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Set up to fail classes
The last two semesters I've had classes where I've met all prerequisites. Yet upon the second week or so (when its too late to drop) I realize the entire class is based off another class which was not a prereq. I think I'm a good student but I'm struggling so much with things the other students do with ease because they've already learned the material. I can't keep doing this every semester, its very discouraging and draining. How do I avoid this or what should I do? I could take the said "hidden prereq.", but this wouldn't help me this semester or the next. In fact, it would only help me in my last semester of undergrad; assuming it'd be helpful at all at that point. Is this common in grad school?
EDIT:
I am following my schools recommended academic plan to a T. We have a laid out course plan to take course A in semester 5, course B in semester 7, etc. I'm 2nd semester Junior, 6/8 overall. You can deviate but I have NOT done that (at least for the courses I'm complaining about). I have not changed majors, institutions, nothing weird. I'm honestly surprised this is not a common thing. To be specific, I'm taking Computational Astrophysics which requires an intro astro course and vector calc + differential equations. I've taken a recommended course in the past labeled as Math for scientists and engineers (also labeled as a continuation of vector calc + diff eq) yet it relied almost exclusively on linear algebra and we never once did a real world problem. I have not taken linear algebra, the only matrix related math I ever took was a brief intro in highschool. NOTE that this computational astro class is specifically for astrophysics majors (me) and the astrophysics curriculum excludes linear algebra and any classes which require it. In general, this course requires way more programming skills than I have learned from my courses, the teacher even said so, although I might manage as I have gained some experience with coding through research I've been doing. Classmates of mine who have taken the same classes are either cheating or dropping out of the class because of how ridiculous it is (they havent gained coding experience in research). I refuse to cheat though because I want to learn and it will help me in my research (also ethical reasons obviously). I state the last bit to show the severity and how I am actually one of the lucky ones (hopefully I dont eat my words and fail).
Thank you for the suggestions to narrow the question, I know its broad.

This seems very strange. Do I understand correctly that you are an undergrad taking undergrad classes? In this case, there is usually a pretty standard sequence of courses that most students follow -- you should probably talk to your advisor (or a trusted professor in your department) about what this sequence looks like.

I agree with @cag51 that this is very strange, and I suspect there is quite a bit of relevant background context missing. Rather than go through some examples I'm familiar with from math, physics, chemistry, economics, engineering, biology, geology, etc. that might be totally unrelated to your specific situation, perhaps you could describe one or two specific examples of a course in a specific field that have prerequisites A, B, C, etc. but in reality also require knowledge of X, Y, Z, etc.

I guess you should try to get the scoop a little better.  Don't just look at official requirements.  Get the inside dope.  On everything.  In life.  [All that said, I agree with Renfro.  You are not giving us the scoop on you, what subject, etc.]

What year are you in school, and does your university have an informative course numbering system? For example, my undergrad institution had 1000 level classes that were pretty basic, for freshmen and introductory courses in other majors. 2000 level classes typically built on 1000 level classes, and you took them either as a 2nd year or in your field as a 1st year, etc. If you were a 1st year student enrolling in a 3000 or 4000 class it might be possible but there also might be some assumptions about prereqs that weren't made explicit.

Please look at my edit.

"the astrophysics curriculum excludes linear algebra ". It what? I hope you mean until (slightly) later?

@Tobias Kildetoft There is a specific class to learn linear algebra, the explicitly written academic plan does not contain it. It is also not a prerequisite for any astro course (including this one).

That sounds absolutely absurd. How can one learn modern physics (which is a necessary part of astrophysics) without linear algebra?

It's common that the listed prerequisites do not necessarily encompass all the knowledge that is needed, or useful, to succeed in the class.  Sometimes this is sloppy design or laziness about updating the formal prereqs.  Sometimes it's because Course B needs only a small amount of material from Course A, so rather than make Course A prerequisite (which reduces students' scheduling flexibility), they assume that if necessary, the student can study this material on their own.  There are other possible reasons.
The professor will usually know what courses a "typical student" would have taken before this one, so they might assume that students know the material from those courses, even if they are not prereqs.  If you are following an unusual schedule, or changed majors, or transferred from another institution, this can lead to trouble.
So if you are in any of those situations, or otherwise suspect that this might be an issue, the best approach is to talk to the professor before you enroll in the course.  Tell them what courses you've taken, and ask if they think you have sufficient preparation for the course.  They might recommend that you wait and take some other specific courses first.  Or, they might suggest that you study certain topics on your own before the course starts.
However, it is also an important skill to be able to fill in gaps in your knowledge on the fly.  Comparing yourself to the other students is probably not useful.  But if you feel there are a lot of necessary things you don't know, make a plan for how you are going to learn them quickly.  The professor can usually help you with this.  Accept that you may feel you are behind for a while, but after a few iterations, you'll have confidence that you can catch up.
This is likely to continue to happen in grad school, perhaps more so.  In a graduate program, the students have usually come from a wide variety of different undergraduate programs.  Grad courses may assume knowledge that is often learned in undergrad programs, but any given student is almost sure to have some gaps.  Again, part of success in grad school will be learning to fill in those gaps for yourself.

Thanks, I can certainly fill the gaps but I'm just frustrated. Your comment gives me some more motivation and helps me see how I'll actually benefit from this inconvenience.

@J. Shakrin, if your teacher looks sane, consider sharing your observations. I teach a certain  class for several years, and when I started I tried to write down reasonable prerequisites. However, it is very possible that during these years teachers of those courses modified actual content so it isn't relevant anymore. Nobody is perfect.


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Accuracy issue on conference paper
I am working on improving an existing deep learning model which was published in last year A* conference. The code and datasets are made available on GitHub. When I ran them the accuracy was less than what they cited on paper I ran code 10 times answer changed a little(>1%) but the difference of cited score and actual scores are like( approx 5%). what should I report in my paper actual one or one I am getting
P.S: I tried contacting all the authors and also opened an issue on github repository of code

You should probably report both.

The first step when there is a discrepancy between the published work and attempts to reproduce the work is generally to email the authors. Let them know what is happening. Maybe there is a bug in the shared code or something about the initial conditions you are missing. Hopefully they will be able to help you resolve the issue. If not, you should probably publish both numbers and a statement that you could not reproduce their values.

source: Stack Exchange

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

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Do the Publication Retraction impact on Co-authors
I am a co-author of a retracted paper. It is very unfortunate for me. I just provided technical assistance in the experiment but the 1st author did some scientific misconduct and as a result, the article has been withdrawn by the corresponding author. I want to know how it is going to impact my career. I just helped with the experiment designing and completely unaware of the scientific misconduct by the 1st author and now I am suffering. Please suggest what to do. I want to stay in the same field of research. Hence, is it possible that my abilities will be judged by this retracted article?

" I want to know how it is going to impact my career": What point of your career are you in?

I am a PhD student now. I want to know that is it going to hamper my early research career? Eg: Post-doctoral application, early career research grants etc.

I am a senior Ph.D. student and my future area of research will remain the same. Is the retracted co-authored article going to affect my future application for postdoctoral positions?

Yes, it is possible that this will affect you unless you have a way to clearly distance yourself from the misconduct. Of course, if the retraction, etc. isn't especially public then it is possible no one will notice.
Being a student now is both a hinderance and a help. Since you are at the very beginning of your career you can likely validly claim that you were blindsided by superiors, being a bit naive yourself. You aren't expected to be as sophisticated as a professor would be.
On the other hand, I suspect that it is only in seeking your first position that you would need to deal seriously with it. Once you have your own position you are building your own reputation. But you will, likely, be questioned on it and need a good, complete, and valid response. But I suspect that if it is reasonable, then it would be accepted by most people/places.

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Final paper submission while NOT attending the conference
I'm the corresponding author of my accepted paper in a conference. I won't be able to attend the conference so one of the co-authors will attend and present the paper.
Now for the final paper submission, I have to make a full registration for the system to let me upload the final version.
Should I register and upload the final paper while I know I'm not going to attend? I know that only the corresponding author can submit the final version.
Is it possible to register and then somehow transfer my submission to my co-author who will be attending or he needs to make a separate registration?

The answer to this question seems completely dependent on the specific conference and their procedures...

