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Working and doing an MSc in physics in Europe
I'm currently finishing up my undergraduate degree and I will soon start to apply for graduate school. I'm gonna apply to some schools in Europe (mainly Germany), but one thing I'm very worried about is funding. As I understand, European universities do not offer TA positions for international students. And I haven't been able to find suitable scholarships. I will most likely have to work, and this is what I want to ask about. How is the job market for people with a physics degree, say in Germany? Can I find a job to sustain myself during my master's study? Thanks.

Do you need a visa to live in Germany? If so you would need one allowing you to work and study.

Some German scholarships for international students: DAAD, DeGiS. There is also German Grant but I think that requires your uni to recommend you. Also, check if you are eligible
for a scholarship that your home country provides to international students.

I am not even sure how much a European MSc. is even "graduate". It is normally heavilly lecture-based and not that much research. In the Bc. one learned some general basics (e.g. general physics and the necessary math) and in the MSc. one learns some more specific subject (astronomy, ttheoretical phys., solid state, ...). You will need most of your time for studying.

Europe is quite diverse in the relevant respect, and the situation in other European countries can be quite different from the one in Germany.

It is diverse, but Bologna harmonised a lot. E.g. here (not Germany) used to be normal to have a 5 year MSc. right from the high school and now we have the 3 year BSc. and 2 years MSc. as Bologna prescribes.

For Germany in particular some answers:

It is not correct that German universities do not offer TA positions for international students. It is relatively common that M.Sc. students conduct tutorials for B.Sc. students and get paid for doing so. But this does not help you much. These "HiWi" positions are very poorly paid. Also, you basically have to start your M.Sc. studies first and then check each semester whether you will snatch one of these positions. Not a good starting point for somebody who has to prove that he/she can support herself/himself before getting issued a visa (note that there is no such thing as an offer letter for a HiWi position, so they cannot be used as a proof of funds in visa interviews). Oh, and if the language of instruction in the B.Sc. is German, then you need to be proficient in German. Oh, and of course priority will typically be given to those students who excelled as a participant of a previous iterations of the course.

How good the job market is depends on (a) where exactly you go, and (b) what you skill sets are. If you, say, want to study in Berlin and are an excellent programmer, you most likely will have more problems finding a flat to live in than a job to pay for that. If you study in a city without companies whose primary working language is English, you will have a harder time finding a job. But note that even if your visa allows working on the side while studying, there is a legal maximum of 19 (or 20?) hours per week of working for many aspects (such as health insurance) because after that it's not working on the side while studying but studying on the side while working. Do not expect your visa type to allow the latter (if you need one - EU nationals have it easier here).

Scholarships are rare in Germany. Now for international students, the database by the German academic exchange service (DAAD) appears to be quite well-filled....for German standards.

Some remarks on the HiWi positions. First, these are meant to be taken by full time students. Usually the contract is for 10 hours a week and the working schedule fits with your other studies. Making studies and work fit into a single schedule can be a major issue for any other kind of job. Second, they are reasonably well paid relative to the amount of work required and the work is automatically related and often useful for your studies. But the pay is nowhere near sufficient to live on, it is nice supplement if you have another non work source of money.

Here is some more insight concerning the situation in Germany:

A lot of people I used to study with and a lot of the students I work with now have at least partially or often fully financed themselves while studying by working on the side. This is very common, and since you don't have to pay tuition fees it is also feasible. The amount of money you will have at your disposal will be at the lower end, and probably some frugality might be in order, but it can work.
As DCTLib already stated, there is a limit of 20h/week that you are allowed to work while officially being a student. As a German, or EU-citizen, you could opt for being a part-time student and work more, but if you enter Germany on a student visa, you probably will not be able to do that. You will be required to maintain the official student status. As suggested in the comments, I will add the following: the 20h limit applies only during the semester. In the 2 months summer break and about 1,5 months late winter/early spring break, you are allowed to work full time and can thus use these periods to earn extra money to make it through the semester.
If you work and study at the same time, the schedule of your courses will dictate when you will be able to work - at least when you take your studies seriously. This is preventing most students to take on "regular" part time 9-5 jobs. They rather work: in bars and restaurants, as sales assistants in shops, etc., that is in jobs that have more irregular hours and allow you to work on weekends, but might have nothing to do with your degree.
You can also work at universities, but as DCTlib already said, the chance you will get hired right away is low, because regularly, students that are already known for their skills from previous semesters get the job. A good alternative, though (especially for a physics graduate), is to look for student jobs at a non-university research institute: in Germany, there are  Fraunhofer Gesellschaft, Leibnitz-Gemeinschaft or Max-Planck-Gesellschaft. They are all renowned research institutions, and have many institutes all over Germany. Depending on which city you decide to study in, the scope of one of their institutes might fit, and they often have student jobs available. Working at such an institution, you might even have the possibility to write your thesis there and do some research on your own.

You could add that the 20h restriction only applies during the lecture period which is only 60% (?) of the year.

@FooBar That is a good suggestion, I will do that. I think the "Vorlesunsgfreie Zeit" is roughly 3,5 months long

@Sursula: I think that, strictly speaking, "vorlesungsfreie Zeit" is between 4.5 and 5 months at most university (almost two months between mid of February and mid of April and almost three months between mid of July and mid of October). But of course the time period that might be effectively used for a full-time job is considerably shorter since many exams, and sometimes also small courses or seminars, are scheduled in this period.

authors: Vladimir F Героям слава


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Should I mention research I conducted at University X in my application to other universities
I am a high school student and in grade 9 and 10 I conducted research for my science fair project at a recognized university under the mentorship of a professor and his PhD student. I designed and carried out experiments in the university lab during this time as part of my research. I think this would be beneficial for me to mention on my applications to universities, especially my first choice university (which is not the university I conducted research at). However, I'm concerned that mentioning another university in my application to other universities may harm my application. I really do want to mention this though because it is relevant to the programs I'm applying to.
Do you think this could harm my application and is it worth mentioning? Is there a way to mention it without harming my application?

Definitely mention it. Any research experience will set you apart from your peers, regardless of the caliber of institution it was conducted at. In your application, you should focus more on highlighting what you did rather than where you did it anyway.
In general, no university should penalize you for doing work at other institutions, especially as a high schooler. Some individuals may automatically equate your work value to the caliber of the institution (an unfortunate reality), but this really only matters a little when applying to graduate school, and more so when applying to postdoc/faculty positions.

People do research at other universities all the time.  This includes whether as part of a high school program in affiliation with local universities or other research institution, or as part of a summer internship program or REU program (sometimes because they didn't have much opportunities for research at their home institutions).
Mention your research.  It will definitely put you a leg up at any competitive university.  In some cases, it can help provide a perspective in terms of why you may want to attend a certain university over another institution.
Note that this also applies to applying to graduate school (and potentially postdocs, as Davis mentioned).  In general, it's a good idea to get different perspectives so you have a better idea of what you want down the road, so you should definitely go to different universities for undergraduate and graduate education, although in some sense this applies for undergraduate admissions as well.

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

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Can I call myself Dr. after getting provisional PhD certificate in India?
I have just passed my PhD final viva voce and got the provisional certificate for PhD in India. The provisional certificate states that "The candidate has passed the PhD viva voce examination and fulfills the requirement(s) for the award of Doctor of Philosophy" . However, the actual degree certificate will be provided during the convocation ceremony as per norms.
So, can I write myself as Dr. from now on in my resume, postdoctoral and job applications- or I have to wait until I get the actual degree? Is there any legal or official regulations for when a person can call himself Dr. Something?

This depends heavily on your location. Are you asking specifically for communication inside India?

Related / potential duplicate: When can you call yourself doctor?

I am asking for communication inside India and also about  intrnational convention (if there is any)

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


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How many days reviewers get to review minor revisions?
I sent  my research work to an sci indexed journal. However, it was under review for 5 months.. So we sent query to the editor. After sending the query, the reviewers' comments came just within 4 days suggesting a minor revision.
We sent the manuscript with minor revision but now it is again under revision for 15 days.
Now, from my earlier experience, I am worried uf they again take 5 months to review a minor revision, or suggest something else (like a major revision after a long time).
I have to leave the institute within 2 months. So, if they suggest anything like that it might not be possible for me to do additional experiments by then.
My questions  are-
(i) How many months do reviewers get to review a manuscript with minor revision?
(ii) Do the  reviewers get reminders from the editor every week? is it  possible that the editor's email go to spam and the reviewer cannot notice it?

Depends on the journal. For one of the journals I used to handle for example, all revisions (minor or major) had the same reviewer deadline of 21 days.

Thanks. Do the editors send reminders to the reviewers within 21 days? do they send the reminders every week?

@Magenta it again depends on journal. Sending these reminders is automated by the EMS, and for the journal in the answer, there's one reminder sent a week before the deadline.

