it won't come in a linear fashion (most of the time).
Another problem I faced was my ego. I couldn't accept that I was unable to solve even simple problems sometimes. Accepting it helped. Heck, I even accepted I'm not as smart as I thought.
Regarding your advisor, I must respectfully disagree with him. If you went all the way to having a physics degree, you can go further. But there needs to be that "phase transition" I'm describing above.
Much like the ABCs, physics research has its ABCs. You need to know the fundamentals of Classical Mechanics, EM, Thermo, Stat Mech, Quantum Mechanics, etc. Then you need to learn Math Methods, numerical methods, coding, etc. It's a hell lot of things so that needs time and guidance. Sometimes, it might be better to stop, take a step back, and assess what went wrong and try again. Try, fail, try again, fail again, etc. Sure, some lucky ones are extremely intelligent and get it on the first try. Most people don't though.
One last thing. Just jump into a problem and enjoy the process. Enjoy what you learned. Develop consistency. Spend some time on it every day. Get a small result. Discuss it with your advisor or some collaborator. Keep moving. Find friends and collaborators. Go to conferences, and keep discussing with people. Socializing that way helps. You need to find some passion for it. Be bold!

@Trunk, I'm not in a position to be someone's supervisor yet but maybe one day I'll get there :)

I like this answer. It reflects my mindset.

"He is not helping me with the technical details of the problem, haven't suggested papers to read."
Unable to evaluate you as a researcher, I can though safely say that your advisor has failed his job. Perhaps a prominent scientist, he is a plainly bad teacher.
My son wasted several years under the supervision of such an advisor, a man equally famous for his scientific accomplishments and his total disregard for his graduate students. While staying in his group, my son devised a clever strategy of creating collaborations with people, from both his university and other schools, who had experience in the area and were interested in the problems suggested to my son by his then advisor. In collaboration with such people, my son published several good works; and I would say that at that time those colleagues were effectively acting as his true advisors.  Eventually, my son found a decent advisor at a different university, quickly wrote his thesis there, and got a postdoctoral fellowship at a stellar place. I would emphasise that the new advisor was not a world-known scholar -- but was a dedicated teacher caring for his grads.
In short, this is what I would do:
(a)  Through publications or word of mouth, try to find people working on this class of problems.  Get in touch with them.  See if any of them could be interested in collaboration. (Don't be shy!)
(b)  Meanwhile, look for a better advisor, at your school or, perhaps, elsewhere.
(c)  Last, and by no means least, do NOT believe your advisor's words that "research is not for you".  Do NOT let him discourage you.  Quite possibly, you are not genius -- but one does not to be genius to write a PhD thesis. And in the situation you have described the principal problem is not you but your worthless advisor (who may at the same time be a brilliant scholar, why not?).

I am really sorry about your situation. Based on what you have indicated, in my opinion, your supervisor might not be doing his(her) work very well, which is to support you and help you to succeed. Autonomy and independence in research come with time and training, and PhD supervisors play a key role for this to happen.
Would you mind elaborating a bit more on the relationship with your supervisor? If you are not really getting support to your growth from it, it may be better to quit and start somewhere else. I am curious that you had not got input from your supervisor even for simple things as suggesting a paper to read.
On the other hand, be cautious when it comes to comparing yourself to others, as every person undergoes a different learning process. Furthermore, not all research problems are the same in terms of difficulty and the work required to solve them.
Soft skills, such as time management, are also important to succeed. Time management is more than just filling up a calendar with things and there is a "science" behind that. You may benefit from training in this respect. You find valuable tips about this on the internet and there are some courses available on platforms like Linkedin Learning as well.
You may also want to read this article:
Nature article on failed PhD
Best wishes,
AME

Self promotion is not welcome here.

@Nobody Just to clarify, I am not looking to promote myself here, but just to state my experience and offer help to someone that clearly needs it, that's it!

@AME I understand you're coming with a genuine intention - it's just not really SE etiquette to invite OP to contact you in person. Not only is it a blurred line between helpfulness and spam, but it makes the solution private, so other users can't benefit from it. It's better to give the best advice you can in your answer, ask OP for further details if needed, and expand the answer accordingly. Or alternatively, you're also welcomed to create a chat channel with OP for a discussion.

@Neinstein thanks for your valuable input, I get the point now and have updated my response accordingly.

Is my advisor correct that struggling with a basic project for a long time is a sign that I lack the research talent? I came to do a PhD in physics hoping that someday I will be a top researcher in my field, so I am trying to see how to improve and become more productive.

