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Unsatisfactory research subject enforced by the advisor
For quite some time I'm doing research in a topic chosen by my advisor. The problem we are studying is difficult and important, with no good solutions available so far. I am currently unhappy about doing that. There are several issues here:

I feel that we are not making any real progress. Still, our advisor wants to continue with the project and write papers.
I think that the approach we are pursuing (invented by my advisor) is not useful at all. So far it has produced numerous difficulties, but no solutions in any nontrivial cases.
At the moment I'm writing a thesis about the subject. I am to describe my contributions to develop further the earlier work by my advisor. Due to lack of real progress, it will only contain complicated solutions to trivial problems. I think it's worthless. To be honest I'm embarassed by it and don't want to show it to anyone.
I feel bad about the fact that I never had any say in choosing the research and thesis topic.

I think these points make strong case for changing the research team after having finished the thesis. However

In general I do want to stay in the field in which my advisor is working in.
I feel changing would have a negative impact on my career.
I already changed once (after finishing bachelor's). I feel that doing it again after finishing master's would look unprofessional. I fear the impact on my status in the department would be negative.
Moving to different city seems like the best choice profesionally, but it is impossible due to family reasons.

Do you have any advice what should I do in this situation?

A great deal depends on (1) the country you are in, (2) the level you are at (MA or PhD), and (3) the field you are in ...

(1) In Central Europe (2) Currently writing MA thesis and about to start PhD program next year in the same institution (3) Physics

Dear colleague, there is no embarrassment at all in changing the field of study when you start a new degree. In fact I think that this is the time to do that, before you get too comfortable performing research on the same subject for several years. I know many theoretical physicists that worked on experimental physics during their master's degree. And more, I know a successful professor (his name is in the Higgs boson paper) that changed completely the field of study after several decades (from high energy physics to biological physics). Keep your mind open.

First there are two possibilities arising from your question that are worth entertaining:

Your supervisor, with greater experience, sees some hidden value that you miss in the work. You acknowledge that the problem is important and such research problems are not typically solved within the context of a Masters. So perhaps your supervisor views your topic as a stepping stone towards some other result, or perhaps they view it more as exploratory and something for you to "cut your teeth" on.
You are correct and the topic is not going to (even indirectly) produce useful results and, furthermore, should not have been given to you as a Masters topic.

If (1) is even a slight possibility still, talk to your supervisor and express your concerns as strongly as you consider appropriate given your relationship. Having such concerns should be taken as you caring about your topic and the impact of your work and your supervisor should work to address them, even if only to tell you that the topic was a long shot and it is becoming clear now that the results are negative.
Aside from this, assuming your masters topic is a bit worthless and you are quite sure that (2) is more the case: what to do? Look to the longer term. Since you are a masters student, this is not the end of the world. If you wish to do a PhD and are accepted for the program, my advice would be to put your focus into that. Working on a masters topic you are embarrassed by is a difficult pill to swallow, and in an ideal world one you would not have to swallow. But doing PhD's is rife with such difficulties for all but a lucky few. And it is worth noting that your professor is also human and one of the hardest challenges of academia is to come up with new, worthwhile research topics; furthermore, the nature of research is such that there are no guarantees that a topic that seems initially promising will fulfil that promise.
In summary, my advice is: Do what you need to do to complete your Masters thesis and then look to get the best start/topic/supervisor possible for your PhD.

Regarding embarrassment about the Masters topic, again assuming the topic really is worthless, there are three things to note:

Anyone whose opinion has value will understand in the context of a Masters thesis that probably the topic came from the professor, not you, and will understand the difficulties you faced.
If you continue to do a PhD and progress further onwards into academia, in a few years time, nobody is all that likely to read about or care your Masters thesis (unless, perhaps, the results were published as a research paper).
The standard expected for a Masters thesis varies wildly from institution to institution, but solving an important research problem is certainly not to be expected. (I mention this because perhaps you have set very high standards for your thesis.)

Aside from all that, even though your Masters topic has not been great, probably you have learned at lot from pursuing it (about the problem itself, the other work done in the area, how it could be done better, how to conduct and describe research, how to avoid a similar dead-end topic in future, etc.). The main result of yours Masters is you (and what you learnt), not your Masters. Your Masters is one or two years of research; it is a gateway to potentially decades more research on the topics of your own chosing.


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What courses should be included as "Course Highlight" in Resume for Master's application?
I am writing my resume to apply for master's in computer science. My question is, what courses should I include as "Course Highlights" at the bottom of my bachelor's degree?
A) Are the courses which I got great grades the candidates? But I have a lot of them fortunately!
B) Or should I include only the courses which are elective and important to my research interest?
C) Should I include a course, which is mandatory for my bachelor's degree as I guess, that I had a great grade, and is really important for the field? I mean Algorithms Design if anyone is familiar with computer science.
Thanks in advance

I hate to break it to you, but for 90% of computer scientists algorithm design courses are not remotely relevant to their life’s work, except for the purpose of passing poorly designed (but ubiquitous) interview exams.

I am in physics, not computer science, and things may vary by field. But in my experience, it's very unusual to see "course[work] highlights" in an undergraduate resume, unless you have taken courses that are (a) relevant to your application, and (b) not the typical required courses that every applicant has taken. In particular, this section is not about grades. If your grades are excellent, you should list your GPA (or "GPA in major") in the same section where you list your school, degree type, etc.

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Referring to a movie concept in Statement of purpose
I'm writing my statement of purpose for computer science master's program.
Can I refer to the concept of a movie that I have watched and kept me wondering and aroused my curiosity? I'm talking about Steven Spielberg's masterpiece, “Artificial Intelligence”. It really had a key role in motivating me to continue for postgraduate studies and research in the field.
Thank you in advance.

You "can" do what you want in a Statement of Purpose, but if you hope that this remark will inspire the committee, or show how inspired you are, it will likely miss the mark.
Generally, I have the impression that you may misunderstand what the Statement of Purpose is for - but you are not alone. From browsing Academia.SE, it is clear that the SOP is easily the most misunderstood part of the application package. I encourage you to browse through the questions here related to SOPs, and gauge how senior professors feel about it. Particularly, look at this excellent resource.
To summarize:
See it as a freeform document where you can document anything that is easy to miss in your CV or letters, or which may need further explanation. Do not see it as a place to sketch your "journey so far", discuss your lifelong dream to become a scientist, or explain how you feel the strong urge to change the world. See it from the perspective of a critical reviewer of your application and what they look for. Will them knowing how a Spielberg movie motivated you to pursue AI make you more likely to succeed in grad school? It's highly unlikely, so why would they care? Better to spend the short attention span that every application gets on what relevant previous research experience you had.

Thanks for the great link. I was wondering how to create an interesting introduction paragraph, instead of being boring and start right to the point. Am I willing to do it wrong?

@AmirMahdiNassiri Let me tell you a secret as somebody who recently looked at 250 PhD applications: it's not relevant if you write something "interesting" at the beginning. Nobody reads your statement carefully end-to-end, they glance over it for something that catches their eye. What fluffy text you write as first paragraph won't matter, people won't read it but instead browse the statement for hard information about you.

:D I really appreciate the true insight! So is it OK to start right away to the hard information? Do you suggest to bold out these kind of information?

The part where I agree is that nobody would read 250 applications end-to-end. But after filtering out the 245 less interesting ones, the 5 ones that remain may demand a closer look. There I'm not so sure if a short inspirational statement will universally come off as of the mark, provided that the hard facts are there as well. After all, some well-regarded researchers have such statements on their websites, too.

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Specialising in a field during a PhD at the expense of forgetting other areas
I'm having a crisis of confidence: I'm a 3rd year PhD focusing on cancer genetics. Whilst I am undoubtedly developing a deep and broad understanding of genetics, bioinformatics, somatic evolution...all that good stuff; I'm also finding that my understanding of basics is all but disappearing.
I don't use or "need" (practically speaking) a working knowledge of biochemistry or molecular biology to answer my research questions. Whilst during my undergrad I could describe cellular processes like translation, splicing, various cell signalling cascades in detail, I can barely summon the basics anymore. Since genetics, biochemistry, and molecular biology are so intimately related, I feel like drilling deep into one at the expense of the others is bad.
Is this something that other people experience? How do you find time to refresh the knowledge of areas that you 'should' know, even if you have no use for them anymore in your research?

Why do you thınk you should know them?

How long would it take you to relearn a topic if, for example, you were assigned to teach a course on it?

