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Is recommendation a must for getting PhD admission in Australia
I am new to this community. The discussions here are interesting so I thought may be I can solve one of my queries regarding PhD admissions.
I am in India and I have completed my post-graduation last year from IIT (one of the top engineering institute in India) in research. I have submitted 2 journal papers and 3 conference papers (as co-author) in my post-grad course. Now I am looking for PhD admission in Australia. There is some personal reason for choosing Australia and I don't want to go to other country as of now. meanwhile I am working as a software engineer in an IT organisation.
I have emailed my resume and thesis to professors in Australian universities regarding the PhD vacancies under them. I have not received any reply (positive or negative). I have started wondering whether I am doing something wrong! Is there some other way to get this information and applying for it? Or am I suppose to send more information than resume and thesis, something that I am missing out.
PS: I have not added any sort of recommendation letter yet. I personally feel that my achievements should speak for me.
Thanks for any help in advance.

Did you supply any references? Or did you supply a list of referees who can be contacted? Or do you mean people who can "canvas" on your behalf?

No, I have just mentioned my educational background, my thesis project, and current job experience. I haven't mentioned any point of contact other than me. Is that a good thing to add a POC?

Referees or references are a "standard" part of a CV IMHO... Unless that is now classed as passé...

I will keep reference for sure the next time I email someone. Thanks :)

Can you edit your post to contain only one question?

You will have a better chance if your papers are published in good journals/conferences.  Simply submitting them has little value.

@AnonymousPhysicist Yes I understand that. They are in the process. So I have written submitted. once the get published I will surely change its status. And also I believe the questions in the post are dependent on the question "Is there something I am doing wrong while sending mails to supervisors". I am open to your edit suggestions, please feel free to edit the post as you feel correct. :)

@SolarMike Are Referees or references really a "standard" part of a CV? But CV is for applying for positions and some positions don't require recommendation letters. If recommendation letters are not required, why should referees be included in CV? I actually don't realize that's a standard part of CV and only include it if the open position announcement requires to do that. Usually an announcement requires the reference letters to be sent by the referees directly without requiring including the referees in CV.

@CaptainBohemian students I know are including references in their cv’s and getting some very good jobs and internships... It may be that cv styles vary by industry, location as well as positions applied for...  I did say it was only my opinion in case you did not realize that....

All of the universities (that have postgraduate programmes) will have an administration office that handles PhD applications and admissions. You will need to find out what these are for each university that you wish to apply to, as these are usually centralised within some area of the university administration and not at the faculty or department level.
Sending your application/resume/thesis directly to professors is the wrong approach. They all receive many such emails and letters and usually have neither time nor interest and will neither read nor forward your application. It is parallel to sending your job application to the CEO or a board member instead of to a company's personnel department.
I myself receive numerous such emails, with e.g. "Dear Professor, I am a student in < country > and would like to study/work/research in your research group", and I am not even a professor. I read that far (at most) in an email and take the next step of simply deleting it as it seems to me that my email has simply been gleaned from a journal site, research site, or other such location.
You need to select the university(s), find the appropriate contact point and approach them. You need to find out what you need to send, and when the deadlines are. A stochastic approach will not help you here, not even were you wanting to do a PhD in statistics.
Edit:
It is, however, appropriate to reach out to a potential supervisor to enquire about research projects that they are offering. This may or may not be published openly. This can open a line of dialogue which may then proceed to a formal application or submission. This is quite different to a blind application by sending a resume with a generic "I would like to do a PhD in your group" message.

I don't think this is necessarily applicable in Australia. If I'm not mistaken, Australia follows the European model where PhD students go directly to research, and professors can directly hire students.

Well, picking UNSW at random, they had this to say on their applications page: "Most Faculties require you to contact potential primary supervisors independently, while others require you to submit an Expression of Interest, after which they will connect you to appropriate supervisors." So, the first step is to contact the university and find out the appropriate process for that university.

@Allure is correct, Mick's answer is completely wrong for Australia, but correct for the USA.