@user1 https://academia.stackexchange.com/questions/55665/what-does-the-typical-workflow-of-a-journal-look-like-how-should-i-interpret-a Does that answer your question?

https://academia.stackexchange.com/questions/169784/awaiting-reviewer-scoresafter-minor-revision What about this then? @user1

From the author's perspective, the formal review timelines are not something to count on, because both reviewers and editors can mess up. A rather recent example: We yesterday received the acceptance for a minor revision we submitted 5 1/2 months ago. Apparently our assigned editor was unreliable in their communication to the journal and reviewers, and was finally replaced with the EiC.
For you this means:

I have to leave the institute within 2 months. So, if they suggest anything like that it might not be possible for me to do additional experiments by then.

You should start preparing a contingency plan in any way. Some other person in the lab (potentially some PhD student or post-doc) should be familiar enough with the setup to continue your experiments, if required.

"We are not able to do additional experiments because of XYZ" is also a fine answer to a concern.

@AzorAhai-him- Potentially risky. Navigating reviewer demands is an art in itself, but if there is one reviewer who requests one specific experiment to be executed before they can accept the paper, then they might be inclined to recommend rejection upon such an answer.

Thank you.  But, actually, it is  important for me to get the paper published to apply for post doc. I don't know if mentioning the work as "under review  manuscript" in my resume will give the same impact or not.

@Magenta We have a question about that, too: How "submitted", "to appear", "accepted" papers are evaluated in a CV?


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Can I use one graph of mine in two publications without citing?
I am a researcher working in the field of Catalysis. I was working on two seperate reactions (suppose R1 and R2) which were supposed to be the part of two seperate publications.
Reaction R1 has been done by me independently with catalysts A B C, D whereas reaction R2 has been done with collaborators with only catalyst B. One can notice  that catalyst B is common in both the cases, therefore some of the characterization data for B are same too . I have already submitted reaction R1 for publication in a journal and it is taking too long to get any response from the editor. On the other hand the collaborators want to submit the reaction R2 soon.
I am worried that as some of the data of catalyst B are common in both cases, the plots for catalyst B will be similar. I cannot  cite R1 work as it has yet not been published.
Therefore, can it be considered self-plagiarism if I just change the plotting style, colour etc for the characterization data of catalyst B (so that it doesn't seem identical to that used in R1 work) and use it in R2 work? Also, the plots used in R1 contain all the data for four catalysts A, B, C, D in a single figure but the plots used in R2 would contain ony the data for B in one figure; therefore can these two plots be considered non-identical? Currently, it is not possible to do fresh characterization for catalyst B, which might have solved the problem.
Can anyone  give any suggestions?

There is nothing wrong with including the same figure in two manuscripts.  You can mention in the figure caption that the same figure appeared in your other work.  You can cite an unpublished manuscript.  You should not alter a figure purely to obscure that it holds the same information; that would be the only unethical/unhelpful thing you could do here.

This might help you: https://academia.stackexchange.com/questions/162537/how-to-address-dependencies-when-publishing-a-chain-of-papers


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Affiliation in collaborative work
If I contribute to a collaborative research work in the conceptualization and data analysis phase (not with the PI), can I use the name of my university in the affiliation ? I have heard that I can only use the university affiliation if I have used the university resources or the research was carried out in the university. But if I am contributing to the conceptualization and data analysis, I am technically not using any university resource. Then what should be my affiliation ?

Are you a student or faculty member at that institution?

@Buffy I started the work as an independent research (mainly involving statistical studies) during my PhD, asked my supervisor for help - which he didn't. So, I carried out the work on my own. Now I am doing job in industry which is also unrelated to the topic of the project. Recently, I have found a collaborator and with his research work I can combine my personal project work. But I am thinking about which affiliation to use as the work was technically done during my PhD but not with my supervisor, I can't use the name of my current company either

Independent researcher usually works

@Buffy I thought about that. But I can not see many research papers authored by independent researchers in reputed peer reviewed journals. I had the impression that the publishers don't take independent researchers seriously, as it is hard to say whether the researcher has a PhD from Oxford or is an amateur writer

No, there just aren’t many independent researchers out there.

Consider affiliation to be a mutual thing. If you are employed by a university or you are a student there then you are affiliated with them. It isn't about resources, but about a relationship that is recognized by both parties. I once did some consulting to IBM, but I wasn't affiliated with them. The people I consulted with there, were, however, affiliated (employees).
You aren't affiliated with the university of a collaborator unless they, somehow, recognize that relationship and will attest to it if asked. That is still true even if you somehow use some of their resources on a collaborative project.
There can be edge cases, of course. If a university founds some research center and invites you as a member of the team, even unpaid, you can probably claim affiliation. But most cases aren't that subtle. Collaboration between faculty at different institutions isn't the same thing.


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Is it mandatory for some students to fail in an exam using relative grading?
I am seeing the relative grading structure of few of the institutions. The formula they follow for grading is as follows.
For a large batch of students:

they take the final marks of students
Calculate the mean marks
Calculate the standard deviation of marks
Then for those students whose marks are greater than mean + 1.5* standard deviation are assigned A+ ( the highest grades).
those students whose marks are less than mean - 1.5* standard deviation are assigned F( failed).

My question is if the distribution turns out to be symmetric around mean (like Gaussian), will it not be true that there must be some students that will fail mandatorily.
I may be wrong but I find this concept quite absurd and amusing. Can someone help me with this?
I have many times seen in class having relative marking all the students to pass, how this is achieved or the distribution is not symmetric there?

What if no student has a score less than 1.5 standard deviations below the mean?

@GoodDeeds If I say that none of the student has got less than 1.5 of standard deviation then I am saying that distribution is asymmetric. However, in a large class distribution should more or less follow Gaussian or for that sake if I take any symmetric distribution then suppose I got 10% students A+ grade is it possible then that no student will fail?

My experience, even with large classes, is a bimodal distribution... the students who get it and the students who don't.  In such a distribution, the mean is not really a useful measure of central tendency.

Possible duplicates or at least related questions: https://academia.stackexchange.com/questions/167023/ https://academia.stackexchange.com/questions/20063/ https://academia.stackexchange.com/questions/160109/ https://academia.stackexchange.com/questions/121991/

@Userhanu Not necessarily: every student getting the same mark also gives no students below -1.5sd. I also see no reason to expect the distribution to be anything like symmetrical. Comparing the data here and here (PDF) for 2019 (since 2020 exams didn't happen), many subjects look very asymmetrical.


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Cannot find a research group for my PhD program before fall 2021
I am a 1st year physical chemistry graduate student in an American University. I was admitted in September 2020, but I actually started the program in April 2021 due to the visa and pandemic issues. For this reason, I started my lab rotations in April and I found that a lot of groups which I am interested to join can no longer take new students before the start of the new academic year (Fall 2021). However, the department office wants me to join a group before that, so that I can be separated from the incoming 1st year students in fall 2021. I feel quite stressful and anxious, because I am reaching out different faculty members in the department, but I still cannot find a group that can take a new student before fall. I even tried to reach out groups which were my 4th or 5th choices, some of them still did not reply or they cannot take me.
I started to lose my passion. I can see I may end up joining a group which does not work in physical chemistry, if I persist to fulfil the requirement from the department. I am not rejecting other fields in chemistry, but the scenario is just totally not what I expected, and I have not even started to work on my own research project yet! I am feeling myself being unproductive, and a bit worthless due to this.
Should I continue to explore the department? Or just wait until fall to see if I can start over again? I would be grateful to hear any kinds of advice.

Are you definitely being pressured to join the group that you will stay with through graduation? Or is it just a matter of finding a group that can support you for a few months?

I am not sure, but I think it would be the later, since the program allows student to change their PI if they find that they do not really suit the group. But I do not think it is not a good idea to just choose a group to stay for a few months.

@tb30624700 I think that's wise. I assume from your question that you are in a model where the typical path is for your first year to be covered by some loose "new student funding" that is explicitly or implicitly designated for students to have some freedom while choosing a lab, but the assumption is that once you choose a lab this is where you complete your primary thesis research and also receive funding for the remainder of your studies. In that model, changes later aren't impossible, but they should be for very good reason.

What I'm getting at is that the department may be concerned about your progress, or they may be concerned that they are paying your stipend from overhead rather than from a grant. The advice will probably be different depending on which of these is the case -- in the former case, it makes sense for you to wait until Fall when your preferred groups have openings (which is only a few months away); in the latter case, it makes sense for you to find a group that can delegate a project in exchange for a few months of funding, regardless of your long-term plans.

I think the department indeed concerns both of them, my admission was deferred and the office is directly paying my stipend this summer. I will talk to my graduate program coordinator and my academic advisor more to see how to resolve this, though I am somehow getting more exhausted mentally and perplexed. Thank you all for your great advice.