I think it is important not to see this as an evaluation of your personal worth. As you have pointed out, by becoming a PhD student you have proven that you possess the necessary skills and qualifications. Your lack of success can be due to a multitude of factors, some of them may be the fault of your supervisor (e.g., he might be misjudging the simplicity of the problem or not providing enough guidance) or due to bad luck (e.g., you have chosen a field or a problem that are not suitable to your abilities, or your best skills are not really for this type of the problem.)
It might be also that you are less suitable for academic research - which does not mean that you are a bad researcher. After all academic research is a pageant, where the winner is not always the most intelligent one - success in academic research is also about choosing fashionable problems, publishing your results quickly, popularizing your achievements, making connections, etc. There are plenty of examples of strong students who were given difficult problems, struggled and eventually abandoned academia, whereas more mediocre ones did good career, because they had a caring and/or influential supervisor or accidentally struck the problem that attracted much interests.
If the situation persists by the end of your PhD, you will have to consider changing career, rather than following a standard path PhD-postdoc-professor. On the other hand, if this is just your first year and your professor makes such remarks, it is more reasonable to consider changing the supervisor.

@Trunk I don't think that this is a view that is held by most academics - this is certainly not the view held by the academics themselves (and those who come to such a conclusion often leave academia.) There's cynicism everywhere, but I think outside if academia things are more honest, since in a bigger world one is less dependent on being friends with grant managers, having influencial supervisor, etc.

@Trunk People with "theoretical" background in software, math, stat, physics are of course more mobile. But importantly, what matters in industry or non-academic government employment is the skills, not the field in which you worked - this makes for a much bigger job market. Tenure is not the only problem in academia - finding a good postdoc, if you come from a small university and non well-known supervisor is hard, and after tenure there is chase for grants, prizes, prestigious positions, etc.

I am also fascinated by the subject, so I do not know why I cannot solve the problem.

Not every problem is for everybody. Specialist fields such as your are as much art as they are science. Very few artists, in any field, are universalists. They like certain approaches and takes on the subject, and dislike or even disdain others. Perhaps that problem is just not your problem. And that's not to say that there is anything "wrong" with you. I'm an electrical engineer. I am supposed to solve a wide variety of problems, but there are only some that I really enjoy working on and got good results in. Even though my training was broader than that.
Look back at what you enjoyed doing in classes. There probably is some pattern there. Look at classes that were most specific to the sub-field you're facing in the research problem, and see if you can figure a way to build a bridge from what you know to what you don't know. Try to digest your knowledge gap into manageable chunks. Read what others wrote about the topic.

I spent a great deal of time reading and trying to understand the subject (which is quantum field theory). However, I can not solve problems.

I'd go on a limb and suggest: try explaining the field from basic principles to a non-specialist with some grounding in undergrad physics/engineering/mathematics. That's one way to evaluate your understanding. Explaining things so that a non-specialist could solve a very simple textbook problem requires exquisite understanding first.
Whatever you find, no one should be suggesting that you're "stupid" - don't think that way. You clearly are not - just asking the question here is a sign that you see what's going on and try to do something to improve the situation.

My advisor suggested a research problem that I am now working on. He is not helping me with the technical details of the problem, haven't suggested papers to read etc., but he suggested that, since I have been struggling with such a simple problem for a long time, then this is a sign that research is not for me.

This is absolutely an issue with your advisor not providing sufficient supervision, mentorship, and training. A friend of mine was told by an advisor that they'd never met anyone who got accepted into graduate school who wasn't capable of finishing grad school. Grad school is about training to become an independent researcher. Being good at that isn't some innate quality. It's a collection of skills that you learn, develop, and refine over the years through guided practice.
For a few years, I struggled to make much progress with my proposed dissertation project (analytical work in theoretical astrophysics). I was stubborn and kept telling my advisor and committee that I could do it, but eventually had a proper conversation with my advisor. I needed to finish my dissertation and the only way for that to happen was putting the original project on the shelf and shifting to projects I could complete in a more reasonable timeframe. I met with my committee members and other colleagues I'd met over the years to chat about other research projects. No one ever told me my lack of progress meant I wasn't cut out to do research. Your supervisor shouldn't be saying that to a student.
Does your programme require students to have a committee? If so, how often do you meet with your committee? Do you know their thoughts on this situation?
I'll emphasise again that I don't think you're the issue . I think it's an issue with your advisor. Are there other faculty or postdocs in your department or whom you've worked/interacted with that you could reach out to? A new (related) project and some extra guidance could make a world of difference.
To answer your questions:

Get help. Trying to complete a project in theoretical physics as a graduate student without having regular help, guidance, and feedback is extraordinarily challenging. Are you struggling with developing the requisite skills? Go through relevant sections/chapters in a grad-level textbook and foundational papers. Chat with other researchers in your group and department (students, postdocs, faculty, etc.) when you're stuck. Unsuccessfully trying to figure it out on your own for several days (or even worse, weeks) isn't an effective use of time.