Maybe it's about time that you started teaching the undergraduate courses, or serving as a TA.  What you experienced is also true in other fields, and teaching is how it comes back to you.

@Joe, I think you're right, if I were teaching it then I would be constantly refreshing it. My issue is that in the UK PhD students are not allowed to teach undergrads, we are paid to study and the point of this is so we don't have any other jobs/responsibilities and can focus on research, as here a PhD must be completed within 4 years. I would probably take a week or so to remind myself of everything, maybe I should just start doing this over holidays.

Is this something that other people experience?

Yes, this is completely normal. Our memories get hazier over time, particularly if we don't make use of them. It is nothing to be worried about. We can't keep everything fresh in our minds at all times - as you learn new things, older topics get pushed to the sidelines and we may lose some of the detail.
However, memory is a complicated phenomenon, and just because you are having trouble accessing a memory doesn't mean that it's been completely overwritten. As @PatricianShanahan hints in a comment, I suspect you would find that if you had to re-learn some of these topics, it would come back to you surprisingly quickly. Partly because the memories are still hidden away somewhere, and partly because you will have been getting better and better at the process of learning itself.

How do you find time to refresh the knowledge of areas that you 'should' know, even if you have no use for them anymore in your research?

I don't think there is any particular need to force this process. The memories that fade the most are the ones that are being used the least, and there's a good reason for that: they are the ones that are less important to you.
General reading will help to keep memories fresh - it's always useful to read broadly around your subject. If you are worried about forgetting things because they are interesting to you then try to find some enjoyable reading on the subject - perhaps pop-science books, or magazines.


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Getting into a decent Ph.D. program with 3.3 GPA
Long story short, I was caught up in the party life in my early 20's and my GPA was a 2.5 when I came back to school. Since returning to school I have done a 180 with straight A's for two of my last 3 semesters. From my current school, my GPA is a 3.5. I have yet to take the GRE but I know I will have strong letters of recommendations from professors and one offered to turn my research design for our final into an independent study with me the summer before I apply for Ph.D. programs. My question is will GPA reflect too poorly on me with a high GRE, strong letters of recommendation and research experience?

Your last three semesters have been 4.0's?  That's something to explain in a cover letter; happens all the time.


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Am I graduate student or underpaid employee?
I started graduate course in a national research institute abroad (3 years ago). I just realized now this is my third year and every year we had different projects.
Main problem is that I am not having enough time to focus in one area to publish papers.  Second problem is that I am not obtaining knowledge from the other doctors.
Should I stop pursuing PhD if I feel I am not learning as much as I expected and feeling I am doing someone else work and tasks?

Are you working toward a PhD, or do you already have one? In the former case, you should have a thesis -- are you making progress on that at least?

Right I should have already started writing it but haven't yet, I don't have real advisor  either. Maybe change to master course and try to finish it. Really messy program

You need a path to completion. This means identifying an advisor, a topic, a schedule, etc. I think it's worth taking the time to really try to identify a path before giving up -- but if there is no path, better to recognize this now so you can cut your losses. In this case, switching to a master's and then doing your PhD somewhere else (or not pursuing a PhD at all) could make sense -- it all depends on what you want to do long-term, we can't make your decision for you.
Focus on publishing in the meantime. If you publish lots of interesting papers, you'll have more options no matter what you decide to do next. Fix yourself a set budget (e.g., 20-30 hours per week) for all tasks other than papers and thesis-related research and don't exceed that.

The downside of academia that you are describing definitely exists.  Have been hearing this for generations now (don't get me started on the pyramid, tournament style rewards, job prospects, etc.).
All that said, it is irrelevant to you.  Do NOT cut your nose off to spite yourself.  You are too close now.  Just buckle down and finish and get the degree.  It is helpful. And you will kick yourself if you miss it.
Be a little selfish about taking care of yourself on papers, etc.  Focus, focus, focus.  Pick your spots,  but I would avoid volunteering always and also occasionally push back on collateral duties.  And push, push, push for papers.  They really are the score card...don't let anyone kid you the opposite.

+1 for point #3...make time for papers, find time (or not) for everything else

At my university, there are some programs that have the students work on projects full time for 2-3 years and then having reduced workload for the other 2-3 years, to write a thesis. This way, the PhD student basically acquires his own funding.
Thus, at least when you are in such a program, it is not uncommon to not have a topic to work on, nor time for papers or anything, in the first few years. Of course if this is the case, it should be made clear, and you should be told (if possible, in your contract) when you will get time and advision (is this a word? No? too bad...) for your thesis.

It's a false dichotomy.
A researcher is always a student: S/he studies problems and questions - both through his/her own reflection and experimentation and that of others. Less-qualified students, earlier in their life, study mostly, or only, through the previous studies of others, shared with them.
Also, a person doing research or teaching a university, whose goal as an institution is to conduct research and to teach, is generally a part of its staff. The question of recognition of the university and the graduate researcher or teacher's employment relationship is, however, a highly contentious matter - since it is financially useful for university management to underpay and mistreat graduate researchers and teachers.
Every workplace - when you're there at least partially due to preference - has parts of the work that you're personally invested in carrying out, and parts that you aren't. A Ph.D. should be flexible enough to allow for a large  part of your work to be of the first kind. If it isn't, then you should try to change this state of affairs within the scope of your Ph.D., before considering leaving it in the middle.
Also, what @cag51 said.

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How to list an old manuscript on my CV/website?
A while ago, I wrote a short paper and posted it on arxiv.
My paper contains an observation that some idea in another paper can be used to give an alternative proof of some other result. I like the paper and other researchers have responded positively to it. However, since it neither contains a new result nor a new idea, the paper isn't really suitable for the usual publication channels. Thus I have not published it in the conference or journal sense.
I'm quite happy to just leave the paper as an arxiv preprint and not go through the publication process. However, I'm currently applying for jobs and I think that it looks odd on my CV/website. I list it under "Manuscripts" but that feels out of place, as all the other papers listed there are recent and most are currently in submission. It is "published" in the literal sense of being publicly available, but I don't think it's right to list it under "Publications" either.
How should I list this old arxiv preprint on my CV and website, if I have not "properly" published it and don't intend to?
Of course, one resolution to this is to find somewhere to publish it. But I feel like that is a waste of time (and also too late for the current job cycle).

Papers on Arxiv are not peer-reviewed. So they should not be represented as such in a CV. Does a publication on arXiv count as an actual publication?

Just put it in an "unpublished" or "other" section of your publications.

A section just for one paper?

Sure. Why not? Everybody's CV has a section with just one paper, at some point in their life.

To list such thing as a "preprint" is also quite a common practice despite the fact that, technically speaking, it is an abuse of language.


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Converting Web of Science ID to pubmed or DOI
I have downloaded a set of articles from Web of Science using their API.
Each article contains its WOS (web of science ID), but the entries for the DOI identifier are incomplete (i.e., not all articles have a DOI).
Is there a way to convert the WOS number to get the DOI or PubMed ID for each article?

Did you try uploading these articles in a reference manager program such as Zotero. If I remember well it can fetch data based on WOS and will then return all other known IDs, such as DOI/pubmed/etc...

That's a good idea, but I'm not sure whether I can simply import the data that I obtain using the web of science API. Do you think there might be a way to do that?

You can manually put parts of the citation into https://search.crossref.org/ and it will give you back the doi.
Alternatively, you could migrate your WOS bibliography into Mendeley using the steps in this video https://www.youtube.com/watch?v=FqtAPRZaz2U . I just started using Mendeley (by Elsevier) and have imported my EndNote references pretty easily. I was able to then find the missing PMIDs for a paper I was writing.
Good luck!


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How much time does it take to get a release letter from a university?
I got in to university A for the Fall, but now I want to go to university B. April 15 has passed which means I need a release letter from university A. University B will accept me if I get this release letter.
In your experience, how much time could it take to get this release letter? I need to know this because university B has given me a deadline.

I don't think anybody here in this site would know the exact time. But, my best guess would be a week at least.

I think it`s better to ask them about the time! Or even ask responsible department/ person about this letter. If he does not answer in 2-3 days, send him something like:
"Dear Professor ... , Sorry for bothering you, I just want to check if you had a chance to read my e-mail about ...? I would appreciate if you reply
Best regards, ... "
It really helps!!