I've known people to be in similar circumstances, though due to funding crunches rather than the pandemic.
You should be able to work with your graduate program to find a suitable resolution, either with office staff or the chair of the graduate program or someone they designate. There may also be something like a "first year advisory committee" that serves students before they assemble a formal thesis committee.
They may be able to bend rules, pressure faculty, access temporary funds to let you continue rotations into the fall or start in a lab, or at least help connect you with a position that makes the best sense for you. You do have a bit of responsibility to make some decisions and take actions for yourself, but in these difficult circumstances in particular you shouldn't be alone in doing so.
Of course, if your interests are more narrow than the opportunities, there might not be anything that can be done. It's not really a responsibility for a graduate program to match every student with exactly the lab they want. Ultimately you'll have to decide for yourself whether you can rediscover some passion in an area you didn't expect to be working in, no one else can make that decision for you. Good luck.


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How "deep" do I need to go with my citations?
For background, I'm working on my master's dissertation for a data science project regarding COVID and want to reference some background information about health disparities. I've done some academic writing before but mostly for classes which aren't anywhere near as demanding in terms of research and citation accuracy. I've been using the citation lists in existing articles to generate new sources to read since I know that in humanities, it's important to cite primary sources if possible (and I am assuming citing the source of a study tends to be better than citing a literature review, for example). However, one of the books I'm reading is somewhat tangential to my topic and still has studies referenced within that (according to the rule I set for myself) I would need to cite as well.
Is there a rule of thumb for when you can "cut off" your research notes and avoid adding sources that barely relate to your subject?

Research papers need not contain a comprehensive review of all of the literature plausibly related to their content - it's neither possible nor desirable.
While you should avoid "through citations" where you cite Jones et al for saying "Baker et al found", it's perfectly reasonable to cite review articles for their overall conclusions and summaries about an area of research.
Don't discuss content that is barely related to your subject, and then you won't need to cite any barely related sources for that discussion. If you find yourself going out on tangents, I'd start by organizing the introduction/discussion of your paper first. Think about what things you need to say to frame your paper and make this into an outline, then start fleshing out the statements in each section. If you start to venture outside your outline, you've probably gone too far and should reel it in.
It's difficult to summarize into general rules that will let you decide for each case whether a paper should be "in" or "out" of your reference list. My advice would be to a) read, read, read papers in your area. Get familiar with how other people do things, and b) consult your advisor. At the research level, you're beyond the undergraduate stage where you mostly write papers by yourself and then have an instructor grade you. You should be conversing back and forth with your advisor about the progress of your research, including writing.

Thanks! This addresses my concerns perfectly!


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Should I write an email to my potential supervisor before interviewing?
I've just got into the interview selection of PhD funded program. As I failed another university interview just a week ago, I am quite apprehensive about this upcoming one. As I've read about interviewing tips somewhere, some mentioned emailing potential supervisor and ask for advice for the imminent interview. Should I do this?

Yes, but do take time to read several papers published by your potential supervisor before writing that email. If the PhD is computer science related, also have a look at RefPerSys

If there are things you genuinely need to know (How long will the interview last? Do they want you to give a presentation? What sort of questions can you expect?) then an email query is sensible and should be well received. This may be particularly important if you're moving institutions/countries so norms will be different. But don't send an email for the sake of sending an email.

Thank you so much  for replying to my concern as it has been bugging me lately. As long as it relate to queries concerning the interview, do you reckon with would be reasonable. As my last interview, I found it was strange to see my potential supervisor didn't ask me much questions revolving around my project even though it is a funded project. I had the feeling she didn't like me much because the feedback demonstrate that my research ideas were not coherent enough


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My paper is unpublished, not novel and contains a mistake. How to list it in a CV?
For my master thesis, I worked on a topic that was new both for me, and my supervising professor. Because of that, we missed a well-known paper of our field, and I basically rediscovered the same idea.
We tried to publish it in two conferences, but it was rejected both times (unfortunately, no one pointed out that the work already existed, it was rejected because of too low impact according to the referees). Currently, it is published on arXiv. We are working on an updated version that includes a reference to the existing paper, and highlights that our results were discovered independently but are not novel.
To make matters worse, I also made a mistake in the central proof, so while the idea is correct, the conclusion needs to be weakened (that was done correctly in the original work).
Now, I am a Ph.D. student working for the same advisor. The paper has not been cited so far, but we will need to refer to it soon in a public report about a software we wrote, based on our technique. Also, my advisor is not in favor of taking down the paper entirely.
I felt bad about this for a while, but have come to terms with it now. While it is a bit embarrassing, I guess mistakes happen and there was no malintent. I am making up for it by doing an extensive literature review now, to avoid making the same mistake twice.
My question is about how to refer to this paper in my CV (or when presenting myself in general). I do have several other papers already, some of them in high-impact conferences with many citations (in a different sub-field). Currently, I have a section of my CV dedicated to those papers.
I'm not sure excluding the questionable paper is a good idea, because I don't want to make the impression that I'm trying to hide it. But I also want to make clear that I'm aware of the flaws, in a way that doesn't harm my overall appearance.
The general format of my list of publications is as follows:
[Paper title], [authors], [conference name], [acceptance rate], [number of citations]
 - Main contribution
 - Second contribution

I'm thinking about using something like this:
[Questionable paper title], [authors], non-peer reviewed (arXiv)
 - Independently discovered [known technique]

This would not hide the fact that it's known, but also doesn't put too much focus on the paper. Also, it doesn't stress the fact that it contains a mistake (that would be part of the updated arXiv version). Is this reasonable?
The question also extends to how to present myself to other researchers, when they ask me about prior publications in a less formal setting. My plan was to own up to it, and reply something along the lines of "For my master thesis I focused on improving [topic]. Unfortunately, I missed [known paper] and independently discovered the same results." (again, not focusing on the mistake I made).

Do you have an "expository papers" section in your CV? If yes, you can add it there -- while not quite expository, it is (once corrected and put into context) a similar beast.

Since you are still working on it and haven't abandoned it, it seems an obvious candidate for a "Work in Progress" section of your CV. Other current projects can be listed there also.
You don't really need to apologize, especially in the CV.

How would you describe the content of the paper? Still as "Independently discovered X", or differently? Or only give the title of the paper?
To clarify: The updated version will include the reference to the known paper, and a note that the results are too strong. I'm not sure we will actually redo the experiments, as that would be a lot of work and is probably not worth it. Future work will focus on actually novel ideas, and be published as its own paper.

And maybe as a follow up question: The paper will never be published at any conference, given that there's no new information in it. Once the paper is updated, should I move it back to the main list of papers, or drop it completely? It's not peer-reviewed, after all

@MissedKnownResult Maybe it's different in your field, but in mine a CV is just a list of papers, not annotated.

Is a description even necessary? If you need to say something, describe the project, not the paper. If you get enough results to replace it, or if you otherwise drop the project then either drop it from the CV or describe it as "replaced by ..." as appropriate.

@BryanKrause I'm in CS. I think giving just a list of papers is the norm there, too. I included short descriptions to give a very quick overview (and to stress the impact, given that I was applying to research roles as a master student, when usually a last-year Ph.D (or similar) was expected. Maybe now is a good time to go back to just using a list. It will also help to save some space.

Agree with @BryanKrause (as is often the case) that descriptions aren't needed in most situations. But, in an interview, it is fine to admit that an old project failed and was abandoned. That is the nature of research. And, for the time-limited research done for most MS degrees it isn't especially uncommon.

@MissedKnownResult If you're applying for positions that expect a degree you don't have then it's highly unlikely that formatting a CV differently than the norm will make up the gap.

@BryanKrause and Buffy, Thanks for the great feedback! I'll wait a bit before accepting the answer, but you gave me good advice. BryanKrause, maybe it worked despite and not because of the unusual formatting, but I did end up getting the internship I was applying for. Of cause, n=1 is no good basis to extrapolate for general advice.

It is always good to wait a bit before accepting. Note that you can also withdraw and assign an acceptance to another answer. See the help center for more: https://academia.stackexchange.com/help

There is also always the possibility of just not listing it at all. Your CV is meant to highlight the positives of your career. We don't list the rejected papers and proposals and other failures :-)

I agree with this (a lot). But the problem is that the paper is on arXiv already. I don't use that, but, IIRC, you can't withdraw a paper there. So, not listing is, which is fine, also requires you can have something to say about it if asked.

@buffy You can always replace it by a newer version that states that the original paper has been withdrawn. That said, I don't think anyone is really going to go out and do a literature search on a candidate when they have the full list of publications right in front of them!


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How to recommend an alternative journal in a (negative) referee report
I have been asked by a top journal in my field (mathematics) to referee a paper. The paper is very strong, but I feel that it falls slightly short of making the cut for this (very prestigious) journal. In fact I believe I would recommend acceptance of the paper if it was submitted to virtually any less prestigious journal. How would I go about communicating this sentiment in the report?
For example, I have thought about explicitly recommending some journals for the author to submit to.

I would say so directly in the report. I have done this in my reports and also had such reports of my own papers.

Can you be m9re explicit about why you feel the paper doesn't make the cut?  Is the research not impactful enough?

@ScottSeidman Does it matter? Probably answering that question would get too field-relevant for this question that is otherwise fine. This site has a habit of getting into too much inappropriate detail in math/CS since that represents if not the majority, the plurality of the uesrbase.