Good supervision, mentorship, and guidance.

Nope.


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Plagiarism detected in a conference proceedings (Edition 2023)
I recently found out that a theoretical concept of mine (published at 2020) has been presented as a new contribution in some conference published in 2023 without citing my 2020 paper. I reached out to the authors seeking clarification, and they explained it was an oversight on their part, as my concept is integral to the title of my paper and readily accessible on Google Scholar.
Although I've contacted the editors of the conference proceedings, I haven't received a response.
Can anyone suggest whom else I can reach out to, and what steps can be taken to address this situation ?

Did they cite your 2020 work?

Independent development of ideas happens. Without many more details it would be difficult to determine malice.

@Try2GetBack2Academia No they didn't !

@JonCuster Yeah, but when you have a paper that mentiones explicitly some concept in its title, it is difficult to say "Oh, I didn't see this paper !", and you have to cite it to be more honest !

@mahou_2019 That's not the standard. The idea that they didn't see your paper is surprising but it's not by itself an indication of plagiarism. After all, the reviewers clearly weren't aware of it either.

Does your paper show up on Web of Science for example? Personally I don't bother using Google to search technical literature. And whatever 'detail' is in a title likely is not as descriptive as you might think. You seem very sure they intentionally did not find and cite your paper, and you have not shown that at all. Of course, with a 3-year head start you should be well down the road of further developments anyway.

@mahou_2019 Is there only one possible phrase to describe the concept? Are you saying that they use the same phrase as you used in your title, so they should have googled the phrase and found your paper?

@Sneftel Let's not forget that many reviewers are very busy and they don't do their job correctly !

@JonCuster I'm not sure abiut their intention, but when we write a paper around some concepts we should check out what others have already said about those concepts. What I mean is, my paper clearly mentiones the main concepts right in the title, so it's hard to miss or not find. Anyway, like you said, we've added a bunch of new contributions since 2020, but it's still important to acknowledge what's not right. People should be recognized for their mistakes so they don't make the same ones again in the future.

@mahou_2019 Exactly. And other academics are busy too. I’m just saying, don’t forget Hanlon’s razor.

In truth, with millions of scientific articles published every year, not everyone can know every relevant article. People will miss some, even with the best of intentions. When that happens, one can politely point out that you had a related paper, but that's about everything you can do -- you can't reasonably demand that they correct the record, nor should you be mad about the situation.

In such situation, the conference editors may ask authors to write a "Correction to" one-page-paper in which they should clarify some errors or missing parts and state that the original paper is updated according to that !

As an editior myself, I would see no reason to ask authors to do that. If they genuinely did not know about the paper (and I see no reason to believe that they did not), they did not do anything wrong.

Like explained below, authors may add a note at the end of the paper like "at the time of publication the authors didn't know about the 2020 work.". This says that not all editors behave similarly in such situations, fortunately !

@mahou_2019 They could, but as I said I don't see a reason why they would need to. If you make them do it, someone else might ask for a second correction, and soon everyone would demand corrections of everyone. Each of these corrections collectively requires a couple of hours of work -- for what? How does this make science better?

You seem to have done what you can do for the moment. Wait a bit for the response from the conference committee. It isn't likely to come in a week or so. But, also think about what you requested from them and what is possible for them to do.
The good part is that the authors have acknowledged the error. The rest takes time, decisions, and effort.
It is possible that while their work duplicates yours, that there was no intent to plagiarize, just sloppy research. Not good, of course, but it doesn't reflect badly on you. You have the publication and the history is clear.

And lets not forget, some fields grow extremely fast, and duplication or overlap of work is getting increasingly common, completely without malicious intent. Only if they resist citing OP in future work, I would become suspicious.

"Plagiarism is the practice of taking credit for someone else’s work."  It is not plagiarism if they did their work ignorant of your work.  From what you say they are not taking credit for your work. They might be duplicating your work, but that isn't plagiarism.
You've contacted the editors, and there isn't much else to do.  The most likely outcome here is nothing happens, the next most likely outcome is a note at the end of the 2023 work saying something like "at the time of publication the authors didn't know about the 2020 work."  Maybe that will show up in the abstract as well, but that seems even less likely to me than at the end of the body of the text.  I doubt the word plagiarism will be used outside this stack by anyone but you.

Duplication happens when different terms with their formal definitions refer to the same semantics, here authors may miss some papers by looking at litterature for one concept rather than other ones that are semantically equivalent to the first one. However, when you try to propose a new concept you should make sure it does not exist in litterature otherwise you should cite what exists and compare it with what you try to propose. If authors use a previously published concept with the same formal definition and claim clearly that is a new contribution, I don't see how to call that !?