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Disappointing advisor for stupid reason
I am a first year PhD student in computational physics in Germany working for some old big name in the field, which means that, of course, I never see him and he's not really my advisor and instead I work for one of his group leaders who is great and I love him.
Anyways, I was under the impression that I was doing great. Most students don't publish in their first year and I am already in the process of doing so because my advisor really liked my results.
Somehow he forgot about my progress and started tracking attendance of zoom conferences to see if I was there. It happened that he didn't find me on these zoom meetings, some of which I actually attended, but this made him really disappointed and now thinks I don't know anything about the field and don't read the literature.
My advisor wanted me to plan a talk for the conference but now he's so disappointed that he doesn't even want to read my abstract because I wasn't at all of these meetings. He of course doesn't tell me in person, he just tells the group leader, which is the person I actually see.
So now I'm working for someone that doesn't believe in me, and maybe wont want to read my papers anyway. It's very depressing and I don't believe I'm being treated fairly.
Some of these talks I didn't go to was because there was no zoom link, or the papers are already published and I had already read them, or they're giving the same talk in several months at a conference I am attending. Not only that but there is always the argument that your time is better spent working than watching talks.
Any opinions? I feel micromanaged and treated by an irrational tyrant. He also seems to forget my results which he was very happy about.
Thank you!

One solution is obvious. Attend all the zoom meetings. Ask questions there so your attendance is obvious. Even if you don't get much out of it, your advisor thinks they are important.
The other possible solution is to ask the "group leader" to stand up for you with the advisor. At least ask them for advice after explaining the situation.


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Visiting professor's office before being admitted to PhD program?
I have applied to graduate school (EE) and am currently at one of the schools to which I applied to. Is it a bad move if I go to a professor's office and express my interest to work with her, and show her my relevant skills?
Why I think this is a good idea:
I am an engineering physics major applying to electrical engineering. I applied to the niche areas of EE that are a good fit coming from applied physics (electromagnetics and solid state devices), but regardless, coming from outside of EE will give a bad impression to the admissions committee. So I want to do whatever possible to show that I'm qualified.
Moreover, the professor I'm interested in works on computational electromagnetics, and if I can show her that I have the required preparation, maybe she'll be more willing to look into my application through the graduate application system.
So what do you guys think? Thanks.

Sounds perfectly reasonable to me. I got my current job by being inquisitive and interested in learning more about the project prior to being offered an interview.

It sounds like an excellent idea.  I like to meet with prospective students, especially ones from atypical backgrounds; a meeting gives both applicant and faculty a chance to gauge whether someone will be a good fit for the program.
However, don't get too pushy.  Keep the conversation casual, and don't put on an elaborate show of your knowledge.  The best approach may be to ask about the professor's research, and express how it tied into what you already learned and found interesting, as well as what you are interested in studying further in the future.

Do you think I should send an email before? I don't want to do this and instead just knock on her door because in my experience professors are pretty careless with email and take a lot of time to reply, if at all.

Absolutely send an email first.

@DavidV Yes, send an email first.  I meant to say that as well.

Is it a bad move if I go to a professor's office and express my interest to work with her, and show her my relevant skills?

Depending on how the department works, it could be a very good thing or it could be irrelevant. It seems very unlikely to hurt. Some departments allocate graduate students to a given professor (or more accurately the funding) and some professors have funding for a graduate student. These professors can influence the admission of a graduate student beyond what the admissions committee is looking for. If I am looking for a graduate student, and the student seems remotely qualified, I would love to meet them prior to the admissions decisions. If the student makes a good impression, I can then lobby that the student get invited for an interview. If I am not looking for a graduate student, then it is a waste of my time to meet with a prospective student.
It would be much better if you sent an email with your CV prior to stopping by than to just show up unannounced. If you just knock on my door, I am likely to not want to meet with you and without me doing any prep work, the meeting will not be as productive.


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How to organize a social visit to a department?
I'm going to a foreign city to meet a friend, and while I'm there I figure I might as well visit the local university and talk to the researchers in my field (astronomy) to find out more about what they're working on.
Who do I contact about this kind of visit? I don't know anyone there personally, and there's nobody in particular that I'm interested in meeting. I haven't looked through their personal pages (much less publications) either. Should I? It looks like a fairly large department, with ~20 researchers at postdoc level and above + some 50 PhD students; checking out every one of them will take time.

In the US it would be appropriate and possibly necessary to contact the head of the department in which astronomy resides. For foreign travel, do something similar, depending on the organization of the university. You need permission to avoid security issues. Strangers wandering around are an issue.
In pandemic times there may be special restrictions. Many large faculty have some sort of "coffee lounge" where they gather informally. It is a good place to chat with people, including graduate students in at least some places. The department head might even be willing to introduce you to a few people.
Offer to give a talk on some subject that you know well and that might be of interest to a few faculty and students. If this is agreeable, the "department" will likely make an announcement, indicating you will be present.
Indicate that you are just using the opportunity of being in the neighborhood to establish informal contacts.

Maybe you can join a colloquium or some other (semi-)public event by that department. Maybe you can give a talk and listen to a talk.
If that is not possible, I would think about a more concrete goal of those meetings. Imagine you get a meeting with some faculty member, you sit in her/his office, and (s)he starts with "Welcome. What do you want to talk about?" and an awkward silence ensues.


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What is the best secondary language for an academic to know?
Let's say someone young (~PhD student stage, possibly earlier) wants to become a professor. He doesn't mind moving around and will go wherever the best offer is. He'll obviously need English, but he's also motivated enough to learn another language. What is the best language to learn that will open the most opportunities?
If we proxy the number of jobs available in any country by research spending, then according to Wikipedia the most likely destinations are the USA, China, Japan, Germany and South Korea in that order. The main language in the US is already English, but the other four have local languages. However, I don't know how easy it is to get an academic job in any of these countries (or the ones later in the list - India, France, Russia ...) without knowing the local language.
If the answer to this question varies by field, the I'm most interested in the sciences.

My answer would be Python, but that is a bit orthogonal to your needs. However, I don't really understand the point of your question. If you can read French or German, say, you can read old texts that haven't been translated. But if you go to one of those places most academics will understand your English.

You're mixing up the order of things. First get the job, then move to the country where the job is, finally learn the language of the country where you just moved to.

@Szabolcs well, I'm thinking more of a would-be academic who's not at the job search stage yet but has the opportunity to learn a new language, wondering which new language to learn. In principle it could also be for PhD studies - I have no idea if knowing Norwegian makes it easier to get a PhD position in Norway, for example.

@Szabolcs That won't necessarily work.  If the position requires teaching or other communication in the country's native language, then they will expect you to to be able to speak it well enough to do that part of the job, and will probably do something to verify your proficiency before offering the job.  I've known French universities, for example, to invite candidates to give a talk in French both to get more familiar with them and judge their ability to teach in French (as the French speak it).

@Buffy judging from this question, it's not advisable to take up a job in China without knowing Chinese, even if other academics can understand you - https://academia.stackexchange.com/questions/104541/persistent-issues-with-salary-pay-as-a-postdoc-in-china-what-can-i-do

There are a lot of questions on this site about academics visiting China. You should explore some of them.

Of course my comment was oversimplified, as it's just a short comment. However, I do think that this is the wrong reason to choose a language to learn.  Personally, if I were to learn a language, I would choose one that I believe I would enjoy studying, where I am interested in the culture, etc. These things are important to keep up motivation, and have a better chance at achieving fluency.  Statistically, you will likely give up learning way before you reach that stage. If you don't, maybe you'll end up developing a connection with the country of the language and looking for positions there.

There's (at least) four aspects of learning a language: reading, writing, listening, speaking; and one might find it valuable to learn different languages in different ways.  For instance, I found it very helpful to learn to read French, because there are important papers in French in my field, but I only ever had minimal need to write it (I once had to write an abstract for a bilingual journal).  As far as speaking or listening, so far, German would have been more useful to me than French.

@Buffy In my (very limited) experience, it becomes more of an issue in informal group networking situations. Almost everybody knows English and is happy to speak it with me one-on-one. But if people are already chatting to one another in German, it's harder to enter the conversation and ask them all to speak English, or even to know whether the conversation's one I want to join.

@zibadawatimmy I've seen ads state that teaching starts in the second year, after you've learned the language. I think at least one institute in the Netherlands does this. I don't know how prevalent it is.