@AzorAhai-him- I would say that If you're going to suggest a strong paper is not right for a high profile journal, and you're wondering how to tell the author and/or  editor this, saying why is a step in the right direction.

@ScottSeidman Sure, anonymousx should tell the authors and editors why, but I thought you were asking them be more explicit to us.

Sounds like a positive referee report!

I suggest that you can say that to the editor, but not to the author. Alternatively, ask the editor whether they would object. Saying that the paper is nice but not sufficiently novel or whatever for this journal is fine (IMO), but less fine is naming other journals.
The author, if rejected, probably knows already that other journals exist and may have a plan without your prompting. Some authors just take a shot at the top, hoping for the best.
But your relationship with the editor and the publisher is also important.

Why not recommending other journals? I was thankful for such recommendations when my paper was rejected because it did not fit the scope of the journal I submitted to. Back then, I was not aware of all the recommended journals.

-1: recommending other journals in a referee report is fairly common, and I'm not aware of an editor having issues with it.

Can you elaborate a bit what you mean exactly? I really do not see how recommending other journals could cause issues with the editor or the publisher, especially in the field in question (math).

As either editor or author, I wouldn't mind you mentioning other journals if you think they're more appropriate. I would also be transparent and concrete about why you think the paper is not appropriate for the top journal. A rejection stating "this is a strong paper but not strong enough" can really burn if it feels arbitrary. You could look at the last 10 papers in the same field published by the journal. If they're all stronger than the current paper, the author will understand the rejection better.

And, yet, in my experience (as an author and as an editor) most quick opinions do not provide such an explanation.

True, I was assuming a full referee report.

You can simply suggest in the referee report to consider slightly lower category journals. But don't name any specific journal for example. I believe there is a downside in suggesting other "specific journals", because the other journals might not send the paper to the same referee(you) (unless otherwise) while the new referee might not find it enough interesting paper (there is a chance) which will end up with another rejection. The author will be upset. The best way to write "the work is something interesting that deserves to be documented somewhere but this journal is slightly higher ranked against the quality of the paper." Now it is the editorial decision to accept or reject the paper.

It is the editor's job and responsibility to assess the article's suitability to the journal. As a referee, you are supposed to help the editor by giving your expert technical opinion on the correctness and interest of the paper. You need not write that the paper "falls slightly short", and even less recommend other journals.

I am not sure if you work in mathematics, but this is explicitly false for many mathematics journals. I have been asked specifically by editors to give my opinion on whether the submitted paper should be published "in a top $n$ journal".

In academia, it is quite common that people ask you to do unethical or improper things. This is a mildly improper case of someone asking you to do what should be their own job. In this case, fortunately, there is no risk in not complying.

I concur with Stanley's comment. I have been explicitly asked about suitability to a journal by many different editors. And I have been recommended journals several times in papers of mine when refereed.

I agree with the sentiment of this answer. But referee vs editor duties are a matter of convention and subjective preference. "Falls slightly short" does feel to be splitting hairs a bit, but it's a subjective call to make. The editor could still choose freely to publish it, or reject it in the face of a positive review.


text:
What is the most appropriate structure for introduction/background/related work when there is a 'gap' between them?
My MSc thesis is a multidisciplinary secondary data analysis project (data science-related) and its aim is to answer a specific question on the specific secondary data. However, I struggle with the structure (mainly the order of concepts) of the introduction/background/related work parts.
For my project proposal, the literature review showed that the problem I am tackling is almost exclusively addressed in a specific way [let's call these: 'methods A' that includes a variety of similar methods from field A].
One of my 'key' papers suggests that problems like that can be addressed differently ['methods B' that includes a variety of similar methods from field B].
This problem in this dataset has not been addressed with the B methods, hence there is some gap in the literature.
Furthermore, methods from a different field can be implemented 'on top' of A or B methods but there is not enough work about this on these specific data ['methods AB+' from field C. To note, that A and B methods can both answer the same specific question and can partially provide the same answer as AB+, so you could say AB+ is a better, more advanced approach.
I have reasons to suggest a specific method from the B methods ('method B1' from field B) and a specific method from the AB+ methods ('method AB+1' from 'field C'). All named fields fall under discipline G and my project title is named after fields B and C.
So overall, you could say my project is based on a lack of work in existing literature for this dataset. While method B1 has been used in other similar approaches (instead of A methods), method AB+1 is quite new and there is not much work with it in general.
So, I understand that I need to:
explain all relevant concepts from field B and field C (overview and introduce relevant terms),
provide an in-depth examination of method B1 and method AB+1
However, what is the most appropriate order to link all these together?
For example, do I make use of the introduction to set the context for all these topics and present fields B and C in a separate chapter (such as background work) before literature review? Then my literature review highlights the lack of work and I go in-depth about method B1 and AB+1? Or do I discuss methods B1 and AB+1 in my 'Methodology/Methods' section?
Hope this is clear enough and appreciate any answer. Thanks

Welcome to Academia SE! Your question is very specific, and your making it generic ("methods A, B, etc.") makes it very abstract and rather hard to follow. Could you please explain why your advisor is not able to help you with this? This is typically what a master's thesis advisor would do.

Hello and thank you for your response. It's primarily a scheduling issue; I have a supervisory meeting in two weeks and wanted to get a head start. I need to prepare a large portion of this in the week following this meeting. If I can decide on a structure early on, it will make writing more efficient and easy (I have all the material I need, I just need to present it in an efficient way) - as well as allowing me to get more out of the meeting. However, tbh I'm not sure if I'll be able to get any structural advice.
Is there any advice you can give based on the above information?

Sorry, as I said, your question has so many particular details, yet you made it abstract and generic. So, it is hard for me to offer any advice.


text:
What is the best e-Ink device for academic paper reading and hand annotation?
Having just started my PhD, my academic paper reading and review has ramped up dramatically and so far I've tried the two predominant methods of doing so: on a laptop or with physically printed papers. I soon found both methods to have their respective pros and cons:

Laptop reading allows for highlighting and text annotations, which I can always easily return back to on different devices (e.g. by annotating the papers in Mendeley and syncing the Mendeley app across all my devices) without the need to maintain a physical copy of the paper I originally annotated. On the major downside, the eye-strain is significant to the point that I have to take regular breaks and consequently struggle to maintain focus.
Physical copies do away with the eye-strain and are more comfortable to annotate by hand (relative to using the mouse for highlighting and keyboard for added notes) but present organizational (Now where did I put that paper I marked with an important insight...?) and traveling challenges (I travel a lot and carrying a stack of papers with me is becoming less and less feasible).

Therefore I decided it is time to try and find a tablet/e-reader solution which incorporates the best of both worlds. Specifically, I would sort the features from most to least important as follows:

Eye-friendly reading experience supporting paper and textbook PDFs,
with low-latency writing for easy and natural highlighting and hand-written notes directly on the paper PDFs,
long-term and regular software support and
a device which would double as a classic e-reader for leisure-time reading, such as a Kindle (if I already have a PDF reader, why not also have an e-book reader in one device).

The first point brought me within the e-Ink device sphere and two major contenders cropped up: the reMarkable 2 and the Onyx Boox Note Air. However it seems pretty difficult to decide between the two; specifically:

reMarkable 2: while reportedly boasting very low latency and a great writing experience, several reviews have pointed out it becomes very laggy with large PDF files (so I am not certain if it can handle textbooks or even very long, ~30-page articles with plenty of figures), saves very large annotated PDFs (since apparently all the hand-annotations are saved as an added image layer on top of the original PDF), requires regular pen-tip replacements (which could get pricey on the long run) and is reportedly very limited as an e-reader.
Onyx Boox Note Air: while again reportedly having a low latency, containing powerful hardware (which should deal nicely with large files), and serving as an excellent e-Book reader (thanks to its Android OS which supports a variety of Google store apps), the writing feeling is supposed to be much poorer (like writing on glass, which I wonder how I would get used to) as well as serving as a full tablet - most people would consider this a perk, however I am quite happy with the narrow focus of the reMarkable; I am not looking for a standard tablet and believe all the added features (music, video, email, etc..) are not only redundant, but could also prove distracting.

Does anyone have any experience using the above two devices (or perhaps any other, better ones) for the purposes described above? Would such e-Ink devices even be a good long-term investment, or is the technology still in its infancy (meaning that the technological advancement could make these quite pricey devices obsolete in a couple year's time)?


text:
Changing Funding statement after acceptance
Does IEEE allow changing the Funding statement after the acceptance of the paper? (In particular, I am asking about IEEE transactions on nanotechnology.)

Probably best to ask them, and likely depends on where you're at in the process and what the change is.

Ask them, but in short: You are free to change typos, grammar errors, and things such as acknowledgments, funding statements, author addresses, etc, that have no bearing on the content of the paper.


text:
Not getting indexed by Google Scholar
Our journal is using the OJS system and has been online for more than 2 years. However, in the recent 6 months, GS stop to index any of our articles.
What we have tried :

Check the response of any of our article pages to make sure it is responded to 200
Change the domain
Evaluate the metadata to follow the gs guidelines.
As an information, our journal is included on the Google search engine

We also discuss it on the OJS forum and no one knows the answer since there is no member of the forum from the official GS staff.
Is there any person who can give us suggestions?
Is there any blacklist mechanism on GS that prevents us from getting indexed to GS?
Thank you for your support.