"a note at the end of the 2023 work saying something like "at the time of publication the authors didn't know about the 2020 work.".......This will be enough for me !


text:
Contacting Department about a Job (UK)
I keep hearing that in the UK, it's a positive thing to get in touch with the department during the application process to show you're really interested. Is this true? (I've read that in the US this isn't really a thing... but places like Vitae.ac.uk recommend it?) If so, what are the sorts of things I should ask?
(For context, I'm in a humanities department applying for a permanent-track job in a really good faculty for our field.)

The practices vary across different Departments/Universities in the UK.
If a University/Department follow a formal process, in which applications are assessed against the selection criteria, then "getting in touch" won't have any effect.
However, many departments in the UK ignore/bend formal rules and instead rely on existing networks of permanent staff (sometimes only Profs) in the Department to form a shortlist of candidates invited for interview. If your target Department is like this, having someone in the Department to recommend/promote you during a selection process is a good/necessary thing. It is not very likely that you achieve much by "getting in touch", unless you're already on their radar, but it won't hurt to try.

It can help at some points in the process. Not the fact that you made contact has influence, but the fact that by getting in touch and asking appropriate questions can assist you in making your application more relevant to their needs.
It helps you understand what research  groups there are there, what courses they teach, what are the gaps that they are trying to fill and so forth. Then when asked at interview, or when making a presentation a question like "How do you think you are a good fit for his department" you know what to say!
Yes: you can learn much of this by reading their public facing materials like web pages, research output and publicity and so on, but remember much of this is targeted at recruitment of students (undergraduate and postgraduate) and not on the hiring of new staff.
Some advertisements often state "for more information please contact A.Prof@uni.ac.uk", and they really mean it.

This is in addition to the excellent asnwers by Dmitry Savostyanov and Brian Tompsett - 汤莱恩 with which I fully agree.
Contacting a department prior to applying also gives you a chance to determine whether the department is a good fit for you prior to preparing an application. You could do this by asking some of the questions that you would otherwise ask either during an interview or after receiving an offer. Examples include questions on what the advertised research-teaching-admin split means in practise, what support is offered to newly hired lecturers, and so on.
You may find that the department is not a good fit for you after receiving answers to those questions and save the time it would require to prepare the applicaiton.


text:
Should I decline a request to tutor a class I will be taking?
I am a first semester master's student. A professor has sent me an e-mail with an offer to tutor a bachelor class (this would be a paid job). I do not know him personally but he told me in his e-mail that I was recommended to him by a professor whose class I took this semester.
Now here is the conflict: I did my bachelor's at a different institution and in my country, it is normal for universities to require students who switched institutions to take 1-2 bachelor classes in the first semesters of their master. Among the classes I am required to take is the very same class the professor offered me to tutor. As a tutor, I would be teaching exercise classes and grading other student's solutions to the problem sets.
Can I decline this offer for the above reason or could it be seen as making excuses? I do want to pursue a career in academia so I am afraid that this could be misunderstood as me not being willing to tutor classes or do work for the deparment in general.

It would help to include which country you are in.

You need to tell the professor. I would suggest that you tell them you want to tutor the class and believe you have the skills and knowledge, but that you are being required to take the class for credit. Then ask if it might be possible for the tutoring to satisfy the requirement.

+1 In my university, it's quite common to be able to get the credits for the course you're tutoring - after all, that way you probably learn the material much better than other students.

+1 I was about to answer that I have in fact done this - allowed a student to grade/tutor for me (in discrete mathematics) in return for course credit he needed. All with permission of the chair and nigher-ups as necessary.

@JiK Teaching something is indeed an excellent way of learning, but most students at my institutions want to get taught by someone who has shown that (s)he has mastered the material. A tutor who takes that course at the same time, would have real trouble with her or his authority at the sessions. For that reason I would not hire someone like that.

@MaartenBuis I totally agree with your statement, but I am not sure that is what the previous comment meant and is clearly not what I meant. I think the comment was saying that you can get course credit by taking the class OR tutoring the class, not by taking the class AND tutoring the class.

@MaartenBuis If a professor already offers the job for a student, it can be assumed that the student is qualified enough, no matter where the bar is. Whether the student needs the official credits for his degree and how to get them is another question, and this SE question is about that case, not about whether the student is qualified.

@JiK I teach in Germany, where they have a saying: "trust is good, control is better". That describes the attitude here well; if something isn't officially certified then it does not exist. So the fact that a teacher hires someone is not enough here to overcome the fact that that course wasn't passed. You may not think that that is a good thing, but I just have to live with the peculiarities of this culture.

@MaartenBuis So are professors, postdocs etc. required to take a course before they can teach it?

@JiK postdocs and up have a diploma, students don't. So students need to justify their position some other way, mainly by having taken the course themselves, and having performed well at it. This is not a formal requirement, but the informal requirements in a culture are often much more binding than the formal ones.