Learning a language is a huge commitment so it is important to be motivated to stick at it. Since English is almost universally the lingua franca for academic research, there are many opportunities for your career (even in foreign countries where English is not an official language). Many people postdoc abroad who do not speak the local language. There are labs that work in English in most countries, although options are more limited in countries such as Japan (where English is seldom used) compared countries such as the Netherlands (where many people understand English). There’s generally an expectation that a postdoc will try to learn the local language if they’re in a foreign country since it helps for daily life. Preparation helps if you’ve got a particular country you are seeking to work in but taking a career opportunity and showing up with no language skills is commonplace. Some countries will require administration and teaching in the local language so it is more important if you intend to be a professor in a specific foreign country. Of course, even a few greetings and cultural awareness will be appreciated if you are travelling or collaborating internationally.
Learning a foreign language is not needed for an academic career but there are several reasons to do so:

It will enrich your understanding of the difficulties of second language speakers working in English such as your future students and collaborators.

It will enable you to communicate with the locals in your daily life if you live in a foreign country (or visit for conference or sabbatical).

It will give you a better understanding of the cultural heritage of your people or the place you live.

It could enable you to read historical texts or understand terminology in your field (e.g., Latin, Greek, Hebrew, ancient Chinese). This is only beneficial in a few fields.

There is no one most important second language for an academic career. It depends on where you are, where you want to live long-term, and what your interests are. It’s a long-term commitment, not something you can pick up over summer to fill out your resumé.
If you want to communicate with minorities in the US, learn Spanish or Navajo. If you want to teach in New Zealand, some Te Reo Māori skills will be beneficial. If you’re studying Chinese history, brush up on rare Hanzi.
For instance, I’m learning Japanese not because it will benefit my career: I could do similar research in another country and be just as successful or more so without the language barriers. I’m doing it for personal reasons: I want to understand my partner's native language and culture. I enjoying living in Japan and sought a career here because I wanted this experience. You don’t need to have the same reasons and choose the same language as I did but you do need to have strong motivation and personal interest since it is very demanding on your time to get any useful level of proficiency.

Probably the quickest & easiest benefit to learning another language will just be in giving you another item for your diversity statement in the US (with Spanish probably most valuable, particularly to teaching schools with large hispanic enrollments), or giving you some favor in other countries or with people from there (at jobs that are still in English). For example I know postdocs whose only distinguishing feature appears to be knowing a little Chinese due to spending a little time there, who landed jobs in the labs of Chinese profs in the US. It probably won't have a measurable benefit for a R1 TT job search though.
As for getting a job which requires speaking and writing in the language, some languages are much harder than others (for native English speakers). Japanese, for example, takes a lot of years. You can get functional in a shorter time with simplified Chinese, for example, though still years. And of course with the Romance languages and German you go much much faster because you can leverage similarities to English words and alphabet.
I'd suggest thinking about where you'd like to live first and look from that perspective, as a way to enrich your life. Because the time commitment will probably not be worth the payoff if your only goal is just finding a job. You'd get a lot more bang for your buck by devoting all that effort to building your technical skills or producing more work output.

Japanese grammar and reading kanji is very difficult to master so you won’t be passing JLPT exams anytime soon but you can learn to introduce yourself and order coffee in a few months. Chinese tonal pronunciation is very difficult so it’s no small task either. Either way, it will be a lot faster in a country where it’s the local language. Of course, they’re both much more challenging for English speakers than European languages with more similarities and loanwords.

since you are interested more in the sciences , it is known that the most important language in science after english is german language , also it is one of the major languages used in academia in general .

This comment is extremely outdated, perhaps it were true in Edo era Japan but it is no longer the case. German is now rarely used in Sciences outside of majority German-speaking countries. Perhaps it is relevant for historical scientific texts but that applies to Latin, Greek, Arabic, French, or Russian too.

I am Finnish. The Nordic countries share much of the culture and climate and are an easy place to move to also for bureaucratic reasons, but in all but the most research-oriented universities the ability to teach in the local language is a requirement or at least a benefit, and it is likely a benefit in even the research-oriented ones. Now I can speak Norwegian, write that and Danish, and communicately intelligibly with Danes and Swedes, too. This increases the size of the job market for me significantly.
I have also read some mathematics articles in French, Spanish and some parts in German, and if I could, I would have read at least some abstracts and maybe articles in Russian, Japanese and Chinese. I can't speak any of these languages, but knowing the basics of French allows me to read French and Spanish mathematics close enough to my research field. Learning the Cyrillic alphabet properly is on my to-do list and should help in understanding paper titles in Russian; right now I can do it only slowly and partially.
If I ever decide to learn another Germanic language (maybe Icelandic or German), knowing one of the Scandinavic languages will certainly help.
Conclusions:

Are you interested in moving to particular countries? Knowing a language spoken there certainly helps. It might be required, but is doubtless helpful.
Is the science in your field done in multiple languages? Learning one that you occasionally meet can be slightly helpful. In some humanities subjects it can be very helpful, from what I hear.
Learning an additional language is easier the more languages you already know, and the effect of closely related languages is obviously even larger. Knowing at least two dissimilar languages is a huge step over knowing just one.

If you don't have any particular preferences for different countries, which I find unlikely, Chinese and Japanese are very different from English, and therefore difficult to learn, but also useful for that reason. French and German are a lot easier and faster to learn, but already useful.
According to rumours, many French jobs require French (I have not checked) and the language is also used in several neighbouring countries and several former colonies. German positions might or might not require the language. At least some Japanese positions do require the language. I don't know about Chinese positions.
You might also consider that every country has to educate teachers and engineers. Much of the education will happen in native languages and employs people with an academic background, though whether this education happens at universities or some other institutes varies by country.


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Is it undesirable to publish a 2019 paper in a 2020 issue?
This question is inspired by How to make sense of a 2019 paper published in 2016 journal issue? From the comments to that question, it's apparent that publishing a 2019 paper in a 2016 issue is inconvenient for the author. This question asks the reverse: what if the journal is so "frontlogged" that it publishes its 2019 papers in 2020 issues?
I have handled such a journal at one point. The journal was receiving and accepting lots of submissions, so many in fact that it was publishing issues ahead of time. Previous editors were reluctant to increase the issue count because they feared this stream of papers would dry up, and if the journal ever struggled to fill its issues it would lead to problems like in the linked question, where 2019 papers are published in 2016 issues. The upshot was, by the time I took over the journal it was more than a year ahead of schedule.
Is the journal being ahead of schedule a problem for authors? What about librarians?

Related: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3534064/

A better question "is future publishing an intelligent solution? Is there a better solution?"

@Roland It could be an issue for the authors; for instance, priority disputes: it's difficult to argue that Smith (2020) was the first to introduce the method used in Brown (2019), and even if it's true other people will easily misrepresent that when they cite the method. Also, missing certain publication targets is a 'bean-counting' issue that may have heavy consequences on you as an author; if these things are used only for annual publication statistics where you work then you are lucky.

@Roland "You didn't publish enough papers in 2018, so we're going to cut your funding for 2019" is a thing in many places. If your paper bears a 2019 date, it doesn't count for this (and it's difficult to convince people to look at the accepted date, especially when this is an automated process).

In the present day, publication year is essentially irrelevant.  What matters for the job market is the acceptance date.  Usually publishers put the article online within days of acceptance.  At this point people begin citing it.  If the paper is not assigned to an issue until the next year, the only effect will be that people citing the paper will be annoyed by copyeditors asking what the publication year and issue are.

It's common to have some delay.  12 months sounds bad to me (as an author).  Would think to move (or stop submitting).  But it's a sliding scale discontent thing.  Might not even notice at first.  But sure, it will have some impact eventually.
Really, more annoying is not having the acceptance (long review delay).  Because once the paper is accepted, one can put it on resume, etc.  Plus I guess you can order prerints (do people even still do that)?

I didn't mean delay - the journal was ahead of schedule; it was publishing 2019 papers in 2020 issues (for example).

OK.  You're right on what you said.  That wouldn't bug me as much.  Still mildly annoying as someone looking at a CV or cite, might not realize a year ahead issue is actually out.  But not a huge deal.

@guest - these days with many journals appearing on-line well before the actual physical issue (if those are even a thing often), it is not unusual to see complete, citeable journal issues 6 months or more ahead of time (so in September of 2019 there are issues dated in 2020). It is the same process as happened in the past, you just get to see it live now rather than waiting by your mailbox for an issue to finally come out...

Apart from its positive or negative mechanical effects in gaming the bibliometrics system, it is undesirable because it's basically lying. It may be an unpopular opinion, but I don't like lies, as a general thing.

How is it lying? The acceptance year needn't match the publication year. Indeed, that can be impossible, e.g., any manuscript accepted in late December (after December's issue) cannot be published until the following year.