What I did before for an IEEE conference is that I asked the presenting author to register for the conference and then I uploaded the Manuscript through my account using a code he recieved. He presented the paper. No issues, it's normal. Now depending on your conference,  it may be the same procedure and maybe not. So check with them. Cheers.

@Pioneer83 Thanks!

Mohammad, your co-author can attend the conference on your behalf, as he/she is also the part of that paper. However, it's better to contact the convenor/organizer of that conference. It depends upon their policies whether they allow it or not.

That may or may not be true, depending on the conference. Someone has to pay, most likely, and credentials may not be transferrable. Contact the conference, as you say.

This is highly conference-dependent, but in outline:

Look up and carefully read any instructions provided by the conference — check both in emails/other correspondence, and on their website.
If those instructions answer the question, great!
If they’re unclear, email the conference’s enquiries/contact address to ask for clarification.  (This is the most likely outcome, I guess.)
If they’re clear but you’ve ended up in a situation they don’t cover, perhaps due to an earlier mistake or a change of plans (e.g. if the corresponding author was supposed to be the presenting/attending author from the start), then email the conference’s enquiries/contact address, explaining the situation, apologising if appropriate, and asking what you should do now.


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Choosing the right selection about previously submitted a paper in a journal
I have submitted my paper in a journal a week ago. After one week the administrator returned  my paper and requested all the authors to associate their ORCID with their accounts and asked us to resubmit the paper.
During the resubmission, a question asked "Was this paper previously submitted to this journal?" and I chose "No" as I thought this not a revision or a final version.
Now I see that it got an entirely new ID and is awaiting again for a new ADM to be assigned. I'm not sure if I had chosen "Yes", the previous ID with a .R1 (probably) would have been assigned with the same ADM so probably I haven't needed to wait again for a new ADM assignment; however, it's not a revision.
Overall, did I choose the correct option? If no, what should I do now? I'm not sure if it's the right action to contact the journal regarding that.

If you had chosen "yes", then presumably the editorial management system would give you some options that eventually return your submission to the original editor who was handling it, who would see that they'd asked you to indicate ORCID IDs and you've done so. If you chose "no", this wouldn't happen and they would treat it as a fresh submission, which might mean your submission reaches a different editor. So the answer is no, you did not choose the right option.
That said, it's not a big problem. Your submission could very well reach the original editor anyway (because their specialty matches yours the best). Even if it doesn't, modern editorial management systems are capable of flagging duplicate submissions, which should catch your paper. The journal staff would then fix any problems for you.
Accordingly I suggest doing nothing. If you're concerned, you could also email the journal (use the desk editor's email, not the editor-in-chief's), and they should handle it for you if they didn't already notice it.

The weird thing is that I contacted the ADM and he told that I chose the "right" option!

@Mohammad: You could write an email reply saying that on your screen the options are arranged vertically rather than horizontally. But don't send the email.

@Dave What do you mean by vertically and horizontally?

@Mohammad: I misread your comment and thought you said "and he told me that I should choose the "right" option. Given this misreading, here's what I meant: If the choices are arranged horizontally, then a "left-right description" makes sense, and if the choices are arranged vertically, then an "up-down description" makes sense. My point was that the ADM's reply is so uninformative that I thought you might appreciate thinking about "returning the favor" (sarcasm intended) by pretending to completely misunderstand what you were told. But it seems this is not what what happened . . .

Often the journal submission system will have something like the following:

When the administrative staff send it back to you, your manuscript will usually show up in "submission sent back to author". Thus usually, you would edit this version of your submission. This generally avoids the issue of getting a new submission ID.
One minor procedural issue  would be if you submitted a "new manuscript" when you were meant to update the "submission sent back to author".
That said, there are a range of journal submission systems.
Most likely, it wont matter and the administrative assistants will let you know what they need.

Thanks. Next to my primary submission, it's written "a resubmission has been submitted (WITH THE NEW ID)". So as mentioned, I think the ADM (if the original guy is aware of that) figures that out.

Just to be clear, could you please let me know what that question exactly means? And in what cases should one select the "Yes" option. For example, if a paper gets rejected with encouragement to update and resubmit, should one select the "Yes" option in the next submission?


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Are not published workshop papers considered in similarity check for an extended journal paper?
I am going to submit my journal paper in 2 weeks. Besides, there is a workshop whose deadline is in a couple of days. I am going to submit a brief version of my potential journal paper (12 pages) in this workshop (4 pages).
In the workshop website it's mentioned that "Please note the papers will not be published in a proceedings but will be made available via this website."
Now I'm concerned about one thing. As the workshop papers will be made available via this website, I assume they will be considered in the similarity check for my extended journal paper submission.
Will not that cause my journal paper to be considered as plagiarism (or self-plagiarism)?

As to the question of (self) plagiarism you should cite one work in the other. I would guess that you cite the journal article in the conference submission. You can also cross cite, of course. That avoids the question of plagiarism (and self plagiarism) altogether.
But the other question is whether the journal publisher will consider the work as already published if you present it. If they have strict rules about original work, you might have an issue. The editor of the journal should be able to settle that for you.
Among other things, you can say in the conference submission as a footnote, that an extended version of this has been/will be published in Journal...

Thanks. What is "cross cite"?

Each paper cites the other. A bit rare but possible if they are written together.

Yeah, but actually I may not submit the journal in the time of workshop submission. Is that fine to cite the journal paper in the workshop as "Submitted" (since I'll definitely submit the journal version soon)?

Whatever is honest: submitted, in preparation, in review, ...

It could be detected by the softare, and depending on the requirements of the journal and/or the conference you could have the paper rejected by one or both venues.
In most disciplines, journals only accept submissions that are new and not previously published elsewhere in any form with the possible exception of papers based on MS/Ph.D. theses.  Journals that take this stance would typically consider "published on a website" as published.  The conference organizers are warning you that appearing on this website could be considered publication.
In some disciplines, it is more common for journals to allow for extended versions of shorter conference papers to be published later as journal papers.  However, there must be some significant expansion and rewriting of the paper and it is important to disclose the prior publication when you submit such a paper.
If the journal has a "must be original, not previously published" rule and they discover that you've broken that rule, your paper will be rejected and you may be blackballed from any future submission to that journal.
So, check the submission guidelines for both the journal and the conference before submitting your paper.  If the conference doesn't mind and the journal is willing to accept an extended conference paper then you should disclose that you've submitted a shorter version of the paper to the conference when you submit your extended version to the journal.

You need to check the policies of both the workshop and the journal. If those policies are not clear, then contact the workshop chair and journal editor or include a note with your submission explaining the situation up front.
There is a lot of variation in policies. Some journals won't allow anything like this, whereas others will accept papers that have already been published in conference proceedings. What you are planning is probably alright, but you need to check.

Just water it down for the conference.  Basically do a version of your slides.  Also all they (likely) need now for the meeting is your abstract.  Send that in and figure out paper later.


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Role of a Senior Editor
I have submitted a paper to one of the IEEE journals. I had to choose a Senior Editor.
What is the exact role of the Senior Editor? As far as I know, the Editor-in-Chief assigns an Associate Editor who determines the reviewers but not sure about the role of Senior Editor. [Whom do typically people refer to by just "Editor"?]
Also in my cover letter, by mistake I mentioned the name of my chosen SE instead of the EiC. Should I contact the journal to modify it or just wait for their response?

Different journals are set up differently. Some journals have an editor-in-chief who assigns an associate editor who assigns a member of the editorial board. Others have the journal office assign an editor who assigns the reviewers. Yet others could let the authors choose.
It sounds like you've submitted your paper to a journal using the last model. My guess would be that the chosen editor will be the one handling your paper (unless she declines). So don't worry about it and let the process run its course.
About the roles of all these editors, the word "editor" has many possible meanings and it's not really possible to tell without insider information what everyone does. Editor-in-chief is generally the highest-ranking position, and is responsible for everything published in the journal, but beyond that anything goes. "Managing editor", "Senior editor", "Consulting editor", "Assistant editor", etc - they could all be doing the same thing. It all depends on how the journal is set up.
Finally, about the salutation, I wouldn't worry about it. Chances are the SE will be reading your cover letter. If it's the EiC (or journal office) reading it instead, they're not likely to take offense.