To more explicitly answer the question the OP asked: When I am hiring, and would accidentally put you in the position you described, I would appreciate if you told me, and would have absolutely no problem with you declining. I would consider putting you in that position a mistake by me, and it would not reflect badly on you.
If you indicate that in principle you are interested, I may look at other courses I teach and see if I can switch tutors between classes to make it fit, or keep you on the list of potential tutors for next semester.

Tutoring such a class while taking it for credit seems like a conflict of interest that should be avoided. You might want to let him know that you are taking the class and want to avoid the conflict. You can and should thank him for the opportunity and ask if there is some other class you could tutor or another way you could be of service.
Tutoring in the strict sense (giving advice and feedback) is no conflict, but you shouldn't be involved in any grading activities for a class you are taking.
If there are several tutors for the class, the professor might also divide the work so that the conflict can be sidestepped. You only tutor. Others are involved with grading and such. That assumes you already have the knowledge and skill to do that, of course.

What are the interests which conflict? How could this cause a problem?

@Behacad, if you grade a course and at the same time are being graded for the same course you could, if not scrupulous, make yourself look better than the others by making them look bad. The potential is there, which is the conflict.

He mentioned tutoring, but I don't think grading? You do raise a good point, although only if grading is in any way subjective.

@Behacad, Actually, he does mention grading.

You should absolutely not tutor the class you are taking yourself, at the same time.
If you will be taking the class at another time and already have all the knowledge (but not the passing grade needed yet), then you might take the job, but make sure to discuss with the professor that you didn't pass this class yet.
You yourself should be sure that you have the knowledge needed for the job before taking it. If you don't, that is a perfectly well excuse, just make sure to point out that you are willing to tutor in general.
If, on the other hand, you take the job and it turns out mid-semester that you have no idea what you are doing, that is bad...

Why not? If the professor is aware that you're taking it, and arranges it so that you don't end up doing anything that is a direct conflict of interest, and if you have the necessary knowledge to tutor it, I don't see anything wrong with it. It sounds like the OP already knows the material.

I think it is not rare, especially for courses that are cross-listed as both undergrad and grad courses, that one of the grad students is the grader for the homework, and even has office hours.  Typically, that grad student is the advisee of the professor and he's fulfilling his stipend responsibilities at the same time.
As long as you fully disclose, there's no problem.  (I'm in the U.S.)

-1. While it may not be rare for US grad students to tutor grad classes, I've never heard of them taking the class for credit (as a student) while doing so. This would require the student to grade their own homework, among other problems. It may be reasonable to let the student tutor instead of take the class, though.

@cag51  You haven't heard if it, and that earns a downvote?  When I was a grad student it was quite common.  In a grad course, the homework doesn't really matter, so the conflict of interest angle is moot.

Fair enough, downvote retracted (or would be, if SE allowed it).


text:
Write email to a professor who is recruiting new PhD students
Should I send email to a professor who has said on his website that he is recruiting new PhD students through xxx program? Some people marked this as a duplicate of another question, but I don't really think that question can solve my problem.

What is xxx program -- is it a valid program? Be specific? Add few more details to make it a proper question.

Yes. I just want to use xxx to stand for the program's name. Because it varies from university to university, so I didn't give a specific name.

Yes you should. This is exactly why that message is on the professors website.

Why would you not?!

Because usually I will contact the professor for PhD position vacancy. But the professor has said this on his website, so there is no need for me to ask for this. Besides, because students are admitted to the program rather than the lab, and I am interested in several professors' work, so I suppose I should not ask the professor whether I am suitable in the application process. Actually, I am wondering if there is a need for me to contact these professors.@ HEITZ


text:
Discovering mistakes in thesis after submission and printing
So here is my issue - I submitted my thesis 2 years ago and it was accepted and i was granted the M.S. degree (I am in the US, BTW).
Now, when I opened it to read some portions, I found some missing references to data tables, and otherwise some typos.
I am starting to freak out about this, because of the consequences. My question is this - can the university somehow "re-evaluate" my thesis and find it unacceptable? I am not sure about how it works in academia, any help would be appreciated.
Edit: My question is bit different than the others, as it is asking whether the university has the power to "re-evaluate" my thesis based on typos and omissions.

For all practical purposes every thesis written in human history has typos in it.  Don't worry about it.

Titles are usually rescinded for actual deliberate misconduct (think "lying", not "being wrong"). Almost all theses have errors in them. If you want the record to be set right, you can post a corrected version of your thesis on your website (or on the arXiv if the subject is one of the arXiv subjects).

The examination regulations specify what needs to happen so that a "re-evaluation" of an accepted thesis becomes due. Generally, such re-evaluations only take place in case of severe academic misconduct, like plagiarism or faking data. In the case of minor presentation issues, there is nothing to worry about.