How does this 1) game the bibliometrics system and 2) is related to lying? I see no relation in either case at all. If you're referring to the link Bryan Krause gave in a comment, that involves delays, which isn't happening here.

@Allure For 1) I think that this strategy may be used to increase the impact factor of the journal. If the journal publishes the accepted papers online (such as in an early view or in press category in their website) then those papers can be cited. IF measures the number of citations for 2 years after publication. Since the papers are already online for a year or more before actual publication they might get more cites by the time the 2 year after actual publication period ends.

@user2768 If you start from the idea that the year an article is labelled with is just an arbitrary number that has no relation to when the article was accepted, then it's not lying. But I don't think that this is a useful mindset. Also, it looks like you are using an edge case (article accepted on December 31) to support the idea that it's OK to artificially add months to the acceptance date in general just because it's convenient, even in much more general cases, and that doesn't look like the most honest thing in the world.

@FedericoPoloni I used an edge case to highlight the point. Equally, an article that is accepted in middle of the year might not be published until the following year, because the publishing process takes time. Books are just the same: Authors finish writing long before books appear on shelves. Certain journals are completely transparent, for instance, they include date received, date accepted, and date published.

@Allure My comment definitely also applies here assuming the citation metric uses the label of the issue (i.e., "2020") rather than the year it's actually published. Besides simple offsets like preparing an issue a couple months in advance (i.e., January 2020's issue is actually ready in Nov 2019), it seems to me like labeling a 2019 issue as a 2020 one is practically fraud. Dates have meanings.

@BryanKrause it's so unfair to call it fraud though. Like, imagine lots of newsworthy things happen today and the newspaper you subscribed to have enough material to fill a second issue. What else do you expect them to do something other than delay some of that material to tomorrow's issue? Especially if tomorrow might be a barren day for news and they can't produce a much-smaller issue without angering some subscribers.

@Allure There's a difference between delaying stories that don't change for a day, and publishing a newspaper today with next week's date and a bunch of stories talking about stuff that happened today. And you're the one who just said you weren't talking about delays but rather labeling today's issue with tomorrow's date: which is it?

@BryanKrause please read the OP again.

@Allure Yes, it is not clear. Are you publishing a 2020 issue in 2019 with 2019 submissions? Or putting 2019 submissions in a 2020 issue?

@BryanKrause The first.

Let us continue this discussion in chat.


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Why do academics prefer Mac/Linux?
In the commercial world, Windows utterly dominates. As of time of writing its market share is somewhere around 85%.
I don't have similar statistics for academia, but my personal observation is that most professors seem to prefer Macs, especially on personal devices. Linux is also a lot more common than in the public at large. Windows computers are still around, but much less common - maybe around 1/3 of computers run Windows, a substantial fraction of which seem to be because they're preinstalled with Windows.
Why the preference for Macs / Linux?

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Do not forget about an important fact: historical reasons. Windows got a huge market share because of great marketing and allowing personal computers. It was never a good operating system, but a somewhat accessible and well advertised one. Loosing market share in this domain seems hard.

After all, nothing screams "serious and professional" like an OS that comes with Candy Crush ads in the main system menu.

Is there a missing word before "academics" in the question, or is this another one of these "humanities don't count as academia" things?

@YemonChoi I prefer to call it one of those "the OP is unaware humanities professors don't use Macs/Linux" things.

It's not entirely accurate to state that Windows 'dominates' in the commercial world. While this is generally accurate in Desktop and Laptop computers, keep in mind that the vast majority of web (and other) servers are Linux-based. Keep in mind that 100% of the TOP500, a list of the 500 most powerful computer systems in the world, are on Linux. Keep in mind that Linux, especially if you include Android, is almost definitely the most prevalent operating system (kernel) in the world in terms of number of devices.
A lot of academic institutions, especially in more computing-related fields, are big supports of open-source/FLOSS communities, and Linux is obviously a very big underlying part of such communities.
And, most key in my experience, for academic/scientific environments, Mac and Linux have enormous computational advantages over Windows - the underlying Unix architecture model and the inherent support of very useful shells like bash, very useful device handles (eg. /dev/random, or device IO handles), etc. These things make the development of custom code, especially for scientific, computational, or instrument-interactive purposes, a lot easier than on Windows.
Even if you're not using custom code, I'd venture to guess that absolutely any computing cluster worth its salt is being run on some kind of Linux. If you want to just use that cluster, it's far less hassle to SSH in with a Mac or Linux computer with SSH built-in, than having to use something like Putty and fiddle around on Windows.
In all, science is very heavily dependent on computing. And high-level computing is very dependent on Linux. In my view this is the biggest reason that very compatible Unix-like systems like Mac and Linux are far more prevalent.

I wouldn't call those computational advantages; rather convenience ones.

Why Mac, though, and not Linux? I don't think more than 10% of university student Mac users have ever opened a terminal window, let alone an SSH session.

@henning OSX currently still fills a niche with enough commercial support for arbitrary "you must use Adobe Acrobat to fill in this form" from (windows using) administration, while being *nix enough for library support. With the move to browser/cloud based software for admin, and the Windows linux subsystem this gap is closing, but there's still inertia.

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Folks - please take all conversation to chat! Comments can only be migrated once; after that they're just deleted. Please reserve comments for questions/clarification requests about the post itself.

Answer also doesn't mention that academics are far more likely to be doing software development that typical users, and developing software on Windows is an exercise in masochism compared to Unix-base OSs like Linux and Mac OS. Unix was designed for software development from day one, and it shows.

I think you mean " FOSS" not "FLOSS".

@user541396 Free/Libre Open Source Software.

I was under the impression that at least one or two of the Top 500 ran on FreeBSD.

@origimbo It's not just *nix enough, it is an official UNIX operating system.

It's not just Linux and macOS, it's UNIX (and derivatives) in general. There are a lot of reasons, but a few things worth noting that might not have been covered yet:

BSD (incl. the BSD Sockets API), was originally developed at University of California, Berkeley. BSD subsystems are utilized by macOS, Darwin, FreeBSD, OpenBSD, et al.
GNU (typically utilized by most Linux systems) is also heavily rooted in academia. Founder Richard Stallman has something like 20 honorary doctorates and professorships.
Mach (utilized by macOS, iOS, XNU, Darwin,  GNU Mach, Hurd, et al.) was originally developed at Carnegie Mellon University.
Non-proprietary, free and open-source systems, software, projects, etc. (like Linux) aren't funded by high volume sales (like Microsoft Windows), so their development largely depends on contributions of knowledge and labour from postgrad research teams, and the academic & intellectual communities at large.
These kinds of operating systems are particularly well suited for distributed & parallel computing, supercomputing, rapid development, prototyping, experimentation, computer science, and science & engineering in general. When people accustomed to well-funded, proprietary products like macOS and Windows10 (i.e. most people) try a Linux distribution for the first time, often their first impression is that it's ugly, unpolished, even "un-finished" or incomplete — like it's still in development.

And they're not wrong. It's constantly being developed, and kind of open-ended; you can add or remove anything you don't need or want. You can adapt it to your needs or to suit any specific purpose, and you're not stuck managing a giant, stubborn monolith that forces you to adapt to it, instead of the other way around. It's kind of like leasing a mansion vs owning & living in a workshop; they're suited to different purposes.
Academics often choose macOS when they're looking for a bit of a compromise between the dichotomy. It's nice and clean, and simple, and easy, and uniform, and respectable, so you can bring your mom or your girlfriend or your grandma, but you can peel back the shiny stuff anytime you want to get back to work in that familiar UNIX-style environment.

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I see an edit was made to remove sexism, and you rolled it back. So this isn't unintentional carelessness, it's deliberate sexism. Why?

Windows reboots itself without permission.  This is very inconvenient if your computer is doing something at the time.  Mac/Linux do not have this problem, so they are preferred.
Some specialised hardware only comes with Windows drivers.  Hence Windows is required.  Occasionaly hardware requires a different operating system.
In practice I use all three.

"Windows reboots itself without permission" Pretty sure you can fix this by editing your registry values.

@nick012000 Sure, but you need to first know to expect it, preferably before you loose a couple of weeks of computations, then actually know what to change and where, which in itself can change from time to time, and then actually do it. If you a large number of computers, then also do it for every computer. On top of that, there might be issues fighting the local IT department, especially if it's understaffed and overworked and has issues collaborating with the research department (in one pathological case, I've even had 1 IT guy servicing more than 500 constantly broken computers).