Closer voters: In my opinion, Academia.SE exists to answer questions like these.


text:
FOMO in PhD specialization
I recently graduated from my Master's program in theoretical physics. Throughout the program I did most of my coursework in high energy physics and did my thesis in the same. However, I also did courses on condensed matter physics. Right now I am considering to apply for PhD positions. But I am faced with intense fear of missing out as in, I have been interested in many areas of theoretical physics along with interdisciplinary areas such as biological physics, complex systems and modelling (did few projects while I was doing my Master's along with few colleagues/friends) and application of physics to areas like economics. My problem is that if I were to choose the hardcore theoretical physics side (which I will enjoy, no doubt) then I would be just a spectator on the research that goes on in the interdisciplinary side (I would like to be an active contributor). And vice-versa if I were to specialize my PhD in interdisciplinary fields such as complex systems, physics of biological systems etc. Has anyone gone through such a phase? If so how would you take care of this irrational fear, if I can say that?

I think you answer your own question. Think of writing your Master's thesis. There was probably a time in there where you focused on this and little else, but from what you where writing, you never considered this as giving up on the other areas. Your PhD will be the same. At a certain point in there you will need temporarily focus on your chosen topic to establish yourself as a competent researcher. But there is nothing stopping you from considering other topics whenever you find the time. A PhD in X does not disqualify you from doing research in Y.


text:
What does "You are the creator and an author for this paper. You have authored an accepted paper." mean in EDAS?
What does "You are the creator and an author for this paper. You have authored an accepted paper." mean in EDAS when the Status is still "Active (has manuscript)"?

Have you asked the journal production team? What do they say?

If you have sent multiple manuscripts to the same conference, this means you have at least one of them been accepted.


text:
What incentives do reviewers in top conferences have to reject or accept a paper properly?
What would be the consequences, for instance, if the reviewer just rejected/accepted whatever paper they got, with a trivial or even nonsensical justification for it? Does the reviewer avoid doing that solely out of concern with the conference's quality?

In addition to possible negative consequences: there is little benefit to a reviewer from acting as you describe. At most, they might be able to remove one or two 'rivals' from the conference. This is unlikely to have any long-term impact on anyone's career.

Talking about these top computer science conferences, it is also important to note that while the reviewers are anonymous to the authors, they (often) aren't anonymous to the area chairs and senior area chairs who make the final decisions. Reviewers are also aware of other reviewers' full names in some conferences.

When I've been a reviewer for a conference, every member of the program committee (usually a lot of people) could see all (usually 3) reviews for all the papers. So writing a dishonest review could really damage one's reputation.

In a word, reciprocity.

@EarlGrey-Did I unwittingly say something offensive? My meaning is simply that one should do as one wishes done to them, and we all want our work to be reviewed properly, therefore any review task should be done diligently by us. That is the reciprocity I refer to. Your reaction seems somewhat odd.

@AppliedAcademic, I read your remark as a sort of Golden Rule (to do unto others as you'd have them do to you), not as seems to have been (mis)read by EarlGray.

@paulgarrett- Thanks, its a relief to hear that. :)

I've been a program chair of an ACM conference before, and my take is that yes we sometimes do get reviewers who act this way. It's not a great look and it's a fraction of our total reviewer pool. Others have mentioned incentives, so here's what we've done (modelled off other conferences) with our bad reviewers:

Papers with one poorly-written review and two well-written reviews and that are borderline enough that we aren't sure (i.e. if the two well-written reviews disagree), we would tend to assign an extra reviewer.
There is a list prepared for the next PC team on all reviewers that wrote poorly-written reviews or for those who ghosted on their responsibilities, so they can be excluded.
Senior PC members and program chairs read these reviews. We're in the same field as these reviewers, so we now have a bad impression of their scholarly rigour and seriousness in exercising their responsibilities.

Some conferences have also started doing a "Best Reviewer" or recognition program for a handful of their most-dedicated reviewers. I think that's a good approach as some reviewers go above and beyond.

Positive incentives:

Building a positive reputation: This is especially relevant for early-career researchers (ECRs) who are not known by everybody in the field yet. ECRs that left a positive impression might be considered for future service roles and cooperative efforts. However, more senior researchers might still want to be perceived as being "good citizens" of the community.
Some conferences give out "best reviewer awards" - That is a nice token of recognition and CV entry.

Negative incentives:

Avoiding a negative reputation: Particularly poor reviews might lead to reputational damage, both for the reviewer and for the conference who let the poor review go through. Most people, to some extent, care about their reputation.

Hmmm. I once won such an award. And it was for rejecting a paper, actually.

@Buffy Rejecting a paper for the right reasons is a great service for the community!

@Buffy You... Shall not... Pass!

I just want to add that, in my experience, the reviewer (a senior researcher) usually delegates their assigned reviews to a junior researcher (usually PhD student) who will do the actual work. This way you have the incentive, building reputation, but without the downside of doing the actual work of writing a good review.

@AlexbGoode That's indeed a common practice, but I wouldn't go as far as saying that it's the default. There might also still be some work for quality assurance required, as to avoid poorly written reviews being submitted, which would lead to reputation damage.

They wouldn't be invited to participate in the future. Someone else would probably have to cover for them. But, beyond that, nothing is likely to happen other than a possible stain on their reputation. The program committee would see the results and they tend to be pretty connected in the field.
Reviewers tend, in my experience, to take reviewing quite seriously, both in an attempt to have a quality conference and to aid authors in improving papers.

There are no serious incentives here, people do this mostly for non-incentive based reasons.  If you see yourself as a responsible person who cares about your profession then you’ll do reviews and try to do the best job you can under the circumstances.  I’m not saying incentives never matter, but they’re not the only thing driving human behavior.

The main thing that prevents that is that reviewers usually self-select into the role.  There are a few cases where conferences require you to act as a reviewer if you are an author of a paper, but aside from that, if you don't want to do a review, you just don't do it.  Reviewers therefore tend to do reviews out of a desire for professional service more than anything else.  It would be extremely unusual for an academic to elect to act as a reviewer but then (intentionally) give a vapid or nonsensical review.  There is not any particularly effective incentive against this; it is just that there is no positive incentive to do it in the first place.

"extremely unsual" - that does not match with my experience. Even one-liner "reviews" of a manuscript submitted to a reputable journal indeed happen, and I would not say rarely. Why these reviewers volunteer to review is another question, to which I do not have an answer. I agree with your self-selection argument in general, though.

Due to the volume of submissions, many CS conferences now require all authors to agree to participate as reviewers when submitting a paper.

@GoodDeeds: Thanks --- I've edited to reflect that.

I think the question is wrong because it talks about "proper acceptance or rejection" as if proper were universally understood and agreed upon.
Instead of one universally agreed upon definition of proper, every conference can have its own understanding of proper and choose reviewers that mostly agree with the conference understanding.
You do not have to agree with the conference understanding, but if you disagree a lot then maybe you should choose a different conference.

Reading the whole question, OP seems to be asking about reviewers who don't make a genuine effort, not about reviewers who do make an effort but judge things differently to others.

Nobody has mentioned yet that a single reviewer doesn't make the final decision. At least in top Computer Science conferences, each paper is reviewed independently by at least three different reviewers, then there is a discussion and the final decision is made by someone above them in the hierarchy ("metareviewer, etc.").
So not only would a reviewer look bad trying this, it wouldn't even work. They would be ignored or overruled by the other participants in the review process.


text:
How to justify having very low undergraduate grades and very high master's grades?
I'm applying to computer science PhD programs in the US and I'm worried about how to justify my undergraduate grades. Some other aspects of my application are strong, so I believe I have a chance (see end of post). I'm not aiming at top 10 american schools, I'm exclusively going to try top 20 and top 30 american schools.
My average undergraduate grades are 7.4/10 and my average Master's grades are 9.5/10. I'm not from the US, but I've estimated the undergraduate grades would translate to approximately 2.8/4.0 GPA and the Master's to 4.0/4.0 GPA, but it depends on the scale and method used.
I attended different institutions for undergraduate and Master's, and I believe the grades in my undergraduate institution follow a distribution with a much lower average, but I have no way to prove that. I feel this way because I never met anyone with a final average grade above 9/10 while studying there, and grades above 8.5/10 in many courses were very rare. For instance, in one of the hardest courses, I got top 1 grade of the class with a 7.1/10. Besides, I didn't feel like I studied a whole lot more for my Master's than I did for my undergraduate, and yet I got way better grades in the former. Do grades tend to be inflated in computer science Master's programs? Anyway, I was wondering if there's any acceptable way of discussing this in my statement of purpose or some other part of the application.
I think other points of my application might compensate for the low grades: I have 3 strong letters of recommendation and 1 first-author paper accepted recently in a top conference in my field (in a year with a record low 15 % acceptance rate for 9000+ papers submitted), as well as some other research experience in minor projects.

this is where a good LoR can provide context to the raw transcript: so rather than justify this yourself, get someone else to justify it for you.