The recent rescinding of PhD titles in Germany were cases of plagiarism, "delegating research work", or outright faking of data. Honest mistakes, and especially if they are minor, such as typos or omissions, should not be expected to lead to the revoking of a PhD, much less an MSc title.


text:
Replying to an editor after plagiarism accusation and manuscript rejection
As the title of this question suggests, a manuscript that I submitted was flagged as plagiarized by iThenticate and was rejected by the editor.
The editor claims that the manuscript has 35% similarity with a previous manuscript that I submitted to the same journal. The email made me feel very bad, as the accusations are something that I have intentionally avoided throughout my publications. I also should note that I chose not to write repeated information and instead wrote a summary of some of the methods while citing the mentioned already published work.
Summary about the scope: it's mainly about sensors and machine learning, though both papers have very different goals and methodologies:

Already published work: usage of many sensors to achieve two goals
with machine learning regression and classification.
Submitted manuscript: usage of one sensor to achieve a completely
different goal from the already published work by machine learning
classification and to explain the models with explainable machine
learning.

We do not have access to iThenticate, but we do have access to Turnitin. The summary:

Overall, there is 23% similarity with other published work.
With the paper that the editor mentioned, there is only 8%
similarity.
The similarity mainly comes from affiliations, references, acknowledgments (funding agency and project number).
The description of the sensor is flagged as well (name of sensor,
company, location).

I have no idea how to do the following:

To tell my mentors that this happened; I'm afraid that I will be in
trouble if I do not sufficiently rebut the plagiarism accusation.
To write to the editor to clarify what happened, though I suspect
they already checked where the similarity is coming from.

What is your position? PhD, post Doc, or what?

I am currently finishing up my PhD, this was suposed to be the last publication (5th) @Walter

@DanielHatton I have checked the other overlaps as well, it was mainly technical terms such as Machine Learning, units, sensor name and name of manufacturer. There are also very generic overlaps such as "samples were taken" or "frequency spectra". I did not copy paste anything except for some parts of the methods section where I also rephrased and added a source to previously published work.

@DanielHatton the editor mentions "... , the overlap goes beyond the normal occurrence of standard phrases in your field... Text copied from copyrighted works from third parties, even in an introduction, should never be used without clearly identifying the other source. Every manuscript should present some new results or insights and be written in an author's own words....". I tried to reproduce the problem with turnitin, but could not. Most overlap comes from the already mentioned sources: references, technical terms, affiliations, funding agency, etc...

@DanielHatton here I should also mention that I opened both manuscripts side-by-side. Could not determine any similarities other than the ones that I already mentioned.

The editor doesn't seem to be aware that you are the author of both papers. Otherwise why does he talk about third parties? It would be worth pointing that out to him, but I would certainly look elsewhere for publication.

@DanielHatton yes, still in the same publishing house

@user207421 the editor mentioned that the overlap is with a previously published work by the same authors.

(Nitpick: you probably don't mean rebuke here.  Perhaps rebut?)

@gidds yeah, sorry for the semantic typo. Not a native english speaker...

@TinoD No need to apologise — native speakers often misuse those words, too.  But perhaps you could edit the question so we can see exactly what you meant?

@TinoD In that case the question of plagiarism does not arise. You can’t plagiarize from yourself, by definition. Did he really use that word?

@user207421 after an email to the publishing house, they sent me a reply that "we see the editor took the following decision reject - plagiarism". Although in the comments he only wrote "high similarity" and that the work is not "original due to the high similarity". I think he didn't look at where the similarity is coming from. Still no reply from him

The role of a mentor is to support you, not to punish you. So, IMHO you should/could have asked this very question to them. They presumably have some experience with this journal and can provide better advise then we can here (as we don't know the journal).
I suspect the editor has not carefully checked where the 35% similarity comes from, since your own analysis doesn't show undue similarities. I would write to the editor pointing our the similarities you are aware of and which are perfectly fine (affiliation, grant number, sensor make etc). If the editor rejects your arguments without really answering them, then I would consider a different editor or journal. There is no point in dealing with editors that see no sense.

thanks for the answer, I will discuss this with the supervisor as you mentioned.

+1. With respect to OP's question about writing to the editor, I would foot-stomp the advice here: talk to your supervisor before replying at all. Your supervisor can certainly give advice about how to phrase your reply -- or they may be so outraged that they send a strongly-worded reply in their own name. Either way, better to coordinate your strategies.

What if the journal has a policy of flagging authors for plagiarism and preventing them from submitting other papers? It's not clear if that's the case here, but if it is, and it's an important journal in the field, it may be worth fighting just to ensure they can submit other papers in the future.