@nick012000 Please send me directions that are compatible with my university's IT policy.  I've tried many times.

@AnonymousPhysicist Ask one of the IT faculty that you’re on friendly terms with how they get permission to modify their computers by installing custom software. ;)

@nick012000 I did that already.  To be honest I think you are wrong.

@AnonymousPhysicist I turned off Windows Update’s ability to force reboots that way back when Microsoft was trying to force people to “upgrade” to Windows 10. If that’s what you’re talking about, then yes, you definitely can.

@nick012000 That's irrelevant.  New computers come with Windows 10 and might not be downgradable to a better version.

@AnonymousPhysicist I was just giving an explanation of why you’d want to turn Windows Update off, since usually that’s not something you’d want to do. I don’t expect that it’s terribly dependent on what version of Windows you have installed.

@AnonymousPhysicist If you're running week-long computations then Windows Server is probably the correct operating system to be using.  Professional and Enterprise desktop SKUs also let you manage reboot policy.  If you're trying to run computations on a Home SKU, well... it can be done, but it takes some registry hacking.  With that said, you can't do anything in Linux without having to put on a chest-high set of text-file waders so I don't think it's a legitimate complaint.

@AnonymousPhysicist  With that said, I run a factory 24/7 full of machines that have windows-based control systems and HMIs.  I can guarantee you that our factory doesn't randomly reboot itself into oblivion.

@J... Yes Enterprise lets me stop updates for 35 days.  That's not what I want.  I want it to update only when I tell it to.

@AnonymousPhysicist Well, if course it's possible to disable updates.  And I'd say it's easier to do than most administrative tasks in Linux.  Apple and Linux both seem to come with reality distortion fields.  Apple's is well known, but Linux seems to promote a forgetfulness about what a pain it is to administer.  I think it's pretty rich when a little baby config change on Windows  draws howls of woe and labourious dread.  If that's too hard for you, how on earth did you even manage to install Linux?

Windows sucks in ways that Windows users are content to accept, because it is what they know...

@J...Linux, by design and by it's very nature is generally much easier to administer than Windows. It's just different to what most people are used to. it's a different style, and I'm not sure style can really be taught. Not easily anyway. You kind of have to get used to it. But it's one of those things where once you get the hang of it you'll wonder why it's done any other way.

In the commercial world, Windows utterly dominates.

If you're referring to researchers in a commercial setting - that's really not the case, or at least - you don't have any evidence to support this. In my experience, research staff at commercial outfits also tends to prefer Unix-based operating systems.
I would say the reason is that these systems are a lot more inviting and amenable to software development, this has at least the following consequences:

A lot more variety of niche applications, libraries and tools which researchers need to use or just find useful.
More amenable to customization, modification and adaptation - which researchers are more likely to want to do.
Easier for a researcher him/herself to code something.

Also, GNU/Linux is free and you can just copy it - and (almost) all software you can get on Linux; with Windows, not only do these things cost money - in an organizational setting at least - but they require the hassle of managing licenses. Ugh.

I don't have similar statistics for academia, but my personal observation is that most professors seem to prefer Macs, especially on personal devices.

Maybe that's true in the US, and even there I wouldn't be sure. Anyway, I would speculate that is more of a combination of vanity/fashionability, and the fact that Macs have very good hardware and well-put-together desktop environments with few bugs and usability issues. But - they are also quite expensive, so it's more likely for richer people to have them.

If you're referring to researchers in a commercial setting - that's really not the case — In particular, it's quite common to see researchers from Microsoft Research at conferences, giving talks that were clearly developed using the beamer LaTeX class, from their MacBook Pros.

@JeffE LaTeX exists for Windows so that’s really not relevant. But you’re right that Linux and, to a lesser extent macOS, are prevalent at Microsoft Research, as well as the more cloud-oriented parts of Microsoft.

It may be relevant that they are using LaTeX rather than PowerPoint because that choice suggests an understanding of the role of software that differs from the one the Windows cultivates.

@dmckee: TBH, if PowerPoint had some stable structural representation of content and slightly-better support for math, a lot fewer people would have been bothered with the warts of LaTeX.

On the other hand, if LaTeX had a reasonable visual user interface, a lot fewer people would bother with the warts of PowerPoint!

not only do these things cost money - in an organizational setting at least - but they require the hassle of managing licenses.  Time == money, and as anyone who has used OSS knows, getting stuff for free comes with its own barrel of headaches.  Code that doesn't compile, torturous dependency chain issues, buggy software, kludgy interfaces, needing to spend time away from getting the job done to fix the deficiencies in your "free" tool yourself... all of this takes time, sometimes much more time than the money those commercial licences are worth.  There are use cases for both, naturally.

@J... "torturous dependency chain issues" In the bad old days this was huge, but I dispute it as an issue today. I type brew install whatever (or dnf install ... or FSM forbid pacman -S ...) and the package management system takes all the headache. And for uses that prefer graphical pickers there are friendly front-ends available.

@J...: This was partially true 20 years ago, mostly untrue 10 years ago, and really untrue today - unless you want to do custom software development. And when you do want to do that, the barrel of headaches is still smaller on Unix-based machines than on Windows. The only counter-case is developing software wholly within Microsoft's own ecosystem.

@einpoklum That's fair - installing software has become a lot better, I'll agree.  Still, often the free OSS alternatives to commercial software are not as elegant - learning curves are typically much steeper, there are odd interface quirks, functionality isn't always fully developed, documentation can be spotty, etc.  What you save in money going with free/OSS you usually have to pay for in time.  I think that's still true today, particularly for advanced applications like scientific simulation, CAD, etc.

I would characterize the ostensible preference for Windows outside of academia as mainly inertia.
In corporate environments, the choice of OS is often dictated by application compatibility. If you have a corporate intranet which was designed to only work on Internet Explorer, you are stuck on Windows for practical reasons -- replacing it would be an expensive undertaking and bring little value, so you just live with the consequences of that previous decision.
Of course, that's just an example -- more common is probably the use of an array of enterprise applications which were designed for Windows, or work better on Windows.
Add to this the cost of hardware and compatibility concerns. From a cost-of-ownership perspective, the availability of commodity hardware with supported drivers is still a strong selling point for Windows, coupled with the fact that this is what you can expect current and future employees to be comfortable with.
Microsoft has some propaganda which attempts to argue that the TCO (Total Cost of Ownership) is favorable on Windows, but I find these claims dubious at best; and certainly, if you factor in user satisfaction, many users who have a say in how their hardware budget is spent definitely swing the other way.
Ultimately, for many users, the deciding factor is whether they need strict Office compatibility or not in their day-to-day work.  If your organization heavily uses one or more of the Microsoft so-called productivity apps, the free offerings are often unacceptable, even if they nominally manage to open and save files in these formats.
Where these popular applications are not crucial, it seems that you can be more productive if you can avoid them.
In academia, then, central use cases outside of proper research are article composition and review (where typically popular word processors are less than ideal, and some disciplines heavily favor e.g. TeX), email, and web-oriented activities, where fortunately free and open source offerings are generally roughly on par with commercial alternatives.  Whether you then prefer (or can afford) Mac or Linux is down to personal preference and budget.
Finally, of course, you might have an important research application which happens to be primarily targeted for Linux platforms (or occasionally, as the case may be, Mac, though this is probably no longer very common).

It's incorrect to call this inertia. The issue is not just Office (useable free versions do exist, even if their quality is not always great), but all the other applications that people use to do their jobs. Your claim about use cases is simply wrong, unless by "academia" you only mean "arts". Those applications are nearly always Windows-based, so it's a Betamax problem - however good your platform is, people care about actually using it, not about the platform.

@Graham I really don't understand your objection. What are all the other applications and why is this more pertinent to arts disciplines? In fact I was very much thinking about various STEM fields where a lot of experiments etc more or less require Linux for analysis etc; though of course there is also a lot of legacy lab equipment which will only work with Windows drivers etc.

And the Betamax analogy is tenuous at best - the reason VHS won in spite of its flaws was because it became more popular; but I'm arguing that this is different: as long as you can do the things you want to do, you don't really care if your chosen platform is popular or not. Open or at least reasonably portable file formats help here - even if you prefer WordPerfect 4.x or WriteNow you can send things to people as PDF and they don't need to know how the document was produced.