@tensors_are_4_engineers No, I'm not from France. I don't know if I was clear, but 8.5/10 is not the official max in my institution. Technically you could still get a 9 or 10 in one of the challenging courses, but this never happened according to my experience there. There were some less challenging courses where getting above 9 was not so rare, however, and I did get a few grades in the 9-10 range. So any individual 8.5 in a given course would have to be translated to a B or a 3.0 according to the usual scale for translating to GPA, as far as I understood.

@tensors_are_4_engineers Ah ok, thank you. Unfortunately, the other students' max grades are not officially released by the university. This is purely my anecdotal evidence from having talked to many other students about their grades.

Opinion only since I have not dealt with graduate admissions at the level you seek.
I don't think you can or should try to "justify" this.  You might note somewhere that your grades improved when you settled into your master's work.  I think it would be a mistake to discuss the grading standards at your undergraduate institution.
Your recent work and strong letters ought to carry the most weight with an admissions committee.


text:
I'm the 1st author of a paper in a top conference in my field, and even then my PhD application got rejected from 5 out of 6 programs, is this normal?
It got me so disappointed because I thought the publication experience was the most crucial part of the application, and, as far as I could tell, not that many students in the universities I applied to got 1st author papers in top conferences before starting their PhDs. The conference where I got my paper had an acceptance rate of less than 17 %, with more than 8k submitted papers, and also among the top 10 in my field for H5-index and top 5 for impact score. So I wonder if this sort of thing is normal, to get rejected with a strong publication.
My field is Computer Science, focusing on Artificial Intelligence, which is in notoriously high demand these days. Still, I didn't expect it to be so competitive that I wouldn't get at least another accept offer than the single one I got, which was from my least preferred option.
I applied in the US, and 3 of the universities that rejected me are in the top5-top10 range in the USNews ranking for grad programs in AI (https://www.usnews.com/best-graduate-schools/top-science-schools/artificial-intelligence-rankings), and also the other 2 that rejected me are in the top10-top25 range in this same ranking. The one university that accepted me is not in this ranking.
To be fair, other aspects of my application were a bit weak, I must admit, for instance, low GPA for undergrad (even though I got excellent GPA for my masters), didn't send GRE scores (it was optional for the last application cycle), and my previous universities are outside of the US and somewhat unknown internationally.

If you were applying to my department (mathematics, but I would guess computer science is similar), the letters of recommendation would be an important part of your application.

I would say it's normal, if what you say about everyone needing a top conference paper in order to apply.   Everyone will meet that requirement.   For example, students applying to top schools all (or most) have a high GPA.  That's the minimum requirement.  After that, acceptance is based on their extra curricular activities or/and letter of recommendations.

You answered your own Q at the end of your Q. Publications is just one (very important) component. Try taking the previous prelims of these places. Can you do that?

I applied my Ph.D. in the US 12 yrs ago, and it seemed easy during that time. People always said "Excellent undergrad GPA + good GRE + good coursework" is critical. My university even didn't care about if I had a master degree, because AD letter said master degree certificate is an optional document when checking in. So maybe you can consider taking GRE test??

Your experience is a unique feature of the AI field - at good departments, a top publication is not a major distinction point, but an entry ticket to even be considered! Relevant blog post

"I didn't expect it to be so competitive " well, you discovered that your field is way more competitive than you thought. At this point, you want to have an entrance point in the field. You have an acceptance rate of 1/6. Not bad, take it. (as per answer https://academia.stackexchange.com/a/185116/128758 ). Once you are "in", it will be easier to change place if things are not as good as expected (easier than now that you are outside academia, not easy in absolute terms)

What you find is that admission isn't based on one criterion alone, but it is a holistic process of looking at an applicant's entire file. This includes not just this one paper, but also your grades, prior research experience, the letters of recommendation, which university you have previously been at and how that university is perceived by others, and many other factors. You mention some of these aspects in your last paragraph, and those who have read your application must have considered these relevant in making their decision.
I think that that is also the right approach for making decisions. Your GPA is a cumulative achievement showing how you work over several years. A single paper, with a number of co-authors, is a noteworthy achievement but it only provides a relatively short-term perspective on your ability to work. It is of course a positive aspect of your application, but apparently was not enough to overrule other aspects.

Congratulations on being accepted. No, seriously. If you are about to start a PhD, and you have ambitions to go into academia, you need to come to terms with the fact that a large part of your professional life will now consist of sending applications for positions, grants, equipment, travel, tenure, promotions etc. If you are like most of us, the majority of your applications will be rejected. Most schemes in academia are highly competitive, with acceptance rates below 10%. Getting 1/6 with a less-than-stellar application means that the rest is good. Take the offer, and make the best of it.
To answer your question more directly: While a publication record is important in academia, it tends to be less important before you start your PhD. Whenever I've been on PhD hiring commitees, much more emphasis has been put on grades and recommendation letters than a possible publication record. Thing is: It is not really expected in most places that you have a publication record before starting your PhD, so if you have one, it is mostly just icing on the cake -- if there is no cake to begin with, you will not be hired even if you have several good publications.
And on a more personal note: I have on several occasions seen candidates with poor grades, and a handful of papers. In most cases they have given the impression of a weak candidate when interviewed. I should give the position to a candidate who will make a good PhD student, ie. take the courses and do well, and then do research. If you fail to convince me that you have somehow turned around, and now will start doing well in courses, I will not accept your application, regardless of how many publications you have. Also remember  this: I cannot know how much you really contributed to that publication. It could just be written by a former supervisor, who I am not hiring.

Thanks, but I am still struggling to decide whether I will stick to this university or not. MIght as well make another question just about this topic. The university seems to be very renowned, but not so much in my subfield.

Also, what's your field? I am guessing that for some fields, like Math and Physics, grades might be more important than extra-curricular achievements since these fields are way more developed and well established, and any substantial progress in them requires a strong theoretical basis, which is evidenced by grades. My impression was that for newer and fast-changing fields like CS, especially for AI (my subfield), grades would be a bit less meaningful, with extracurricular projects and research being more valuable.

The sign over my door indeed says "Physics", but in reality I am working at the intersection between physical chemistry and CS. YMMV of course, but my statement holds also for my more pure CS colleagues

And hey, good luck in either case!

It's been mentioned that the process is very competitive and a publication alone doesn't imply a strong overall application.
I would just add that PhD admissions are often about match to potential advisor research. It's not about whose application is most impressive, it's about who they want to do research with.
Your application may not have been read by the professors at those schools who are close to your interests. (Maybe you didn't signal well who you would like to work with.) Or you said you're interested in topic A, but your publication is more about topic B and professors who do A were not excited about your app. Etc.
Even more likely, the professors who share your interests might just not be hiring this year, or they may not exist at those institutions if your interests are niche.

I carefully researched the professors and dedicated an entire paragraph in each application to name 2-3 professors and describe their papers that sparked my interest and how I could improve that line of research. I didn't get into contact with those professors previously only because they stated on their web pages to not send any emails to them if you aren't a student at their uni, that instead, we should simply mention their names in the application.

@jonesy Naming names can go both ways; if you seem interested in working with 2-3 professors who aren't taking students this year, they aren't going to accept you because it would be a waste of everyone's time.

@jonesy that sounds like about as much as one can do.

I applied for MSc in Computer Science this year to 4 universities in Canada and got rejected from 3 of them (no decision yet from the fourth one). My GPA is 17.84 / 20, my last two years' GPA is 19.01 / 20 (sometimes the last two years' GPA is more important for universities in Canada), and I ranked 1st among 73 undergrad students. My IELTS score is 8.0 (less than 2% score 8.0 or higher in academic IELTS), and I have several projects and research in AI, image processing, and NLP (No publication, though).
There are a few problems; I guess because of covid in the past two years, many students decided to wait, and now that everything is going back to normal, they are all applying at the same time. Because one of the universities I applied to said they make all decisions by the end of April, mine didn't come, I emailed them, and they responded that since the number of applications was so much more than they expected (more than 1400) it took them a long time to make all the admission decisions.
Not to mention that the competition for computer science is unbelievable. Another problem is that, at least in Canada, no matter how much the faculty members say we don't make decisions and the admission committee will admit/reject you, they are the ones who make the final decisions. What is the problem with that? Try to contact them, send an email, and explain how much of a perfect match you are for their project/work/lab/research you get no response because when 1400 people pay more than 100$ and fill out a long form to apply, so much more will send an email, and your email will get lost.
When the number of applications is really high, they may automatically ignore a huge proportion of them. For example, the only weakness I see in my application is that I graduated from a 1200+ ranked university. Since they have so many applications, they might not even look at those who graduated from any university with a rank higher than 800. So no matter how much talented you are and how good your resume is, you don't even get a chance. Because let's be realistic, they are not going to review 1400 applications one by one, and this is just the MSc in Computer Science. Think about Ph.D. applications, bachelor's, and other programs in that faculty.