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Love Courses, Hate Research?
I'm in the third year of my physics PhD, and although I have done very well in courses and passed the written candidacy exam, I have already switched research advisors twice and all three times I couldn't make myself productive in research. I'm planning on doing a Masters now but even that is taking some effort, and at this point I just want to leave.
I truly enjoy learning about physics, taking courses, solving problems, reading (good) papers, and the initial stages of learning the jargon and ideas of a sub-field, but after that when it comes down to business and I have to focus on the real research I'm supposed to be doing, I feel like all joy and curiosity I have towards the subject is sucked out of me.
To me physics is a very personal subject. It's an intellectual detour from work. It's like therapy to me. Give me paper, a pencil, and one good textbook introducing some ideas to play with and I'm like a kid on a playground.
Trying to make it into a career, however, means I'm not free to truly explore and examine topics. Any organic thought process or line of questioning I have is immediately crushed under the weight of the research I'm supposed to be doing and the judgement of my peers/advisor as to whether or not I'm just wasting time.
I went into a PhD solely because I really loved the physics courses I took in engineering, not because I had a career plan. Meanwhile most of my peers and professors treat courses like a nuisance that must be overcome to get credit and focus on the work that they really want to do.
I'm at a bit of a loss of what do for work now. My goal for an ideal living situation would be a modest but livable income at a relatively simple minded job that doesn't follow you home so I could spend some leisure hours studying and playing with ideas. However, it seems like most jobs that use my only assets of engineering and physics knowledge demand too much active attention to allow one put serious effort towards other pursuits simultaneously. Can anyone advise a good career path for this situation?

Interesting. At least for me, exploring and playing with ideas is research. However, you do have to bring them to a decent conclusion, which requires hard work and lots of questioning (preferably driven by oneself) if the conclusion is actually any good. Perpetually toying with ideas is not achieving anything in particular.

Right, but you don't just get free reign over ideas to play with. There are a ton of constraints with grants and peers that you need to introduce intermediate results to and explain every intuitive flight of imagination that you might not be able to clearly articulate at first.
I'd be much more comfortable being allowed to truly freely explore what I want and scrap what doesn't work without having to explain my thought process until I finally reach a conclusion I think is worth writing about.

You need solid intermediate results to know you are getting anywhere in particular. Why is it not fun to go in a direction somebody else cares about? Is it somehow less interesting than heading off in a random direction? What if you found out your random direction was important to somebody else - would you quit following it because of that?

It's not that somebody else cares about it, or that I want to go in a direction I see as completely random. I believe I have some intuition in some small scopes about which avenues of research will be fruitful and which ones will not. Those intuitions could be wrong, but it feels very unnatural to force myself to commit significant effort to research something I'm unsure or pessimistic for when I think I'm catching a glimpse of a better idea. I also think I require a large amount of time alone to process ideas, and having to touch base too often cuts that short.

You might want to specify your country, because PhD studies can be at least three to five years long and candidacy exams are foreign to many academic systems.

Consider teaching as a career. You don't have to do research then, but you do have to the understand the material. If you like learning about the material then this would suit you well; you might even be able to convey your love for the topic to future students.
Potential problem: chances you'll need an advanced degree to be able to teach at university level. With just a Bachelor's degree you can still teach at high school level and below.
Alternatively, consider publishing/science journalism. These two fields don't need you to do research too, but your output in both improve if you understand the material.
Potential problem: it's possible the physicists you'll be speaking to consider publishers a scam, and you by working in one are complicit in the scam. You'll have to decide for yourself if you can put up with that. Science journalism is relatively benign in this sense, but you'll be forced into confronting how something you find so wonderful, so interesting, and so amazing can be considered by others to be boring and pointless.

Regarding potential problems of teaching as a career, some universities offer teaching only positions

To add to this answer: Many professors also teach part of the time, because only researching 100% of the time can take lots of energy. But still, they keep something like 10-20% of their time for research (that can be together with a group of PhD students or alone in the office). Sometimes, this time they have for research is even fixed in the contract of a teaching professor. Of course that always depends on the country and university, but it is possible to do both without loosing motivation from doing one thing all the time.

Ignore the "must" and enjoy doing physics.
The worst that can happen is that you are going to enjoy the next couple of years, and then leave to take a decent position in the industry.
The focus on deliverables can be curiosity-crushing. Purely as a career, academic research is a poor choice: long hours, lots of competition, little pay compared to qualification. The real reward is figuring out how  the world works; don't forget that.
So, play with physics, enjoy; most likely nothing of public value comes out. However, if you do figure something out, do take the bother to write it up, maybe it is not that bad?!
An advisor's perspective: I want to add that the above is not the most common advice that doctoral advisors (myself included) give to their students. It is because the advisor does not get to share the fun, but has to deal with any negative consequences. Yet many of the somber professors that surround you did the same in their youth.

Right, but I don't even know if I can get away with that for the next couple of years. My advisor wants results, and my peers are similarly too focused on reading software documentation to get their simulations to work to engage in any "fun" ideas. I don't sense any passion or spark in them for the work they do, it's all just endless debates about dry technical issues. I suppose it's a sign of immaturity on my part but it also makes me constantly feel at odds with my advisor and peers. I'd much rather research for free with zero constraints.

Physics is a particularly special field in that it is extremely-old and there are many very old research niches that still continue. At the same time it can be super-broad, with physicists also doing research in very different fields that may be only analogous to physics problems, like network science and neuroscience. My guess is you simply haven't found a topic you like yet. Every area in physics was probably great fun to think about when it was brand new, but by this point research questions in many areas may be down to extremely-small increments that require a ton of work to get to in some sense (else they'd have been resolved already). I'd suggest seeking newer areas to work in.
Others have mentioned teaching as a career. However, in some ways teaching is farther from the enjoyment of taking courses than research is. In my opinion anyway. The goal of teaching is not to learn or to explore topics you like (we all push for those aspects as much as we can, but it's the tail trying to wag a dog). The goal is to get ideas that you understand thoroughly, through to someone less "smart" than yourself. And do figure out how to do it with some small fraction of the amount of time you'd like to use to address this challenge. Further, at the college level, the research schools, who's concern is overwhelmingly in hiring top researchers, not good teachers (ironically), have the best students. A more realistic job for someone who doesn't do research will be at a lower-ranked school with a mix of scholarship winners but also lots of  poorly-prepared/poorly-motivated students who can be far less fun to deal with.


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How do you find out if academia is the right path for you?
Apologies if this question is not entirely fitting for this Exchange, but I didn't know where else to ask.
I am currently working through my Masters, and while talking with one of my professors the question "Would you be interested in continuing with a PhD" came up. I have thought about this frequently over the last few months, but I can't seem to come to a proper answer. I believe the problem here lies in the fact that with a Bachelor or Masters you kind of know what you're getting into and what will be expected of you, while for a PhD it is kinda hard to find information (at least for me / in my country).
I have already gained some industry experience before coming back to University, and thus I know for certain that I would not like spending my life doing boring, repetitive office tasks; I plan on taking on as many extra-curricular activities during my Masters that can expose me to the 'department life', or at least give me a glimpse of what working in Academia is like.
However, despite all this, I keep coming back to the original question and not knowing what to think: Would a PhD hold my interest for however long it takes me to complete it? Would I enjoy working in Academia afterwards? What should I expect from a PhD in my field? Would I get one just to (possibly) be hired by a top-tier company doing cutting-edge/research work?
I don't know if I'm conveying my thought clearly here, but what I am trying to say is that there is virtually no information on what is expected of a PhD student, what Academia life is like and all this kind of stuff. How does one know if doing research would be a good fit for him/her if there's no prior exposure to this kind of work? Would I be good at teaching in case I decide to stay in Academia? How do I assess this?
I feel like there must be a way to clear my thoughts and get some answers before I decide to enroll in a multi-year PhD program and possibly waste years of my life leading up to nothing, having to fall back to an everyday industry job with less experience than someone of my age.
Again, I realise how general and convoluted this post is, and I won't mind deleting it if it is deemed unfit for this Exchange, but I'm honestly at a loss on where to go next and would like to hear opinions coming from people that are/have been in the field.
Thanks in advance for taking the time to read all of this!
As pointed out in guest's answer, I'm specifying that my field is STEM (Bachelors in CS, Masters in Data Science). You can read more details and my reply to his answer in the comment section, which might give a little bit of insight into what I initially wrote here.