I meant that it's only arts disciplines where your primary use cases are web browsing and document creation. I'm an engineer, and I literally can't count the number of other applications I and my colleagues use on a daily basis. Some are cross-platform, but many aren't - SolidWorks, for example. Outside of a narrow techie group, people don't care about whether they're using Windows or not, they care about being able to easily do what they need for their work, and their use cases are much wider.

Well yes, of course there are disciplines or departments - in Arts too - where local conditions force your hand one way or the other. Then of course the question at the top of this page is moot, though the last paragraph in my answer specifically discusses this case.

Re VHS, the reason it became more popular was because they had the films people wanted. That's the point here - it's not popularity of the platform, it's availability of software for the platform. Macs only exist because historically they had DTP and graphics software which was not available on other platforms. And to be fair, there are a very few applications which are only available on Linux. But a great deal of third-party software is written for Windows and doesn't have Mac or Linux equivalents. (I would say "the majority" but I don't have evidence to back up that assertion.)

In my experience, younger people go for flashy, fashionable, stuff. Macs certainly fit the bill there, and Apple marketing specifically on that, turning their products into fashion items, does a lot for that.
Older people in sysadmin jobs often are almost religiously fanatical about their support for Linux. This they picked up 15-20 years ago during the operating system wars, and has little basis in reality but it sticks to this date. That's not to say there are good reasons to use Linux on occasion, but it's certainly not the one size fits all perfect solution these people think and claim (and push on those who depend on them for their computer hardware and software support). This causes a prevalence of Linux workstations in places where these people end up in the IT departments, which happens to be more likely universities than companies by now as most companies prefer more pragmatic employees.
Personally, I use both Macs, Windows machines, and Linux machines, the latter mostly (almost exclusively) as servers. In the server world transitioning from HP, Sun, and IBM (among other) Unix platforms to Linux based ones is a major cost saving while retaining a Unix style platform, easing transition. Which is the original reason most servers now run Linux. On workstations, it's a much more personal preference thing (myself, I consider Linux to be clunky still on the desktop, though less so than in the past) and there are religious fanatics supporting different operating systems. In academia those gravitate towards Linux, in the graphics industry towards Macs, and what few there are left in industry usually towards Windows (after the demise of OS/2, which had its own fanatical fanbase in the 1990s).
In the corporate world, many companies default to Windows because it's easy to use for the end user and Microsoft has a pretty good support infrastructure, giving you a single place for all your problems if you can't solve them yourself.

Windows 10 + WSL2 crushes vanilla Linux in terms of capability, I feel sorry for all the people still struggling to get audio and power management to work properly with Linux on their laptops... I have been using Linux professionally since the mid-90s but there is no doubt that Windows is superior now

@Gaius I agree, but didn't want to ignite a discussion on the comparative merits of operating systems and thus kept things neutral :)

While @tjt263's answer sums up most reasons I specifically want to point out that this seems to be the case in STEM related fields. I work in a STEM working group as well and this is definitely the case here. In my brothers group, which is civil engineering, they all use windows. My girlfriend works in a group related to humanity science and they all use windows.
The biggest reason for Linux I observed is: It is just simpler. My group is related to machine learning, deep learning, computer vision, etc...sometimes it seems almost everyone in this field is producing "throw away code". Just publish a paper and that's it for the code. Since there is no end product involved, it does not matter if it runs only on this machine or more general, only on linux. So most people just use Linux because the libraries they need can be installed via simple command in the command line, they do not even care(or know) where it is installed...it just works.
Also you have to keep in mind that Linux is free while Windows is not.

I am an academic and have more than 10 years of experience in the academia, including my doctoral studies.
I use Windows as the main operating system because most programs are made for Windows and because of subjective preferences.
Within Windows, I use a Linux virtual machine (VM) to run scientific software that is only or mainly developed to run on Linux. Linux also has a powerful command line and scripting, with which amazing things can be done. Additionally, many computing clusters run Linux, and they are useful for large calculations.
I used Mac in the past but now don't see any advantages in doing so over my current combined Windows/Linux setup.

There is a lot of talk here on software availability. Let's talk about software developing. The whole thing is quite multifaceted though.
While Windows has a quite dominant share in applications, for a long time it was harder / more costly to start writing software for Windows. Nowadays the cost / availability factor is quite relaxed. However, some architectural obstacles remain. It is just easier to obtain and use (open source) libraries under a UNIX-like system, which both Mac OS X and Linux are.
Linux strives from the controllability of everything, the typical young adult rebellion, and from experienced people on the server side. Macs have the image of "just working", even if it's deteriorating. However, from the developer's view it's much easier to make a typical programmer's workhorse from a Mac than from a Windows machine. There are not many more extra steps than with Linux.
With Macs, the looks, the availability of drivers (like, 10 years ago there was a real driver hunt under Linux, if you wanted to support, say, both sound and suspend mode in your laptop), combined with relative ease of programming usage speak for them.
Of course, there are some special software products that work only with Windows or even rather on Linux and nowhere else. So, some times you need to adapt. This seems to be rather field-specific.
Next point: Apple has screwed up many things, but the beamer presentation works flawlessly–if you still have your adapter. I have seen many academics struggling with their Windows and Linux laptops at conferences.
Surprisingly, cost is a lesser factor. But if you compare a sanely configured Mac with a proper business notebook (say, by Dell), the difference is low.
A further point: telemetry and better CUDA run times under Linux. I know multiple people (including myself) who switched to Linux on their workstations in the middle of Windows 10 heist.

tl;dr: Programmer often prefer UNIX-like systems, performance, eye candy, proper image, and similar prices for durable hardware round up the deal.

I am a Mac user at client side but my scripts run on Linux based server. Because the way of work is similar I don’t need to learn double logic. I try to avoid Windows as much as possible.
My main reasons for Linux:
- free, available to anyone at any time; this enables free research, free science, free development, free sharing
- many free and open source projects shared by universities
- open, yes - you can adjust or create your own Linux if you need something special, or find out how things are made if something doesn’t work as expected
- scalable, secure, social
My main reason for Macs:
- user friendly (for Mac users haha)
- hardware and operating system tuned to work together which results in more effectivity, efficiency and less failure; many startups and edu decide for Macs because in total it is less expensive than Windows based systems in a period of 3-5 years even the purchasing cost is higher
- easy to port linux stuff to MacOS and get benefits from Linux
- secure, stable, beautiful

I'm always amused by Linux "stability". Yes, as a server it's rock solid. But then add a desktop environment and associated apps, and watch it die. As a user of both Windows and Linux, I see no evidence of the Linux desktop and Linux apps being any more robust than Windows.

I'm a Mac user for these reasons too, but also because: The expected lifetime of my Windows laptops (Dell, Toshiba, Sony, Lenovo, IBM, HP, Acer, for the brands I recall) was about 2 years (and even less in rare cases). My Macbook Air and Macbook Pro about 4 years.

My experience with inexpensive windows laptops is also that a twoish year lifetime is expected. But I have colleagues who don't buy from the bottom of the line and they get lifetimes similar to those I experience with my macs. Which is great, but it also take price out of the decision because those durable windows laptops have very similar costs to a macbook.

I'm still more than happy with my 6 year old refurbished x230 ThinkPad with FreeBSD and a replaceable battery. I've used Macs for 15 years, but the hardware is no longer good value for money.


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Why do departments fund PhD students instead of postdocs?
If I'm not mistaken, most PhD students (at least in the sciences, which is the field I'm most interested in) are funded. They're provided with a stipend, and all tuition fees are waived. In other words, it's effectively a low-paying job for them. My question is, why fund PhD students instead of postdocs?
I'm dismissing the altruistic reason ("we fund PhD students as a service to the community") immediately since it doesn't make sense - presumably if someone is spending money in this fashion, they'd fund need-based scholarships. The only other reason I can think of is that the department wants something out of the PhD students - presumably research output; can't think of anything else - that they think they're getting a good deal on.
Now according to Google, the typical PhD stipend is about $20-25k / year. Meanwhile, the typical postdoc is paid $47k / year. That means that a department can hire approximately one postdoc per two PhD students. To that we can add:

Postdocs have already been trained; PhD students are in training. Postdocs should hit the ground running while PhD students take time to get up to par.
PhD students especially in 5-year programs spend the first couple of years taking courses, i.e. not doing research work.
Postdocs can do other things like supervise Masters students that PhD students can't.
PhD students apparently have a high attrition rate, as high as 50%. Postdocs have been in the business longer, so presumably are also more aware of what they're going into.