I'm a professor in ML/AI at a Canadian school that's probably roughly in the same caliber for AI as the #15-25 schools on the US News list. (I got my PhD at the #1 school on that list, but at a time when admissions in this area was far easier – I am quite confident I would not get in today with the application I sent in 2011. Even then, I was also rejected from some schools ranked far lower on that list than the one I went to.)
I don't have the numbers in front of me, but admissions rates in AI/ML are actually far worse than for CS grad programs in general: in my department, more than half of the applicants currently say they want to do broadly-AI topics, while even judging very generously as to who counts, under 1/5 of the professors are in that area.
It sounds like you have a first-author AAAI paper – congrats! This is definitely a positive signal that makes me pay more attention to an application. Depending on what area of AI you're talking about, though: "core ML" people like me tend to value AAAI papers significantly less than those from venues like NeurIPS, ICML, or maybe ICLR/AISTATS/UAI, all of which have higher numerical acceptance rates but whose average ML paper tends to be (in my opinion) of higher quality than the average AAAI ML paper. (This is not the case for other areas of AI, though, where AAAI is the premiere venue.)
But: you say you've already done a master's. Having a paper out of undergrad is definitely a distinction from many applicants who do get in (though not everyone agrees), but out of a master's, it's far more typical. (I would expect that most, though certainly not all, admits to top graduate programs who already have a master's will also already have a paper or two.) It's for sure a good thing, but not something that sets you super apart from the competition.
So, this leaves all the other factors that everyone is talking about. The middling GPA from not-well-known institutions certainly hurts. Maybe your reference letters weren't as positive as they could be, particularly if they're from people and/or a country that US schools don't know so well. Maybe the topic of the paper and/or what you wrote about in your statement is different enough from potential supervisors' interests that they have a hard time seeing themselves working with you.
Candidates who are "pretty good but not super-outstanding" can tend to have a hard time in admissions, since the strongest-on-paper applicants will tend to get a lot of offers, but advisors are wary of over-offering since then if too many students come they'll have to find a way to pay for them all.
(As you've mentioned elsewhere, it's highly unlikely you're going to get any specific feedback on that from anywhere.)
In any case: it is what it is. You can either go to the school you're not so thrilled about, or decide to do something else with the few years / rest of your life. The quality of the work you do in grad school is more important than where you do it, and though this will make things more challenging versus going to a top place, this is definitely not necessarily the end of your academic career or anything – plenty of excellent researchers went to lesser-known schools.

thank you, this answer was particularly helpful.

Rather than questioning your application and suitability, have you considered who your competitors are? In my experience of applying for and interviewing for a PhD I found that the position would frequently be offered to people who already knew and had worked with the supervisor(s). Advertising the PhD publicly is a funding requirement in a lot of cases. When I eventually did get accepted to a programme it was a result of contacting my future supervisor directly, then seeking funding. This is the case for many PhD students I have met. So, I do think it is normal to be rejected so often.

Unfortunately, most of the potential advisors I found stated on their personal web pages that students from outside their institutions shouldn't try contacting them and should only mention their names in the application if they were interested, so that's what I did.

Are you applying in the US? This sounds like a non-US application strategy.

Wow, I haven't seen that before. Have you asked for feedback about your application after being rejected? It might be helpful for future applications to find out why the other candidates had the upper hand.

@Dawn If you are asking me, in the case where I got accepted it was a non-US university. But I have previously formed contacts with potential supervisors in the US via email, prior to deciding not to go ahead with a PhD in the US.

@LouiseWilson I didn't, but I think it's unlikely I'd get good feedback. Only after many emails I managed to get a few schools to tell me if I was rejected or not after 1 month past the usual time frame for admission/rejection notification. The best feedback I got was from a professor from my top choice university that said my experience was "relevant", but that he "only had a few spots in his lab this year". Most CS programs are receiving more than 800 applications, with 10-20% acceptance rate, so it's unlikely they would have the time to provide personal feedback to everybody.

It's very normal.  Even if you had a stronger undergrad GPA and good GRE scores it would probably still be normal.
Congratulations on being accepted.  A single paper isn't going to do much for the acceptance committee.  If you'd like to go to a more prestigious school, then you should take the GRE, do very well, and reapply.

You should thank the admission committee for not admitting you to their PhD program. This is the sanest thing to do when no professor is interested in further supporting your advancement in the program after you get in.
I was admitted to a top 50 CS PhD program in the US without a pre-assigned advisor. After one year of futile search for a PhD advisor in the program, I could not find one and had to leave the program at the end of the first year, as department discontinued my funding. I was an international student coming from a poor country and it was impossible for me to afford the tuition and other costs.
During my study in the program, almost all faculty (around 14-15 people) relevant to my intended research field (very broadly AI/ML) did not even consider responding to my emails that inquires for positions in their labs. Note that these emails were sent after I gained admission and was officially a student in the program. I could only get polite rejections after graduate coordinator got involved in the process and asked faculty to reply to my emails. I did not lie or misrepresent my research interests, professors whom I am interested in working with etc. in my graduate school application. So at the first place, I should not have been admitted to that PhD program. From the day one, it was obvious that no relevant faculty was interested in my presence in that program.
In addition, my experiences with other students indicated that lots of communication happened between professors and students long before the admission process. Admittedly, some students were much better than I was in terms of research experience and publications; but some of them had no prior publications or a serious research experience, but had the same nationality with the professor. Probably, school factor, coming from the same culture and alma matter issues heavily influenced decisions of professors. Even during discussions with senior PhD students, some suggested not to even consider applying to (non-American born) Chinese professors' labs because they never admit non-Chinese students. Whether you consider it as a form of discrimination or having a better ability to evaluate students from your own culture, usually professor’s care more about sharing cultural values, nationality etc. Consequently, recommendations from their colleagues in their home country (India, China etc.) might overwrite unknown someone with a good publication record.
I suspect the program heavily needed a large number of cheap teaching assistants to compensate increasing undergraduate enrollment and my PhD admission was a disguise to cover up that demand and to exploit me as a teaching assistant, rather than seeing me as a research student. Otherwise, you do not admit a student that no professor wants to supervise. My firsthand experiences indicate that US PhD programs are no way fully meritocratic, but this is the image they present to the world. That's why you think that your publications should get you in.
I wish professors could openly say "do not apply if you are not from country X, school Y or race Z". This would allow both ends not to waste their times, but discrimination laws in US do not allow that so they had to revolve around it in other ways. It has to be projected as your inadequacy.

Interestingly, at the one place I mentioned that accepted me, I managed to contact and be assigned to a professor who is from my country and has a few more students from my country in his lab. This professor also mantained contact with my previous advisers, so it must have helped as well.

I recently helped screen AI/ML applications at one of the top-4. Unfortunately, having a publication is essentially a requirement, not a plus (this isn't necessarily true for non-AI or other universities). We were also told to expect more from masters students than undergraduates. For instance, my job was to narrow it to the top 10% (to be narrowed further by PIs) and I remember feeling very bad about having to reject a masters student with 2 good publications and good application package overall. PIs knowing the letter recommenders also helps a lot.
It's indeed harder for countries that do not encourage research from early on, as the US does and from lesser-known universities.
Having advised many undergrads while in grad school and talking with my PIs about this, some of the main criteria for choosing whether to go to grad school should be:

Do you want to be a grad student? If this answer depends on going to the top-4 (and not at least top-30), the answer is probably no.
Do you like AI so much more than other topics? The answer may be no, in which case going to related areas may give you a higher chance at cracking the top-4. Still, if you do not want to go to a non-top grad school I wouldn't do it.
Do you like an advisor at that university? There are plenty of great advisors outside the very top universities. He/she will be your main academic influence by far. Being at a top university just provides a larger safety net of alternative advisors, as well as more people to get advice/conversations from time to time.

I expected this level of competition for the top 5, which is why I didn't apply to any of them. What surprised me was how several other schools in lower rankings than that also didn't seem to care a lot about 1 strong research paper.

Sorry @jonesy, I had slightly misread where you had applied. To answer this particular question, the answer is that in AI there is an increasing distrust about the reliability of paper reviews. For professor applications (not grad school), PIs (at least in top unis) will read the paper themselves rather than check venues/citations. For grad school apps it's just too much work to read them.
What they can trust are recommendation letters by people they know and trust. Very often, that is the final deciding factor.

Consider treating your Ph.D. application as a job search process - which it is; you would be working as a junior researcher. You've just described to us how you applied to a bunch of universities as generic entities, with no prior contact with the potential employers. It's a bit like sending your CV to arbitrary companies, asking "Would you like to hire me for a junior position?" - Instead of going at it this way, you could have thought about potential subfields you are interested in, found some relevant academics working on that at a decent university, got in touch with them, and if it seems there might be mutual interest - then apply, or rather have them promote an application for your admission/employment.
(This is not to detract from the other valid and useful answers.)