@AnonymousPhysicist Where is the UNSW? If it is in Australia - why do you then suggest Mick's answer and follow-up comment is incorrect?

My bad, I actually didn't think it was necessary to expand UNSW in the context of Australia to spell out University of New South Wales. Missing link to the quoted text: https://research.unsw.edu.au/finding-supervisor

@Allure In my case (in Australia), I spoke directly with my future supervisor and faculty staff but sent my formal application to a central administration office within the university that handled all postgraduate administration for the university as well as liaison for joint-institution and cross-disciplinary programmes.

@AnonymousPhysicist Perhaps your experience with postgrad programmes in Australia differs from mine, and perhaps (or probably, universities being what they are) not every university operates their admissions and administration in the same way, but in picking a random university that was not mine, I found it was very similar.

The short answer is yes. You're not going to get PhD admission virtually anywhere in the world without letters of recommendation.
But there's something more important: your approach is wrong. You should not start by contacting professors directly. First, find out if the university has a centralized PhD program (these centralized programs are very common in the US, for example). As far as I'm aware, Australian unviersities do not, but if they do then contacting professors individually is just inappropriate and a waste of time; you should apply to join those.
If they don't then you should find out if they're recruiting PhD students. They might have a webpage with a list of possible projects for example. If they do then you want to check those projects out and make sure you're interested before contacting them.
Here's an example of how to get a PhD position in astronomy at the Australian National University. After Googling for this, you should land at this webpage for the RSAA. You can see what topics are being studied there. You can also find a link to a list of potential projects, sortable by the level of study. Restricting the search to only PhD-level projects, the first result as of time of writing is this one on 3D modelling of nearby galaxies by Dr. Brent Groves, with a short description of what is involved. If you like the project, then you can email Dr. Brent Groves with your CV, motivation statements, thoughtful questions about the project (if any), and ask him if he's willing to supervise you. If you've read Dr. Brent Grove's work and have a suggestion for a potential project, you could write that too. If you just send your CV and "thesis" (what's this?) without any apparent knowledge on what Dr. Brent Groves is doing, he's likely to just ignore you.

Thanks @Allure. If you just send your CV and "thesis" (what's this?) without any apparent knowledge on what Dr. Brent Groves is doing, he's likely to just ignore you. I suppose this is happening to me all along. Can you comment, whether it is appropriate to email again to a professor with the approach you have mentioned? Actually I have mailed to only those professors who I believe work in my interest and knowledge area.

@RC0993: This is just a random thought, and perhaps others can comment on whether this has any merit, but if you are starting the process early enough so that you have the time to do this, perhaps snail-mail letters would less likely be ignored (giving your full contact information in the letter, of course). (I'm used to the U.S., where in math at least one simply applies to the department, like applying for undergraduate university admission.)

Overseas snail-mail is not possible for me unfortunately. But I can see its importance. :) Thanks for advise.

To answer the question "Should I include a recommendation letter when emailing a potential supervisor for the first time?"  No, you should not.  In your CV, list previous supervisors or other people familiar with your work.  If the potential supervisor wants recommendation letters, they will request them.  Recommendation letters should be sent by the author of the letter, not the applicant.

Yes I have heard this somewhere that "Recommendation letters should be sent by the author". But I remember seeing a girl from my previous organisation filling out some kind of recommendation form which was printed with some format. I wasn't applying abroad at that time so I let it go. Which was now confusing me whether to get a letter from ex-supervisor and sent it across with my email or does my ex-supervisor sent it himself. Thanks for clearing that doubt :)


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Difference in CS application between MS and PhD
I am an undergrad student in CS and I am planning to go to grad school after graduation. My ultimate goal is to pursue PhD since I have done research and I am interested in. However, my research experience may not be good enough for top PhD programs. So, I may go to MS first and then apply for PhD when I get good publications in my pocket. I understand that MS can cost a lot of money but I am able to afford it if I have to. There are some PhD programs that I would like to apply and it’s not that competitive. I think my profile could have a chance. That means I will apply both MS and PhD this year. If I get PhD, I will take it. If I get rejected from PhD, I will go for other MS programs.
My question is: “What are the difference in applying MS and PhD.”
I have heard a lot that applying PhD needs to emphasize research. But is it different in MS? Some MS programs even have track that does not require thesis. Is that mean they should not expect research experience from applicants? Then, what to emphasize in the application?
Thank you very much!