Thanks for your welcoming message! I understand (and agree) with your point of view; If the powers-that-be of the Exchange deem it too opinion-based I will take it down promptly!

You will get a more helpful answer if you add the field you work in.  Perhaps leaving the question general, but "sneaking in" some info on your field.
I have worked in several industries and never been bored.  Certainly more routine jobs do exist.  But I would not exaggerate the stereotype of industry boring or even of academic research being exciting (it is not, always).  New products, initiatives, markets, etc give many private sector jobs plenty of excitement.
I urge you not to do the Ph.D. unless you see yourself as top 25-50% in your field (a higher percentage correlating to subjects with more industrial hiring of Ph.D.'s).  It is very important to realize that there is a glut of Ph.D.'s on the market.  At least in STEM, the number of doctoral slots is determined by the amount of (mostly federal) funding for research.  It is NOT determined by the number of high paying jobs needing graduates.  [I laugh at C&EN exhorting more kids to go into STEM in the same issue they talk about the intense competition at job fairs...and chemistry is actually better than math or physics.]
This is not to say don't do it. But go in with your eyes wide open.  At a minimum talk to kids looking for jobs in their final year.  (Or about advisor relations, thesis writing, etc.)  I do think the experience can be OK but you really need to look out for number 1.  Don't just do it because you don't know what you want to do, prof talked you into it, etc.  At a minimum, do a job search in parallel (you don't need to let each "side" know you are doing this).

Thanks for your answer. I'll try to address some of your points; 1) the field is STEM, CS specifically and a Masters in Data Science. 2) I didn' want to imply that industry is always boring, it was more of a personal reflection on my country's market and specific job I did (consulting) which to me was not fulfilling. However, when I did an internship abroad in a world-famous company I did find the experience very interesting and motivating. I believe here every company/team would be wildly different. 3) I do not see myself as a top-anything in my field and I think it would be foolish to (cont.

presume otherwise. I see myself as a diligent student but certainly not better than anyone else willing to put the work in. I've consistently been in the top percentage of my courses, but I feel like the pool of people to compare myself with is too small to draw meaningful conclusions when compared to the whole field (especially in CS, which is full of very smart people). I particularly appreciate your last paragraph, however that seems to apply only in cases where you expect to do your PhD in the same institution where you're doing your masters, or when you at least know people doing (cont.

a PhD where you would like to apply, which is not always the case (and most likely wouldn't be my case). I feel like the problem stands that hopeful PhD students don't really know what they're getting themselves into until well after they've made their choice, at which point it might be too late to back out (well, not too late since it's never too late IMHO, but still, could end up costing you a lot in term of industry experience and whatnot).

We are all trying to find a path, with limited information, and with no ability to do it over to try to " (at least in the Western religions).  https://en.wikipedia.org/wiki/The_Road_Not_Taken  Given what you have said so far (field, masters, ability, the two jobs), I recommend to work.  Try some different jobs.  Computers are an immense, still growing, industry (compare where we were 50 years ago).  Don't do a Ph.D. when you are half hearted about it.  And (Buffy will kill me), I think CS is a field where industry is much more relevant than academia.

If you do a Ph.D., the question to ask is, is the master's uni is different from bachelor's?  If different, I don't have a big issue with staying there (everything else equal).  If it is same, you need to move on to a new school, so you see different things (not all 3 degrees in same place).  Of course excepting personal family situations that drive location.

"I think CS is a field where industry is much more relevant than academia", I do agree with this statement but I don't really know if industry as a whole would be more fulfilling for me compared to academia (not that I have the means to compare the two right now). Here we fall back to the road not taken so point taken. Regarding Uni, no they are not the same (moved around quite a bit both for work and studies, don't really have a problem with the "seeing different things" mentality). I feel like however that a PhD leading up to Academia is fine in any university, when it's done with (cont.)

the hope of getting into industry after, though, the name of the institution/advisor plays a really big role in getting hired or not.

Maybe in CS.  My impression in a traditional hard science was more the opposite.  In any case, it's great that you have moved some and done some things.  "Salted veteran."  I would probably "peer down each forest path" (do a job search, now AND also look at Ph.D. school options).  I would definitely at least look around to other schools.  Not just "go with the one ya brought to the dance".  This is a convenient time to do it. Sorry...it's more work.  But (rationalization), I find you always learn something from a job visit or school application.

Good luck, man.  Sorry, I don't know if there is a canned perfect answer (and some of it is considering yourself, what you like, what you are good at).  But I am confident you are at least thinking about it well!

I am actually interviewing for a DataScience position in another continent right now, and got 'hired' for internal uni work under the supervision of a professor/his PhDs this semester. I feel like I am doing my best in exploring every option, I guess I'm just scared of committing to something without complete information, but oh well, nothing you can do about it I guess :) Don't worry, I know there's no 'correct' answer to a question such as this, and I thank you very much for the time you've taken in giving me your opinion!

No worries.  Keep pushing for insight!  (Come to the US.  It isn't perfect.  But it is still the land of opportunity.  Just so many options here.)

The position I'm interviewing for would be in NY, fingers crossed :)

You are going to have a blast in NYC.

The academic life is mostly about research and teaching. The balance between the two depends on where you work. At large research institutions, mostly research and advising grad students (researchers). At (usually) small teaching institutions, mostly teaching.
The only way, I think, to learn if it is a life for you is not to think about it, balancing out the various factors, but to actually try it. You are in a good position to do so if you take a PhD in most fields. You will mostly be involved in research, of course, but you can probably TA for a professor and get a taste of teaching. Initially the taste of teaching is pretty small, but advanced students are often offered to teach a course completely.
But if you start a program you can end your commitment at any time that you learn it isn't right for you. It probably isn't good psychologically to be too tentative about it, but it is a process that plays out.
Your attitude as expressed in your post seems particularly good for making a good go of it, with evaluation along the way (trying lots of things). I'd suggest that you are a candidate for success.
Contrary to another answer/comment here, while there may be a glut of people in STEM fields at the moment there is also, currently a massive hiring push in CS. I get many announcements every day.  And, as has been true in the past, today's glut can be tomorrow's dearth. Literally, tomorrow. And the reverse, of course.
Do what you want to do. Evaluate what you are doing. If it isn't right, do something different. Life is too short to leave opportunities unexplored.

I agree that the student seems strong (mentally and emotionally) and is capable of success in various arenas.  I disagree that the market rewards Ph.D.s in CS.  This article mentions the foregone income AS WELL as the on the job raises you get from experience.  http://www.pgbovine.net/practical-reason-to-pursue-PhD.htm  Really, I think the key thing is for Luca to find something that satisfies him.  This of course, is tricky.  However, even within CS, hard core academic jobs (e.g. R1 with good funding) are very hard to get.  "Tournament" is the term I hear used.

Thanks a lot for your answer! When you suggest trying it, do you mean going for a PhD and evaluating after actually experiencing the program? What I am quite scared of is trying it just to have to back out of it, which to me feels like a defeat (I unfortunately have a mentality where when I start something I try to push through it until the end). The professor I spoke with also told me that there might be chances to TA as a Masters student, which is something I should definitely explore more in depth since it would bring a better perspective to the whole situation.

CS industry is a hairy subject to touch IMHO, there's people grossly overpaid because they got in early, there's people underpaid (either by choice or forced by their market), there are researchers making millions in FAANG companies and others making a cent on the dollar in public institutions. I believe it comes down to luck & personal preference, regardless of any study on the market and income vs. years of experience/education. Might as well throw in that satisfaction is not necessarily the biggest paycheck :)

I think you would be better served to just start a doctorate. The research  experience will be better. You don't need to make a 7 year commitment on the first day.

@guest, frankly I think money is overrated as a life motivator. I started out not making a lot but ended up doing very well  as a CS prof and have a very healthy retirement account and expect to leave a pile of money to my kids. But that just happened. It was never a driver. But if money is your main thing then, no, academia probably isn't where you want to go. Banking and finance these days.

Try for a school, prof that gets you out in 4.  Not 7.  Maybe even 3, since you do have the master's.  Just watch out for these profs.  They need sla...students.  ;-)  But seriously, you did the masters.  And you are looking around now.  Do you really need to take a hike into the forest to evaluate the Ph.D. path?  P.s.s.  If you do start the program, I will advise you to finish it, once you are part way through.  A half done Ph.D. is as useless as a two-wheeled tricycle.