It seems more sensible to me that departments should concentrate all funding on postdocs, and leave PhD students to pay for their own education. This is already the case for undergraduate studies. Why do departments continue to fund PhD students?

Which country? Because things vary enormously from country to country.

As aside, you're missing the PhD student's tuition and fees on both sides of the equation. Depts can both pay them but also get them depending upon the school. In some school, a PhD or post-doc will cost the same depending upon tuition.

At least in Germany, this is totally different. PhD students are paid like normal employees, resulting in about 46k€/year or even more. Postdocs earn more.
Many PhD students also supervise Master's Theses, this is not limited to Postdocs.
PhD students do not have many courses in the first years and can mostly focus on research. However, there may still be several projects coming from the industry.
Most PhD students are publicly funded. Well-educated PhD students will return this investment in later years.

If you don't fund PhD students, you eventually run out of post-doc candidates. Plus, you seem to have a peculiar view of how PhD students are funded, which depends on country and institution...

I'm most interested in the US since the apparent contradiction is most acute for 5-year programs, but am also interested in how other countries work. If PhD students are paid EUR 46k/year or more in Germany, it seems even less economical to hire them instead of postdocs. The same goes if a PhD student costs as much as a postdoc. If I'm misunderstanding something (very possible) I'd sure like to know what and why.

Obvious answer: If everybody funded only postdocs, there wouldn't be postdocs.

@aeismail according to the Economist there's an oversupply of postdocs right now (https://medium.economist.com/why-doing-a-phd-is-often-a-waste-of-time-349206f9addb), so if it makes more sense to hire postdocs than PhD students, I'd have expected individual departments to do so until the supply / demand balances out.

@J-Kun "At least in Germany, this is totally different. PhD students are paid like normal employees, resulting in about 46k€/year or even more" not always, actually pretty rarely. Most of them are supported by department scholarships or the like.

@gented Certainly not in the natural sciences - almost all PhD students I know there have an employee contract.

"I'm dismissing the altruistic reason"

Therein lies one of the biggest problems with your question. I work for a land-grant state university in the U.S. Our mission includes education. It's not an altruistic reason, it's literally why we exist.
The other flaw in your question is assuming that the money to hire these two groups is fungible - it isn't always. For example, there are grant programs where education of graduate students is a major component of what one is supposed to be doing - "we're going to hire a postdoc" is simply a non-alloweable use of funding.
There are some other nice features of graduate students to consider as well:

They're cheaper. While a postdoc is probably more value for complex activities, there are sometimes things that require some expertise, but not a full-blown PhDs worth. Masters and early-stage PhD students are excellent people to conduct literature reviews, field collection, etc.
You can identify promising researchers early. Lets say you see someone in undergraduate courses whose impressed you. If you only recruited postdocs, you're essentially saying "Look me up in 6 to 8 years, I'd love to work with you." If you recruit graduate students, you can usher them into their research career.
You get them for longer. Postdocs are (by and large) transient positions, and much of their time may be taken up by looking (rightly) for another position. In many labs, especially those without long-term technicians, graduate students may actually have more institutional knowledge.

Thanks for the answer. Follow up question - if part of the reason for funding PhD students is because it's the university's mission, why not fund more scholarships? Both need-based or merit-based, as opposed to blanket-funding all PhD students? On that point as well I'm now wondering why undergraduates pay for their own education but PhD students don't, but that might be more appropriate for a separate question.

@user3727079 That's really the content of it's own question.

Can someone provide specific examples of "grant programs where education of graduate students is a major component of what one is supposed to be doing"?

One of the premises of your question is simply incorrect in the US. Since most of the funding for postdocs and PhD students in the sciences comes from grants and the usage of that money is specified by the grant and approved by the funding agency, departments can't simply decide to spend the money differently.
Furthermore, in the US, postdocs can be considerably more expensive than PhD students.
For a Postdoc you've got to pay full time salary, plus fringe benefits (typically 30% on top of salary) plus overhead on the salary and fringe benefits.  For example, a postdoc might cost $50K in salary per year, $15K per year in fringe benefits, plus another $35K per year (54%) in overhead for a total of $100K per year.
For graduate students the costs include a stipend, fringe benefits
(typically much lower for graduate students than postdocs, e.g. 2% at my institution), tuition waiver (varies a lot between universities), and overhead (on stipend and fringe benefits only, since tuition waivers are excluded from overhead.)  A student might cost $25K per year in stipend, $1K per year in fringe benefits, $20K per year in tuition, plus $15K in overhead (58%), for a total of $61K per year.
In these calculations, a postdoc was almost twice as expensive as a graduate student.  Also notice that the postdoc costs three times as much in overhead as the graduate student.  Many program managers hate to see funds going to overhead.  For these and other reasons, there's a widespread preference in the funding agencies for funding graduate students rather than postdocs.

Thanks for answer. Follow-up question: if funding agencies hate to see funds going to overhead, why do they preferentially fund researchers who are affiliated with universities? When I asked about why researchers needed universities a few weeks ago I got the sense that to apply for most grants a researcher needed to be affiliated to a university, even though the university takes some overheads if the researcher wins the grant.

@user3727079 there is a lot of research that only ever gets done in an university environment, because its exploratory research, something that may or may not turn into profit for an hypothetical investor (a lot of grants are given by research councils or whatever is similar in your country). Not to say that any company will charge you way more than the salary of the person doing the job if you want them to do anything. Still, most university research, even in engineering, is not funded with the idea of obtaining profits in the near future.

The major alternatives to universities are the DOE national labs and the research labs associated with the military services.  Overhead rates at these labs are typically higher than at universities.  SBIR grants are an interesting example of grants to companies, but only small businesses can participate.

@DSVA Probably tuition cost of a grad student should be the net cost, so whatever the university collects from the department as "tuition" minus whatever the department gets back as their cut of revenue for enrolling the student. I'd be amazed if this is $20K.

@ElizabethHenning the nominal tuition is what gets paid out of the grant to the university.  From the point of view of the grant PI or from the point of view of the funding agency, that's what it costs.  Except in really extreme cases of RCM (responsibility centered management), individual departments see a direct relationship between enrollment and department budget.

A few additional points that I have not yet seen mentioned.
First, many funding agencies have an explicit preference or even requirements that the funding be used to fund PhD students rather than postdocs. If your main funding sources don’t want to give money for postdocs, it’s hard to have them.
Second, tenure-track faculty members are usually expected to shepherd some number of PhD students to their degrees as part of the expectations for receiving tenure. You can’t do that if you only hire postdocs.
That said, postdocs are useful, and having an excellent postdoc does “pay for itself” several times over in terms of cost.

There are several reasons, here are some:

The most important one, IMHO, is that the reputation of the department depends a lot on how many good PhD students they can produce. This will affect the ability to obtain funding, attract (masters/undergraduate) students, etc.
There are some grants that are only enough to fund PhD students, or that can only be used to fund PhD students.
Advisor to PhD student can be considered academic parent, advisor to postdoc is just another employer.

It seems more sensible to me that departments should concentrate all funding on postdocs, and leave PhD students to pay for their own education.

In Computer Science (and STEM in general), if you don't fund PhD students, not many people will do it. If one can have a PhD offer from Stanford, s(h)e can also get a job offer from big five (Amazon, Google,...) with a six-figure salary. And you want them to work for free in 5 - 6 years?

Adressing your points:

I find this only partially true. The spread inside each population in competence is larger than the distance between the populations.
(+4.)  PhD students - if motivated and good - will stay until you give them the PhD. Others (not motivated, not good) will leave early. Postdocs are less easy to control and may be more prone to doing politics. Typically the motivated postdocs will change when it fits them best (e.g. after having a good publication) and the others may stay
That is purely theoretical. Wherever I looked, PhD students had other functions in the lab, too.

Additionally:

people can be assessed and trained during their PhD - if they are good they may stay.

Another point that hasn't yet been mentioned is that it's not always correct that research output is what PhD students are being paid for. Especially at large American universities, PhD students are paid for teaching, often for leading discussion sections rather than lecturing courses as the main instructor. A postdoc is generally too senior to serve as a teaching assistant in this way, so there is a constant stream of money from undergraduate tuition to graduate student stipends.

Aren't PhD students usually just TAs, while postdocs can be entrusted with teaching a full course?

@Allure Precisely—but at a school with a large lecture model, there is a need for many more TA’s than professors. This model is surely cheaper than smaller lectures led mainly by postdocs, and allows undergraduates at least some exposure to full professors, even at huge schools.