If you want to do a MS to get research experience, you should not be considering MS degrees that do not require a thesis.

From my own research MS without thesis tend to be considered "professional" masters. They are intended for those going into industry. I second if you are looking to continue to additional research based degree avoid the non-thesis option. Also look at the program as a whole (and of course talk with the grad advisor for your prospective program) for what the program's objective is. Some may require thesis, but overall the course work is more applied than theoretical.

What country is this?

I'm aiming for schools in the US.

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Will it be a good idea to take 3 months off after PhD defense to improve my skillset and work on my mental wellbeing?
I have struggled throughout my civil engineering PhD. My topic was away from the realm of my advisor's expertise, and as a result my research can be considered as an independent endeavor. She (advisor) was always there to guide the direction, but she didn't give any technical input to my research.
In addition, my group colleagues, who worked in topics related to my advisor's expertise, published several publications in prestigious journals (IF > 10). While, I struggled to get one published in a 2 impact factor journey. This caused a lot of anxiety during my first 3 years of PhD.
On top of this, my advisor did not proactively correct my manuscripts I had submitted her. So, lot of my manuscripts are pending her consideration. This also affected my mental peace.
Being in final year, I started looking for postdoctoral positions since the beginning of the year. Applied to many, but was rejected. My advisor said to me the other day that if I don't get a postdoctoral offer, I can stay in my current lab for next 6-8 months and search for positions.
I am all burned out and having it difficult to be optimistic about my future. I am thinking of taking some time off (2-3 months off) (I have some savings to pull that off) after my PhD to gather my composure, work on my programming skills, and then join my current lab as a stop gap while searching for positions. I am already 30 years of age and have been a student throughout.
Will it be a good idea to take 3 months off after PhD defense to improve my skillset and work on my mental wellbeing? No, I have not been to any mental health counselor.

Take three months of, yes. But don't "improve" or "work on" anything. Go hiking or surfing, visit friends, sleep in, celebrate your graduation.

What henning said. In the long run, mental well-being will help you a lot more in whatever you do next than some programming skills. Just as a short remark: To be able to really forget the PhD and relax, I would suggest to also finish all bureaucratic procedures (e.g. hand in written copies of the thesis to the university library, fill out some forms, etc.) that might be necessary after the defense, so that you can start into the holidays knowing that you will start a new chapter in your life afterwards and that the PhD one is completely finished.

Unfortunately this question is too personal for good advice here. User kenning's comment is probably good. Unfortunately, a full break, in a competitive world might be a permanent break and I have no way to advise you about that. But, implicit in the comment cited is the fact that any sort of break from what you are currently doing is probably beneficial. You may need to keep  active in the job market though, just as protection. Even if you were to immediately start a new position, it would represent a break and might bring you peace and time to think. (more)

My go-to exercise in grad school was bicycling. You can do it gently or intensely. It is good for getting the blood flowing. Currently, I use Tai Chi because it is explicitly a mind-body fusion exercises. If I do it well, I need to put aside the worries of the job and the world and focus the energy. Not necessarily aerobic, though. But what really needs rest is your brain. A counsellor might be a great way to explore your real needs and get out of potentially "destructive" cycles.

I took about 3 months off. I just did not very actively search for positions and when I found one ask for plenty of time to prepare (the start date was basically "whenever you can make it" from my employers point of view).
It was amazing. Yes, in that time I was in the process of interviewing (but I had not applied for more than this one job yet, that just was too good to not try) and then packed up my life and moved to another country. But I also met with friends, slept in, decluttered my stuff, data and brain, visited family and just took time to recover.
Everyone so far has reacted very positively to this fact. My family and friends admit that it made me a more happy, balanced person. My colleagues and supervisors (old and new) encouraged me to take the time off and stated multiple times that this was an appropriate and good thing to do. Even the lady at the office where I had to sign up as unemployed completely understood the situation and promised me not to bother me for at least three months, as long as I kept making progess with at least one application.