Buffy, you're a "tournament winner".  Not statistically representative.  Like Mick Jagger.

@guest, not true at all. My colleagues generally all succeeded and we were definitely NOT in one of the top US schools. We were happy with our reputation, locally, but kids in Kansas didn't grow up dreaming of coming to us.

OK. My bad.    @Buffy

But for comparison, I have a friend who always worked in industry. He is about my age and our careers tracked pretty well. I was  senior professor and he was something like a senior scientist at major companies. He always earned about twice what I did, but there was little difference in our actual lives because of it. And his career was also subject to the ups and downs of the economic cycle, just as mine was. Do what you love.

Thanks for all the insight, both of you. Regardless of your personal (differing) opinions, hearing people more experienced than me is always welcome and I'm sure will benefit me greatly when having to make my own decisions!


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From "editor assigned" to "editor invited"
A quick question about paper submissions. I have submitted my paper to a journal for a peer review. For 2 months the status was "Editor assigned" but changed a few days ago to "editor invited". What does that mean? Should it not generally be the other way round? I mean.. I expected an editor is firstly invited and then assigned after acceptance. Could someone shed me any light about this?
Edit: In What does the typical workflow of a journal look like? How should I interpret a particular submission status? there is a well detailed description of submission process however my question concerns a very specific situation. More precisely, in the first place it was not clear to me the difference between Invited editor and Assigned Editor. Admittedly, this is explained in the post above. However, the main point of my question is about the change of status: Why an editor had been assigned to my paper and, weeks later, the editor became invited? I would have expected the other way round as I explained above. Hence my question. Below there is an answer of some probable situation I have thought about but I preferred to ask here just to see whether other probable situations came out.

Why not just ask the journal?

@user438383 Thanks for the comment. I could ask to the journal, however I thought it was a ridiculous thing to ask..

@Nobody Thanks for your comment. However I don't see how it answers to my question. Might it happen that an editor accept the invitation and, after a few weeks, another editor is invited to handle my paper?

This is not a site for speculative answers. I don't know what the edit is trying to achieve. And I really don't understand what you will personally gain by knowing this. It will not make your paper be published faster. It will not even make your next paper be published faster, as the exact same situation will probably not happen again. Go and do what @user438383 suggested and ask the journal if you are so keen on knowing the reason.

Another potential duplicate target is My manuscript gets "with Editor" then "Editor invited", What is the main reasons for this? though I think the difference in "with Editor" duration favors Allure's answer here. Editage Insights offer some more potential reasons for Springer journals.

The most probable explanation is that the assigned editor is inactive and did not invite reviewers (which would also explain why you never saw the status change to "under review"). After two months the rest of the journal decided to invite a new editor, causing the status to move back to "editor invited".

This is a situation where the author is held unnecessarily hostage by the journal and frankly a waste of time. IMO, in theses cases of neglect and delay it is better to withdraw the submission and look for an other better journal to submit.


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Acceptable length for thesis defense presentation in mathematics
I'm a Masters' student in maths and it's close to my thesis oral defense. As such, I'm preparing my slides to present them. However, I'm feeling that my presentation has too many slides (albeit my equations are quite long as well), but at the same time I'm afraid of handwaving things too much if I omit some prrofs and such. To add more doubts, I watched a friend's defense and it was quite smooth, but later he told me there was 96 slides.
How do I decide if my thesis is getting too long? Is there some time metric (like time per slide) that can help? Is it OK if I omit the proofs of my theorems (and only mention the ideas of demonstrations while I'm talking)?
I saw some other questions and articles around, but I wanted some advice more related to mathematics, where rigorous proofs are expected and equations can get quite long.
Edit: It seems I have 45-60 minutes to present all the content, however I see fit (no presentation templates and such)

Which country? The norms vary widely, even within the same discipline.

How long should your presentation be?  Find out your institution’s instructions + guidelines!  We absolutely can’t answer this part for you; every institution will have its own timetable and expectations, and you must find out what those are and follow them.  How to find these?  You can try asking your advisor, asking the general co-ordinator for your department’s thesis presentations, and looking for instructions in the department’s website or handbook.
And for the subsequent question, how many slides?  This is just a part of a much bigger question: how to write and give a good presentation?  As you get experience of presenting, you’ll develop a personal style, and the rate of slides will be part of that, but just as a guideline to start with: a typical rate is one slide every 1–2 minutes.  Personally I prefer aiming for the slower end of that, one slide per 2 minutes (e.g. 12–15 slides for a half-hour presentation, allowing time for questions at the end); it forces you to keep the slides down to just the key points, not overloading the audience with more than they can read, and gives you time to expand on the slides with what you say in person.  Having too many slides, and too much on them, is a much more common problem than having too few slides.  But, again, finding a rate of slides that suits you is part of the bigger issue of finding a presentation style that suits you; and that’s a very big and fun problem to work on, but not one with a simple answer.

The norms for defences vary a lot between universities and sometimes even between different subfields within the same department (e.g., applied and pure math). Therefore only your supervisor or somebody else who is familiar with the customs of your department will be able to answer:

How much time you have.
Whether detailed proofs will be expected or not.
What you can expect your audience to know.

Given that you already attended a defence at your department, your guess is already better than what you can possibly get from the Internet.
As for the length of your talk, there is only one reliable way to find out: Test it, ideally with a human audience. If we knew your style and such, we might give you a minute-per-slide estimate, but a test talk is much more accurate and something you should do anyway. If any possible, get feedback from somebody from your group on your slides and also what you say.

Your advisor is the best source of an answer for this. I suspect you have something like an hour (maybe less) to present, followed by questions. You don't likely need to present details of any lemmas, but should outline proofs of main theorems. At least give a hint as to the direction someone would follow if they wanted to try to reproduce your work.
If you say too little, you will get more questions, so be prepared to fill in detail if you don't include it in the talk. But the ones who will judge your work are already experienced in your general area, so may not need as much detail as other people might if it is a public talk.
But the insights into your work are much more important than the detail, which can get quite pedantic.
But you can also do a trial run a few days before the talk, presenting your work to a toy duck or to a friend or two. In the latter case, you will get some feedback on it.

Thanks for the answer! Also, may I shorten propositions and theorems in the presentation, or should I show them as I wrote in the written thesis?

You make a considerable amount of assumptions that do not translate to every (math) department in the world. For example, I know at least one where defences were limited to half an hour and every decent mathematician should be able to follow them.

@Wrzlprmft, yes, the "hour" came more from thinking about doctoral defense presentations. The advisor will know the actual rules. I agree about "every decent..." at the MS level, but not thereafter. But if it is "insight driven" rather than detail driven, more people will be able to grasp the main thread.

@Buffy: At least at my alma mater, the rules for PhD were more or less the same: The talk should last one hour sharp and be addressed at a general audience of scientists from the field. Anyway, debating about this is mostly futile since for every reasonable combination of rules, you will find one department that uses them.

@Wrzlprmft, hence: ask the advisor.

@Buffy: Sure, but I would not even offer speculations on this.

I would aim for 30-45 minutes for oral presentation.  20 slides max.  Let the committee pick at it if they want--perhaps they don't want!  If they pick, just explicate, using the chalkboard.

If I try to fit everything into 20 slides, I'll only present the definitions and main results, and maybe one example. Every proof will only be mentioned, and no preliminary work (important but well-established results) will be shown. Isn't it handwaving too much?

If you are worried about cutting too much, put that material in an appendix just in case.

@AspiringMathematician: How much detail you can include isn’t limited by the number of slides; it’s limited by the time you have.  If you only have 30 minutes to present, then writing fifty slides packed with details won’t show more proofs — it’ll just make it harder for the audience to follow the key points.  Equally, experienced mathematicians in the audience will understand that there isn’t time to give detailed proofs of everything.  If you use your twenty slides well, to clearly present the main definitions and results, that can make an excellent talk.

In Finland you have 15 minutes, in Denmark an hour. "Aiming for" a generic number makes no sense without further information.