I carefully researched the professors and dedicated an entire paragraph in each application to name 2-3 professors and describe their papers that sparked my interest and how I could improve that line of research. I didn't get in touch with those professors previously only because they stated on their web pages to not send any emails to them unless you are a student at their uni, saying that, instead, we should simply mention their names in the application.

@jonesy: That's super-weird to me... all the Professors I know recruit to a great extent through being contacted by potential advisees.

I read that previous contact is expected among European academics, perhaps it's not an American thing. Or it might also be my subfield that is in such high demand right now that the Professors simply can't find the time anymore to read emails from prospective students.

@jonesy It varies a ton, even between departments at the same university. Some have an "admissions committee", others let individual professors recruit students. My current dept is sort of a mix: there's a (more competitive) rotations program, but students can be directly admitted to a lab too.

As a professor with a paragraph like that on my website: in AI, we get a lot of cold emails from people who are for the most part fairly poor applicants, including even months after the application deadline. (I'm sure more-famous people at higher-ranked schools get even more.) If you have a specific research or personal connection to a potential advisor, it might be worth reaching out despite that instruction (and making that connection clear ideally in the subject line) – it can certainly help to have a specific connection, but you also risk annoying them.


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Can't decide what to place first, literature review or theoretical description? (Master Thesis in Computer Science and AI)
I am writing my master thesis in Computer Science and AI. I am very undecided about what to put on the first place, and changed my mind many times already. Because of that, I keep rewriting the contents to fit the structure.
I have read from multiple sources that literature review must come first, then the theoretical description, however it feels wrong to me. Because how could I talk about a series of works that involve many hard and specific concepts without first explaining them first? If I have to assume that the reader is familiar with the concept, why should I have a theoretical description then?
Or am I misunderstanding the purpose of these sections?

For a master's thesis, you should ask your advisor and do whatever they tell you to do. That is the practical correct answer. If you get advise from Academia SE but your advisor disagrees, then it is pointless.

@Tripartio Sure... i know. I have some communication issues at the moment with my advisor for now. I need to progress with my thesis until I can consult with him again. If later he asks me to change things it's fine. The problem is that for now this indecision is preventing me to progress. That is why I wanted some opinions.

What exactly do you mean by "theoretical description"? This is not a standard term. Do you have a concrete example of an article where you have seen either format? It is easier to ask the question if you can link to publicly available articles (e.g., on arxiv.org) that show the formats that you are asking about. And the exercise of finding concrete articles with the different formats could help you a lot in answering your own questions about which format makes sense.

Indeed.. Maybe should I say 'background'? Framework? Idk. Here I mean the section where I describe the theory necessary to understand the work. For instance as I work with CNNs (but this is not my contribution, ofc) I intend to briefly explain what they are. I see it as very different form the lit. review where I ll not talk about the paper who presented CNNs but rather about papers that used it to my very specific use-case. Does it make sense?

Yes, that is clearer. I have offered an answer along the lines of my comments here. Thomas Schwarz's answer is also pretty good.

The answer is partially based on the prevalent academic culture. Some places have very concise ideas how a thesis should be structured and some are much more free. In some places, it is some bureaucrat who checks your thesis for conformance to a given standard, in some places it is the thesis director, who might or might not have a certain scheme in mind, and in some places, anything that the committee agrees with is fine.
From the later perspective, a theoretical perspective in general, followed by a literature review, followed by a theoretical perspective more geared towards the problem at hand would be a nice enough scheme. The purpose of the literature review is to place your work in the context of the current state of the art, but also to show that you read what you were supposed to read (and understand).  If the literature review comes first, it is more than just an elaborated list of authors - result pairs, but includes putting the thesis in context, which is very similar to a "theoretical description".
Ultimately, a master thesis has usually a very limited audience for which you are writing. Most theses will be read just by the members of the committee or the rapporteurs, or whatever it is called. There are memorable exceptions to this such as a thesis that gets converted into a book or a famous paper, but these are still numerically exceptions. If possible, address your question to them.
TLTR: Not all theses follow a boiler plate and a generic scheme is not a good idea. However, academic customs vary, and some places insist on a given scheme. It is not worth your time and effort to fight that. But maybe you can ask your advisor.

Thank you for your relevant points. To be honest I got a bit surprised by your suggestion of general theoretical perspetive > literature review > specific theoretical perspective. Is it common place? It would make some sense in my case, since i need to describe some very specific concepts. But somehow looks a bit unorthodox to me.
I also know that many works prefer to explain concepts together with their references in the literature, but in my case I believe this would make a very disorganised result.

It seems to me that you are looking for a boiler plate for your thesis where you can fill in the points and are done with it. The writing process does not quite work like this. You can start out with a scheme and you will probably change it between versions of the thesis.

For a master's thesis, you should ask your advisor and do whatever they tell you to do. There are so many different standards and expectations that, practically, what it comes down to is that whatever the person who is going to approve or critique your thesis is the best approach to go with.
This is not a matter of "the advisor is always right"; rather, it is that there are many good choices and it comes down to preference rather than a single or even merely a best "right way" to do things. When it is a matter of preference, then it is always a good idea to go along with your advisor's preference to keep them happy.
However, if as you indicated in comments, it is not easy to get your advisor's immediate response on this question and you want to advance with your work, then I recommend that you carefully observe the structure of the articles that you are reading and then follow the patterns that strike you as clearest and most logical. You will likely find that there are many different patterns in practice, but as long as you follow a pattern that is already published, then you have some precedent to justify the pattern that makes the most sense to you. Moreover, if your advisor later questions your choice, you will have published work to refer to as a justification for your choice; your advisor would be more likely to consider your choice seriously and might even let you go ahead with your preference because of the precedent that you refer them to.

Thank you for your points. I think i came to a structure that at least looks decent to me. It helps me knowing that these rules are not so much set on stone and that I may be able to justify my choices later.


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Can I include subjects I self-studied in my CV when applying to graduate program?
I am going to apply for a graduate program that requires background in subjects A,B,C. I have not studied those in my uni.
I self-learned them. The application process starts next January. So I have no time to audit these courses or get a RL from a professor .. etc. How to include this in my CV. Is it meaningful?
I have a youtube channel where I solve online final exams and HWs for these courses from  other universities. Should I include the links on my CV? Or does it seem desperate?

Why haven't you studied those things formally?

They were not available at my uni.

My suspicion is that if your undergrad university doesn't even offer courses that your target university considers standard enough to think of as prerequisites for application, they will probably not view your educational background favorably.

The question I always find relevant in such cases is: do you have any proof that you studied those things? If yes, absolutely go for it.

You could mention your self-study in your statement of purpose.

Definitely do it; I had done more self-studies during my Bachelor than the course I took from my uni. formally, and I put all of them to my CV during the application process. I don't know whether they helped or not but I got into a school I wanted, so why not put them.

Yes, you can include them, but it is unlikely that they will count for much unless you get a chance to answer questions about it in an interview. The problem is that there is no real independent verification of what you have learned.
You need to ask yourself whether you have really learned as much as if you had taken a course under the guidance of a professor, with evaluation of your work and feedback on what you have done.  This is very hard to manage for self study.
If you have done research, with some output, based on your self study it would be good to focus on that as evidence that you know what you say you know.
But a section of the CV on self study, listing books you have studied from or online courses you have "taken" might be worth the effort.
Unlike a commenter here, I don't think that the SoP is a good place for such things. The SoP should be about your goals, not about your past. A very brief statement about how some online study has pushed you toward a goal would be fine, but spend the "words" of the SoP focused on the future.
But, if your undergraduate study is non standard then you want to write things in such a way as to get an interview in which you can be queried about what you really know. And, without letters of recommendation from professors it will be especially difficult.

Thank you. I have done research but in a different topic so, I am looking for my best bet, I understand that there are no guarantees but, I am looking for what I can do about it :)

Yes, it would be better to have some very-tangible evidence of your self-study, for example to have some faculty vouch for you... but, as we know, this is not always possible.
From a U.S. math perspective: simply tell the textbooks (with authors!) you've read, and on-line notes you've read, etc, without much further comment.
From my viewpoint, as a long-time admissions cte person for a grad math program in the U.S. at an R1, I do realize that not everyone has the opportunity to take formal classes ... Whether they do or not, the interest and initiative-taking that self-study demonstrates is a big plus in my assessment of people. Yes, being outside of the conformist milieu means that people will need a bit of time to get in sync with the styles and conventions... but I don't care much about that, in fact.

And what do you think if someone linked their youtube channel in the cv? I mean, I started this channel to give them some kind of verification or a proof since I can get no recommendation in the mean time, standard courses starts in Sept. and I will apply by Jan.

@Nadine, mmm, well, I don't like to get caught up in the whole youtube thing, for various reasons... Apart from that, it'd not have any impact on my current thinking. Maybe it should, but I don't know that yet... If you promote such a thing adequately in your explanation of it, I might look. True, it's an opportunity to make a more dramatic impact than dry old PDFs... Interesting idea...