It is good that your story ended positively in all respects. Unfortunately it can't be extrapolated. Too many employers won't go along.

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Undergrad research program application: should I say explicitly that I want to make connections?
I'm applying to a summer undergraduate research program at a top research university (in US), and the application asks for a statement of purpose. In particular, I need to talk about why I'm applying to this program.
One obvious and strong reason is that I want to work with professors there, make good impressions, and potentially work with one professor there during my Masters and/or PhD program - I'm pretty sure that at least 75% of all applications have this in mind.
Is it acceptable to explicitly mention this? I'm in dilemma because, while mentioning this conveys what I want, it might make me seem overly intentional.

I doubt that will make or break your application, though it sounds a bit like pandering. Don't think of it as a backdoor way to get into that university's graduate program, though. For that it won't work. There is a defined process for graduate applications.
But such a research experience will be a plus in any graduate application in the US and likely elsewhere.
I you mention any professor by name, make sure that you know what it is that the actually do, not just that they are prominent. Look at some of their recent work, for example. And make sure that you find that interesting.
Make sure that the SoP says what it is intended for. Express you goals (learning goals primarily) for this program but also for longer term goals. Do you intend to work toward a doctorate eventually? An academic career? Are you seriously considering a particular subfield?
In fact, if you think about it, you can say something similar to what you suggest without saying it explicitly if you are a bit subtle. Note that "connections" are important in academia even when you don't have an ulterior motive at the moment.


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Equipment/Computer Budgets for CS PhD Students
I plan on attending graduate school in computer science next year (fall 2020 semester).
In a computer science (or related field like software engineering) PhD program, is it standard to furnish graduate students with a "work computer", separate from a personal laptop purchased out of pocket, for conducting research?
I want to know if I'll have to shell out some cash for a beefier laptop or if computing resources are usually provided. If so, what computing resources are available (either as cash/budgeted money or as computers PhD students can use), and where does the funding usually come from?

Where are you located?

What do you think you'll need a beefy laptop for? I did most of my PhD thesis on an old Optiplex desktop with Linux on it. I'm guessing unless you won't actually need that much computing power unless you specialize in GPU programming or something.

@Buffy I'm located in the U.S.

@AlexanderGruber I did an REU (research experience for undergraduates, a program for US undergraduates interested in research, funded by the NSF), and some program attendees did some fairly heavy work on their personal laptops; I was able to work remotely. We were not provided with separate personal computers for the program. We did also have access to a cluster as well. Because I haven't yet entered graduate school, I wasn't quite sure how computing resources worked when one is a graduate student.

This answer is based on my experience in France and Ireland. I would assume that it's similar at least in other European countries [please edit or comment if I'm wrong].
In computer science PhD students are usually provided with everything they need to do their work including (at least) a desktop computer, office space, and generally there is also a budget for traveling to conferences. Depending on the country they might have the status of staff member or not, but even if not the working conditions are very similar to those one would expect in a regular job (well, an academic job, don't expect too much!).
The budget related to equipment/travel is usually a part of the PhD funding which is given to the institution, as opposed to the main funding which is a grant or salary given to the PhD student. The budget for traveling/accommodation is usually the most limited part, it might even happen that there's no budget at all for this. It's a good idea to ask the supervisor about it at the beginning in order to submit papers to conferences in a sensible way: it's a shame to have a paper accepted but find oneself unable to attend the conference.
PS: in terms of computer equipment, in computer science it's also common to be provided with an access to some kind of high performance cluster.