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No response after PhD interview
I had a face-to-face interview at a German University for a PhD position on Feb 12. The project is co-supervised by two professors. I was asked to prepare a presentation of my Master thesis for the interview. I was told that they invited only 4 out of 90+ applicants. It went okay and the sit-down interview after that went more or less fine. They seemed to value my enthusiasm while doubting my mathematical backgrounds. At the end of the interview, they asked me to send my transcript. I sent it the very next day (Feb 13) through email and got a reply from one of the professors on the same day that said they would soon be in touch with me regarding the position. However, I have not heard from them yet. I sent an email politely asking for an update last Friday (March 1) to one of the professors, but no reply again. Should I send an email to another professor? Or should I wait? Also, does it look like I am being refused? Any help would be good.
Thanks!

Wait.
You aren't refused until they say so. It may be that you aren't first in line, but you are certainly still in line. They have no advantage in stringing you along. But they may be waiting to hear from others. That can take a while.
The time has actually been very short. The institution probably has rules about contacting candidates other than officially.

Can I now send an email requesting the update of my status? I still have not gotten anything from them...

Certainly you can. But you will possibly only get an answer when they are ready to give it. But, after three weeks it is reasonable to be wondering about your status.

I just got an email from one of the professors. In short, I am their top choice for displaying "the highest scientific ambition," but they are not sure of my mathematical background to offer me the position. They also let me know that the position remains open.
Do you think I can make one more attempt at convincing them that I have good math training? Would it be helpful to tell them that I am willing to take online math courses to meet their requirements or ask them for an intern/assistant at their lab before the PhD studies?

Hard to say exactly. Thank the prof for their interest. Express your own continued interest and just note that you will continue to work on your math skills. I wouldn't mention online courses, etc. You don't want to sound desperate here.


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Will I get rejected because PI cannot show funding?
I applied to Cornell's College of Agriculture and Life Sciences for PhD program. I have talked with PI before submitting the application. I have 3.9 GPA from Master , 2 publications and one paper as the lead author under review in a great journal and plenty of research experiences. I think PI really likes me but, he said he doesn't have funding right now. He still asked me to apply for it and is willing to seek out funding options for me. I may be a very strong candidate as the program fits me, my background and future goals like a glove plus competitive academic profile. LORs will be excellent also. I am scared that I will get rejected because PI cannot show the funding this year. He recently got hired so, he is very active academically and applying for funding actively as well. What is the likelihood that I will get rejected? Any advice on anything that I can do?

Does this answer your question? How does the admissions process work for Ph.D. programs in the US, particularly for weak or borderline students? (Although you're clearly not a weak student, this is the closest fit to your question. Everything else is too specific, depends on your individual circumstances and is therefore off-topic.)

The answer to your question depends upon your specific advisor, the specific program, and your specific application and is thus off topic for the site. Also, the link from @henning--reinstateMonica will give you more information, although I do not think you're a weak student based upon your question details.

My brother was accepted to a history program without funding.  But as stated above, this would depend on nation, university, department, professor, your own scores, etc.

@JosephDoggie FWIW, My understanding is that history students are often not funded, whereas many (most?) science programs will not accept students without also a funding offer.

Thank you very much for your replies. @henning--reinstateMonica, Richard Erickson and josephDoggie. The link shared is informative even though it is not directly related to my situation.

@Richard Erickson:  In my own EE program I was accepted (I think, if I remember correctly, it's been 32 + years!) w/o any guarantee of funding, and that was a 'science' program (or engineering as in Electrical Engineering).  I did eventually get funding for most of the time.  My brother (history) did get some limited funding for part of the time also.

@JosephDoggie every program is different, but engineering is STEM, but not science. Many engineering students, especially at the MS-level are "professional" programs" and are often paid for by the student or the student's employer.

Actually, in the US it would be unlikely that your application would be rejected only for lack of funding. But you could well be accepted without funding if it comes to that and your background is strong enough.
In spite of it's association with Cornel, CALS is part of the New York State university system, so NYS rules apply to many things there.
But there may be other funding open to you than direct funding by the professor. You might be eligible for TA or RA employment. But you might also have to apply for that separately than for admission.
But work with the professor who will know all of your options.

Thanks for your thoughts. It is encouraging. I am also an international student so, almost all of the government funding options are closed for me. Yes, I will be working the professors to seek out fundings.

Wakanda suggests Africa. Cornell is in the not quite Arctic North. Beautiful place, though.

@Buffy, Wakanda is a fictional country located in Sub-Saharan Africa, created by Marvel Comics.

@StephanBranczyk, yes, I certainly know that. But it is also a trade partner of the US according to official sources. (reported on news on Dec 19, 2019). ;-)  https://www.bbc.com/news/world-us-canada-50849559

@Buffy, It's no longer a trade partner. Someone snitched on Wakanda and told the US government that it wasn't a real country.

haha.. thats not so relevant with topic but I like how you guys went off road. @Buffy i just like the movie.


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Is it important to do a PhD at a different institution than undergrad?
I'm currently studying at a good school and I was admitted to do a PhD here. I got into some other good schools for my PhD, but for various reasons (e.g. less of a good research fit, weather, etc.) I feel that my current school would remain the best fit for me for grad school. I feel very, very happy here every day and I am very interested in the research taking place here.
My advisor is pushing me to go somewhere else as he says it will allow me to grow and do better research. Other professors have more of an indifferent view of my choice and said that I can't go wrong when choosing among the schools.
Do you think staying here would be a mistake? Would staying at the same school be viewed as a negative when applying for research positions?

Feynman would suggest going somewhere else, but really, it is a personal choice.

Probably a small negative, yes, especially if you are not a top school. But doing less good work, regardless of reason, is a very large negative. If you are sure you will do better work at your current school, you should stay there. I admit I do find "weather" to be a strange reason, but "I feel very, very happy here every day" is an excellent reason. It also sounds like your undergrad and grad research advisors are different; so much the better.

Also related: PhD at same location as undergraduate?

Also related: Which is preferable, to go to graduate school at same school as undergrad or to go to a lower-ranked school?

@cag51 https://www.mayoclinic.org/diseases-conditions/seasonal-affective-disorder/symptoms-causes/syc-20364651 Not a strange reason.

If you like sun, you might like Singapore or Australia.  Good universities, and ridiculously sunny (Victoria and Tasmania not so much).

Thanks for clarification, makes sense. I think we're hesitant to "overrule" your advisor, since he knows the situation better than we do...but from what you describe, I would likely stay.

He used a lot of hyperbole which has made the decision seem dramatic.

We do not know this person, but it is possible that this is the professor's way of saying he wants you to change your plan for a reason he does not want to tell you.  Perhaps he thinks the PhD supervisor you are considering at your own institution is not suitable, and he does not want that professor to realise he thinks they are unsuitable.  So he is telling you indirectly.
Reflect on past advice this professor has given you.  Was it reliable?  Was it coded?  Ask more faculty for advice.  What do they tell you?  Ask your potential supervisors' former students what they think about the supervision they received.


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Effective reviewing in top tier Computer Science conferences
Most top conferences in Computer Science receive a record number of submissions every year, like AAAI received almost 9000 submissions this year, while CVPR 2020 received 6600 submissions. That would mean atleast 27000 and 20000 reviews respectively. That would mean almost 5000 and 4000 reviewers respectively, assuming 5 papers per reviewer.
I've also come across a few posts of area chairs (of these top-tier conferences) expressing their frustration of not getting reviews from the reviewers in time, and as a result there is a compromise on the quality of reviews. Is the burgeoning rise in ML/AI leading to falling standards? Is there an effective solution to this? Do such conferences have a way to check the quality of reviewers given that a lot of them are PhD students?
One criteria mentioned on their sites is that the reviewer should have 1-2 publications in such top-tier conferences, but is that enough? For instance, I have 3-4 publications (not in highly ranked conferences/journals), but I don't think I can provide effective reviews for papers submitted to those particular conferences/journals. Is there some additional criteria as well?

What are you asking? "Is there a solution"? "Do conferences check reviewers"? Or do you want to be a reviewer? Or "Are you good enough"?

I'm asking whether there is a compromise on the standard of reviews or not. If there is, because of the number, is there any solution to it? Do the conferences have a way to check the quality of reviewers? I gave my example to show my inadequacy, in reviewing papers where I have published work previously. I've edited the last part to make it more clear.