@anjama i'm afraid this can happen. At the end of the comments from the editor: "... the journal will automatically detect the repeated submisison of this paper, and maybe reject it."

@TinoD I think it's pretty standard that you can't resubmit a rejected paper (unless invited to do so). I'm referring to hypothetical future papers that are different from the one that was rejected

@anjama Is that a policy that exists in any journal?

I agree that it is important to wipe that stain off even if one does not intended to resubmit to the journal. If only for the record.

@AzorAhai-him- DNA and Cell Biology announced 3-year bans for evidence of misconduct (plagiarism, data manipulation, etc) back in 2015. No idea if it's still an active policy (I don't see it in current author guidelines, but it may still be an internal policy)

Anecdotal answer here. I once had a similar experience, except it was 98% similarity...to the preprint of that paper on biorxiv. Never assume editors have put in the leg work, they have a lot on their plates and do it without pay. I politely pointed this out to them, I got an apology, it progressed and was published.

Thank you for your answer! I brought a paper back to life once before: editor rejected despite the positive reviews. I wrote the editor and they mentioned a "mistake occured during the decision process". The decision was rescinded and now it is still in revision...


text:
Why are there barely any Masters programs in Pure Mathematics in the USA?
I was just wondering why most graduate programs in the US have no Master's programs. They mostly are PhD programs. Why is this the case? After obtaining an undergraduate degree from a Canadian university, what would be your advice about going straight to a PhD in the US? Do you gain the same knowledge en route to the PhD as you would in a Master's program or would it be more beneficial to do a Master's elsewhere first and then apply for a PhD?

Because US PhDs typically have one or two years of coursework leading to a Master's before you start research, so you don't need a Master's beforehand.

I'm not sure it is even true. Lots of places award Master's. But many of those are awarded to doctoral students along the way.

Many math programs offer master's degrees as well as Ph.D.s  Some students enter intending to get only a master's degree.  Others enter intending to get a Ph.D. but decide at some point to stop at a master's degree.

Many programs offer master’s degrees but prefer Ph.D. Students and admit very few students into the master’s program.

I think @NajibIdrissi raises an important question. I got a master's degree in CS early in my career both to get the theoretical background to my programming job, and to enhance my promotion prospects. What careers would benefit from a pure math masters?

If you are acceptable and accepted in to a doctoral program there is no reason to earn a Master's degree first. Many universities will give doctoral student a Master's along the way. For some (maybe not many, but I don't know anymore) there is nothing special to do but to ask for it. In my case I wrote a thesis, though not of the depth of a doctoral thesis.
If you earn a Master's at one institution you may actually have a problem in that what you did doesn't match up well with the requirements of the doctoral program you apply for later. This could actually slow you down. If you want both, it is advisable, if possible, to earn them from the same institution, perhaps with an "automatic" Master's along the way.
But for some, who don't want or need a doctorate for what they intend to do, a Master's can be earned. Some HS teachers do this. Some people are just not convinced that they want the commitment of a doctoral program after undergraduate. A doctoral program is a much bigger commitment than a Master's of course.

Mine was also a "got it when I asked for it" situation.  Technically speaking I was awarded my Master's one semester before I got my doctorate.  I'd completed the requirements years before that, but had just never filled out the paperwork.  The department also had good funding, and so admitted everyone as a Ph.D. track student to give them a TA position. Even the students they "knew" were probably only going to earn a Master's.


text:
What is a good GPA for acceptance into a top mathematics graduate program?
I am in a Master's program which is graded 100% on my research thesis. I also have a first class Honours in mathematics with average grade somewhere between A- and A, where A+ is best. Also, my university's math department is ranked somewhere between 40th and 50th in the world.
In short, my grade point average is okay but not great, and so is my school. I would like to go to a First tier (Harvard, MIT, Oxbridge), or at least tier 2 (Chicago, Michigan, UPenn) graduate school. Do I have a realistic chance at any of these places? Also will age a disadvantage (I'm 28)?
Edit: My GPA on the US scale is around 3.6 plus/minus 0.1.

Welcome to Academia.SE. Please note that we can't evaluate applicants' individual credentials or chances of success.

(I am the Graduate Coordinator for the mathematics department at the University of Georgia, which is consistently ranked around the 50th best mathematics department in the US.  I also received my PhD from Harvard, which is consistently ranked in the top three.)
Zeroth of all, if you think that University of Chicago is a "second tier program," then I think your tiers are too small to be meaningful.  I am very familiar with both Chicago and MIT and think these departments are comparable in quality according to a broad range of metrics.
First:

Also will age a disadvantage (I'm 28)?

Absolutely not.  Age discrimination is illegal and also not truly not done in American graduate programs.  Moreover I am not even sure that you have to disclose your age, but as someone who has been most directly involved in graduate admissions in my department for the last two years, I can assure you that the admissions faculty almost never notice the age, let alone take it into account.
Second:

Edit: My GPA on the US scale is around 3.6 plus/minus 0.1.

That is indeed not a great GPA relative to your competition.  The median GPA for applicants to UGA is, I believe, slightly higher than this, and I shudder to think where UGA would rate on your "narrow tier" system: eighth tier, maybe?  The very top graduate programs have their pick of the litter: they could, if they wanted, enroll a class full of candidates with essentially maximal GPAs, GRE scores and recommendation letters.  And this is what they largely do, while also looking for candidates who are exceptional in their research achievements and promise.  So, for instance, a place like Harvard would take a candidate with a 3.6 GPA if they had written a truly significant research paper.
Third: the GPA is just one number, and as a number, 3.6 is not so bad.  With that GPA, a more important question is: in which courses did you do well, and in which did you do less well?  If the less good grades are confined to the early years of the program and your transcript shows a clear upward trajectory that is supported by the recommendation letters, then many programs will not view a 3.6 GPA as a negative.
Fourth: we all want to go to the best programs we can (as we should!), but when it comes to your admissions strategy, you should take a more conservative approach of applying to schools in multiple tiers.  As a quantitatively minded person, I recommend that you tackle the "Fermi problem" yourself: how many students in the world do you think are interested in doing a math PhD at Harvard / Princeton / MIT / Stanford / Chicago / Berkeley / Oxbridge and have strong but not perfect backgrounds from internationally renowned institutions?  How many spots do each of these schools have per year?  I think you will find that the competition is fierce.  You might get in -- and I heartily agree that you certainly won't if you don't apply, so I think you should apply -- but there are going to be a lot of other, similarly (well!) qualified candidates.
By the way, schools "as far down" as UGA still have very strong programs in certain areas, and a strong student can do very well at these places.  At UGA some of our PhDs have gotten NSF postdocs, one of them is now a tenured faculty member at one of the elite schools you mentioned, and so forth.  UGA is internationally renowned in algebra, geometry, number theory and topology.  I could say similarly strong things about most other institutions at the same level on the rankings --e.g. Boston University, University of Virginia, Dartmouth, Emory, University of Massachusetts -- they have some tremendous strengths.  In summary, the number of really strong graduate programs in the US is larger than you might think, especially as an international student.  Please keep that in mind.

The OP might be using QS 2017 Math ranking: MIT 1, Harvard 2, Oxford 4, Chicago 13, Michigan 19 and UPenn 35. Yes, this ranking surprised me. Of course, we can say QS have their own way of ranking. But, at least this is one of the world rankings. What truly shocked me is UPenn 35. . How did they go out of top 20?

@schaahu: That's a good find.  I agree that there are some surprising findings there, e.g. that less than ten American departments are better than the National University of Singapore.  But it is hard to compare dissimilar things...

The numbers are fine, the schools are fine. What isn't fine is that the competition is all pretty much like yourself and there will be a lot of competition. Don't assume that every school you apply to will accept you so apply to more than one (several?).
However, at this level, the numbers don't tell the whole story. You need to say in your application materials what is "interesting" about you so that those evaluating will put you into the short pile (further consideration) rather than the big pile. Talk about not only your past math successes, but also your interests. Talk about any research that you have pending or under consideration. If you get an interview (used some places, not all) be prepared to shine but also be flexible.
Committees are looking for people who will work hard and who will most likely be a success. Nobody is perfect, but some candidates will appear to be perfect on paper.
Why do you want us? Why should we want you? Think about those questions.

My own comment here reminds me also that it is useful to remember that "ability" in mathematics is not, generally, independent of field. You can be the third wonder of the world in Analysis, say, but struggle a bit in Abstract Algebra. Much of this is a question of insight - do you correctly flag the things that "ought to be true" and are worth studying, or are you limited to following the proofs of others. If your lower grades in some courses is limited to that sort of effect, then (a) I suspect those aren't your favorite topics nor the ones you want to work in, and (b) you have a basis for explaining the lower grades.
Also, in this case, the makeup of the faculty at a particular school may be more important to you than the ranking of the school overall. Find a place that plays to your strengths and where you will find the best guidance. Lots of great schools out there with lots of great faculty.

It is my impression that top graduate programs only consider those who has near perfect grades, for example a 3.9 GPA, and I'm guessing this the level of excellence expected by such schools?

Like I said, the competition is fierce. But whatever the situation, your record is what it is, neither more nor less. If you don't apply you won't get in. Guaranteed. But you shouldn't panic in any case. There are also plenty of great schools you haven't listed, both in the US and elsewhere. If you have specific interests, say Analysis, the faculty in that specialty may be a more important consideration than the "tier" of the school. Assuming you want an education and not just bragging rights.