One frame check: decreasing quality of reviews is not necessarily the same as decreasing quality of accepted papers. Also, both mean and variance are relevant here.

I think you mean top papers will get through in any case. That may be true, but a fair number of papers would be on the fringe (http://blog.mrtz.org/2014/12/15/the-nips-experiment.html), and could go either way depending on the reviews. Also promising papers which couldn't make the cut don't really get a chance to improve. Constructive rejections/reviews can go along way in improving quality of research.


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Workload of PhD in US/Europe/Canada
I am a Masters student applying for PhD in computer science to various universities in the US/Europe/Canada. I wanted to know about the workload in general which we will have while pursuing it in these countries.
I did a bit of research here, and found that the teaching workload is highest in the US, followed by Canada and then Europe. In the US for the first two years we will be doing coursework majorly and working in different labs to find out what we want to work on, this time is lesser in Canada and Singapore, while in Europe we straightaway start working on the problem.
Any information would be very useful, specifically in teaching and in general. Thank you
In Singapore, NUS and NTU, in Canada the University of Toronto, the University of Alberta and McGill. In the US, CMU, University of Chicago and UNiversity of Minnesota
In Europe I'm specifically looking at colleges in the UK ( like the Imperial College of London, Oxford and UCL) and Switzerland (EPFL and ETH Zurich). Answers on any other university are welcome as well.

Teaching, supervising and organizing seminars are always helping to capture more research questions. However, I don't think it is suitable for PhD students to observe research problems, it is rather helpful for senior PhD students or postdocs.

Probably each and every institution will set their own limits... Contact the institutions directly and ask.

I think one the question: what are average teaching loads in PhD programs in [short list of countries] is a reasonable question for this site?  However, the actual answer varies wildly with the university and department, so this may not be helpful for you.  The more specific and precise your question can be, the better.

I'll narrow it down as far as I can at the moment

Should I narrow it down to a couple of universities or so only?  I was actually looking for a comparison between these universities, that is too broad?

I can provide some information about the US, and maybe a bit of perspective.
First note that the process of doctoral education is quite different in the US and parts (at least) of Europe. I'll focus mostly on things such as CS and mathematics. It may be different in other fields.
In the US, there is a relatively low bar for acceptance into a doctoral program. An undergraduate degree is all that is normally required, though some institutions may expect more. Not only that, but a four year undergrad program in the US is a generalist degree, not a specialist one. The "major" subject is between 1/3 and 1/2 of the total coursework and not every student is much exposed to research.
Moreover, most doctoral students in the US in these fields are, in a sense, self funded, as they are employed by the university mostly as TAs (sometimes RAs). Universities with doctoral programs in math and CS, also normally teach a lot of undergrad students, which means either lots of small classes or larger classes with lots of TAs. There aren't normally enough regular faculty to teach all of the courses, so they depend on doctoral students to help.
In Europe, I suspect that the bar is higher for entry, with more courses and research experience expected. I also suspect that doctoral education there is somewhat less dependent on student teachers and assistants. In some places, doctoral students are regular employees, and may, therefore, also be teachers.
But, I think you need to expect that no matter where you are, that doctoral education is a full time endeavor. You can "have a life" with outside interests, but your full time "job" is directed toward your degree. The exception would be for someone who can do a degree part time on their own funding. These are rare. And, I think that "full time" normally means more than 40 hours per week. Most people make sacrifices in that way and require that other family members are willing to accept that. It isn't so much that it is demanded of you, though it might be, but that research isn't a regularized process. There is no way to say that in X course I will achieve Y results. Insight is precious.
Whether the "time to degree" differs depends on how you measure it. From the end of a secondary education to a doctorate is likely about the same anywhere. There are things that need to be learned and research that needs to be done and reported. Whether you count that as part of a specialized undergraduate degree, or an MS degree, or doctoral education, matters little. Since the starting point is about the same, and the end point is about the same, there are few shortcuts.
So, what is best for you, depends on where you currently are. If you have the prerequisites done for specialized research, then you want a program that will let you get to it. Otherwise you want something that will help you reach that point.
I'll note, however, that, even in the US, if you are well prepared on entry, many doctoral programs will expedite your entry into research without a lot of course preliminaries. You need to pass exams and write a dissertation. You won't, most likely, be expected to repeat courses for which you are already well prepared, though you may need a way to demonstrate your competence. You will need funding, and, as an international student, few fellowships will be open to you. So you will probably be expected to teach or TA. If you are already an experienced teacher, you may have more advanced duties than most, but (student) visa restrictions can still get in the way.

Thank you, that was very useful. US Universities take undergrads directly, but when they are considering Masters' students for admission into a PhD programme, I think they would be expecting a minimum quality of research work done, is that right?

Not necessarily, or at least not a lot. Not every US master's has much research. Some do, of course. What you need is some evidence of preparedness to do research.

"In Europe, I suspect that the bar is higher for entry, with more courses and research experience expected" Many European PhDs have no courses. All coursework is wrapped up in the bachelor and master. The PhD consists only of research and teaching, as a paid employee. At least that is the case in the Netherlands.

@ElectronicToothpick A PhD student is not an employee in all European countries (France: yay, UK: nay, Spain: has been changing form model to model if I'm not mistaken). The coursework requirement also depends on the country and the programme. I had formal coursework requirements in France (some of which had to be non-STEM for a CS PhD); but they weren't strictly enforced (I got my language courses to count towards it though). Some UK PhD programmes also admit students directly from Bachelors and the newer CDT programmes have obligatory, enforced coursework in the first year.

Oh, and surprisingly, I've never had a teaching obligation in France (in fact, they make a distinction between teaching PhD students and non-teaching ones in their contracts), and I've had many other colleagues that had to do no teaching. I am still actively trying to make up for the lack of teaching experience, even though I missed out on it through no fault of my own. In the UK, teaching or not depends on your contract, as well as if you'll be paid for it or not (if teaching is listed as one of the things you have to do "in return" for your grant, then it is not paid, otherwise it is)

@penelope, I think you have the basis for an answer in these comments.

Possibly, but this is mostly about (first year) courses and teaching possibilities. I'm not sure I feel confident enough to comment on the workload in top-tier universities OP is asking about. I'm in a mid-ranked UK university right now, and my team actually puts great value in work-life balance (we still binge for deadlines, but this was the first time ever I was told to take an "unofficial day off" after a submission). I'm not sure I can realistically extrapolate info about workload in top-tier unies, like Oxbridge for the UK and EPFL and ETH for Switzerland, based on my expirience.

@penelope, you don't need to carry the whole load. Others can fill in as well.

@penelope Please do write an answer, this information is incredibly useful, especially coming from someone who is doing a PhD first-hand, I will be applying to universities in the top tier, mid-ranked and safe ones too, I specified them as a starting point because my initial question was too broad

I can provide an answer for the UK (Cambridge, Oxford - Doctoral Training Centres):

It is very competitive to get in (a degree with top marks from a well known university + a flaming recommendation letters + a paper from your BSc/MSc thesis (or thesis in a top lab) would usually get you an interview).
Once you are in you should be aware that doing a PhD (DPhil) in such
places is way beyond a "normal" job. It is more a philosophy and you
are basically married to your thesis project. And people do not mind putting insane working hours in as work and life merges. You will not hear a phrase like "Its 5 pm - time to go home". This is not because you can not go home (if you want to for some reason no one is going to stop you) but because you do not want to go home because you want to make the best out of the chance given to you.
This does however not mean that you will not have any free time. Top
places usually make sure that you have time to relax your mind and social activities are a big deal ("rowing teams" is a keyword here).
Teaching: It depends very much on your funding - between zero and few
hours per week (definitly not suffocating).


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Opening of applications for PhD in computer science at UCL,King's College London
I am a Master's student studying computer science in India. I will be applying for a PhD in computer science in the UK beginning in October 2020. UCL and King's college have not updated any details for the academic year 2020/21 yet, they still have the details of last year. Can someone provide some information as to when they open? Some sources say that PhD applications are processed on a rolling basis, i.e. as and when they come, they are passed on to the respective supervisor, and there are no deadlines per se.
Any information on scholarship deadlines would be immensely helpful. I'm referring to the UCL's GRS and ORS, and King's international PGR scholarships (the webpage seems to be down). It is recommended that one applies as soon as possible for the scholarships, but is it possible to apply some time later and still avail them? If say they start applications in December 2019, can i submit an application in February 2020 and still have a reasonable chance to avail those scholarships? I'm an overseas student, and as such a very few fully funded scholarships are available. If there is a lot of competition for those slots, then I think it would be better to apply as soon as they open, otherwise I'll wait for some time, so that I can improve my profile and have a better shot by applying a couple of months later.

Have you thought about asking UCL or KCL yourself?

I did, they said it would happen soon. I just need an approximate time, because i couldn't find a single month or date online. KCL says July is the last month for applying to an October start, that's about it.

Ask the universities your questions directly.

Generally speaking you should see applications for the upcoming year open in mid to late October in the UK. This allows the admissions offices and administration offices to deal with the students who have made a September or October start before the floodgates open again.
Regarding University-specific scholarships, you will gave to talk directly to the universities in question.


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Will an undergraduate math or economics degree better position me for a top economics PhD program?
I'm currently a rising sophomore (just wrapped up my first year) at a top US university, and time has come for me to start taking decisions about major classes, now that I'm done with required introductory classes. I don't really know what I want to do after college yet, but one possibility is definitely getting a PhD in economics, which is something that combines all my interests really well. At the same time, I'm very very interested in pure math as well. I've heard people say that your math education is more important than your economics education at the undergrad level if you're interested in going to grad school for econ. Is this true? Should I focus on taking the hardest math classes I can, or should I balance the hard math ones with the hard econ ones (though I'll admit that the math ones are generally considered to be way "harder"). Do I need an economics major at all, or is it sufficient to become as good at math as I can?

I took the liberty of changing your title a bit; people love to downvote/close questions that seem like personal choices, whereas you're really asking about the career implications of this decision.

Just pick up real analysis and the like on the side. The amount of math needed in a graduate econ course is not beyond what a good sophomore math major is learning. You don’t need four years of math to get to it.

But what if I want to major in pure math over econ? I really enjoy pure math (and so I’d love studying it for 4 years), but I honestly don’t see myself doing it as a career. So what I mean to ask is whether the additional 2 years of pure math (over just the 2 years’ worth of experience you’re saying is required) will make me a more competitive applicant.

Have econ grad school applicants typically done undergraduate research or learned how to program? If so, that could affect your choice.

Think about where you might like to go and look at their admission requirements/comments. Some want a substantial writing sample, one wants calculus, another wants probability, statistics, etc (advanced), and so on.

How about the non-mathematical parts of economics? Maths is a tool; do you need other stuff too?

I've heard people say that your math education is more important than your economics education at the undergrad level if you're interested in going to grad school for econ.  Is this true?

Yes, it is definitely true.  Almost everything in graduate level economics involves real analysis and optimisation conducted at quite a high level of proficiency.  Now, obviously there is a trade-off here, but generally students who come in with a solid mathematics education are at an advantage, even if this additional mathematical knowledge comes at the expense of an absence of previous exposure to economics.
One of the difficulties that most students encounter in graduate level economics courses is that they have to learn two things at once.  Most students struggle with the mathematics, and so they are trying to learn real analysis and various optimisation methods.  At the same time they are trying to learn the economic reasoning and intuition for the material they are studying.  Often the difficulty of the mathematics obscures economic understanding of the material, which creates learning problems.  If you are one of the lucky students who finds the mathematics easy, you will be able to turn all your brain-power to the task of understanding the economic principles and intuition of what you are being taught, and that is a major advantage.

At this point, I’m pretty certain that I’m going to do pure math as one of my majors. What I’m confused about is whether I should do an econ major along with it as well (which is very possible at the school I go to), or whether doing an econ major at the undergrad level doesn’t really help me. If I don’t do econ, I’ll have much more space to take harder math classes (maybe even grad level), stat, comp sci, and so on. Which of the two approaches would you recommend?

You should take enough Econ classes to get a recommendation from an Econ professor and to have some idea of what economics topics interest you for your statement of purpose.

Another advantage of doing some economics is that you will at least find out if it is a field that seems interesting to you.  Almost all the math for econ is either real analysis or statistical modelling.

Before you make a final decision, note that different economics doctoral programs in the US have a quite different focus. I think that U Chicago and Princeton, for example sort of exemplify the difference. Some programs are very heavy on modeling, in which case a math background might be useful. Others are not like that at all.
So, investigate the range of possibilities through their curricula and some papers that have come out of them to see what you want your focus to be. The two schools of thought are called "freshwater" and "saltwater", which might give you the basis for a search.
Outside the US it may be the same or not, but I can't help with that.

Both for US and outside of US, some maths classes are way more important than those of economics. But that does not certainly mean that you need a maths major, but means that you should absolutely have a notion in maths thinking. Other than that, those majored in engineering or maths can perform better in economics grad school as it relies very much on theory and modelling classes etc. but this is something you can achieve by having serious maths classes while doing an economics major too.
If I were you, I would take primarily core math classes for sure together with intermediate economics classes. Not mentioning Linear Algebra, Calculus, Real Analysis to name only a few along with their advanced versions. If time permits, you may also take graduate level economics courses to put them in your transcript as they strengthen your applications if you pursue a rigorous PhD programme in Economics.


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What does it take to be a researcher/professor at a top, top university?
I'm just an undergrad, so I'm not really asking this question for myself. This comes more from general curiosity. I know/know of several people who did PhDs from top universities (e.g. Princeton, MIT, Berkeley, etc) but could not go on to be hired by top universities. Many were hired by good and well known universities (e.g. University of Toronto or Haverford College), but not by the absolute cream of the crop.
Based on this, I wonder what it is that qualifies or differentiates someone to research and teach at the very finest universities (I'm thinking Harvard, Princeton, MIT, etc). What's the difference between Princeton PhDs who teach at Princeton/Harvard/etc and Princeton PhDs who teach at Haverford (again, no offence to Haverford - it's an excellent institution - just using it as an example of a school that's good but not quite up there with the New England schools and the likes)? Is it because the former have just engaged in far superior research (and write far better dissertations), or that they have been able to "network" more effectively in the academic community, or something else? What role does luck have to play, if any?

Here's a very similar (but perhaps unfortunately named) question: What does it take to get a tenure track position at an Ivy League School? I particularly like the point made in Anonymous Mathematician's answer about the numerical guarantee.

... so I’m not really asking this question for myself. “Asking for a friend”? ;-)

@DanRomik No. What I mean by not asking the question for myself is that I'm not even close to thinking about thinking about post-phd academia jobs, and so whatever answers I get here don't have any bearing on anything I do in my life (if I do decide to enter academia at some point in my life, I will surely not remember this thread so many years into the future). A genuine question out of curiosity based on something I've observed.

Also, can the downvotes explain? I don't see a reason to downvote a perfectly valid question, based on an observation which people do generally seem to agree with.

@gtoques no worries, it was a joke. I wouldn’t think poorly of you either way, whether you are asking for yourself, for a friend, out of curiosity or for any other reason.

I didn't downvote, but can see why people would think this not a good for for Academia.SE. What kind of answer would you consider "correct"? How would you objectively differentiate "superior research" from "networking"? What data are you expecting to see in response? Without objective data, this becomes a "primarily opinion-based" question, which is a reason for closing.

Yes the question is way too broad. It is like asking what makes a good son, a good ____ (insert profession). Too many qualities, across a board. A discussion about the selection criterias is more concrete and specific. It is also somewhat offensive, comparing different colleges as better and less than. Many very accomplished Ivy League professors prefer the smaller institutions due to the increased freedom and being able to connect with different communities as part of their work. Implying somesort of gradient denigrates this.

I think this is answered by Anonymous Mathematician's answer in the question linked by Anyon.

@Poidah, I have clearly mentioned that the places I refer to as "less than" (in your words) are just taken as examples of schools that are very good at what they do, but not considered to be at the level of Princeton, Harvard, etc. I completely understand that people might prefer smaller schools to bigger ones, but I don't think any argument can be made for the kind of schools I have referred to being "better" (or more competitive to get hired at) than top ivies and the likes. That's all I mean.

The same thing it takes to get hired at any place of employment: convincing the people at that institution that you’re a good fit for their organisation’s culture and strategic goals.