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How do you Protect Your Academic Work?
I'm a masters degree student trying to figure out how publications and co-authorship work.  I know that the school/PI retains legal ownership of any monetary profits that may result from the work, so please don't mention this in your response as it is irrelevant to what I'm asking.  I WANT TO BE PUBLISHED AND DO NOT CARE ABOUT MONEY.  I just want to ensure that I get academic credit/recognition this time since some of my work was previously passed off as another student's work in a different lab.  I'm concerned because the new PI and another professor working on the project seem to want me to do all the grunt work/data collection, but according to the previous student that worked on the project, they prefer to keep the analysis to themselves even though I'm willing [to try] to learn how to do this myself...  What protections do student have against others taking credit for their work, not giving them even partial credit/co-author status, and/or allowing another student to take credit who didn't help?  Should I mail copies of my data to myself and retain a sealed copy?  How do/did (when you were a grad student) you guys protect yourselves?  Please list some measures/methods you use to prove that work you did was done by you as opposed to someone else in the lab.  As things stand now, it seems like my PI, in theory, could hand over my work to another student who he likes more, who's viewed as younger/more promising, or who has a rich/important Daddy.  Not saying he'd do this, but hey, its happened to me before, so yeah - just looking for some solid concrete measures I can implement to protect myself.  I don't feel comfortable discusses this with my PI for reasons that should be obvious to anyone with a modicum of common sense, so please don't refer me to my PI.  If you can't/don't want to help, fine, but please don't down vote me as somebody else may have some insight that would help me.  Thanks.

Trying to be bullet-proof "against" one's advisor is a hopeless cause, I'm afraid. Not that one shouldn't object to abusive advisors... but perhaps the correct analogy is to a "mugging" (in U.S. English sense: essentially armed robbery, but in any case by a  tough scary person... to whom one gives their wallet...). How to "guarantee" against this? The only way is to "stay out of that neighborhood", but if the 'hood is "academe", then it's not truly possible. The point is that one needs a good advisor... then, how to find?

Where are you located?

Please improve the formatting and remove the ranting from the question.

I don't feel comfortable discusses this with my PI — You need a new PI, for reasons that... how did you put it?... should be obvious to anyone with a modicum of common sense.

@paulgarrett if the 'hood is "academe", then it's not truly possible. — Fortunately, the hood isn't "academe".

In my experience, the best way to ensure that you get appropriate credit for your work is to work with trustworthy people.
Now, whether somebody is trustworthy is not always easy to determine (especially for a new graduate student), and there are also both genuine mistakes and genuine differences of opinion and criteria that often occur.
Nevertheless, there's a good heuristic that can help you test the waters early.  You can lay claim to your work by finding opportunities to share early results.  If you're in a software-related area, you can keep your projects on GitHub, where there's a nice public record of everything.  If you're in a more experimental area or if sharing on GitHub doesn't work, then there should be opportunities with student conferences, internal group meetings, etc., to present work, even in early stages.  These often exist explicitly for students to get feedback on work that's not yet ready for a proper publication, so the stakes are low. And even if it's an internal presentation rather than to the general scientific public, that will still greatly expand the group of people who know what you've done and what sort of value you're contributing.
If you get encouragement and opportunities, that's a good sign; if you get ongoing evasions and push-back, that's a bad sign.
Bottom line: the best way to ensure you get credit for publishing is to start "trial publishing" as soon as you've got interesting work to share, and see if you're in a supportive culture or a controlling one.

And, yes, you don't need to "defend yourself" against honorable people, and, at the same time, it is nearly impossible to defend yourself against dishonorable people who are much more powerful than you. Just stay away from them. There is no (successful) strategy to defend yourself against dishonorable-but-powerful people.

Github won't help.  I recall there was a scandal recently where sexist claims of misattribution were based on poorly interpreted github records.

@paulgarrett A key goal with my answer here is to try to give people faster means of diagnosing whether they're dealing with an honorable or dishonorable person.

There are likely to be policies protecting trainees at your institution, and you should review those - including process for lodging complaints about scientific misconduct (which could apply to some of the behaviours you are worried about).
You should also review policies about handling of data (of the sort your work with) to be sure that taking raw data off-campus is allowed (in a medical center, for example, this could be grounds for dismissal even of a Professor); honestly, some of your ideas for self-preservation seem bizarre.
Constant worry about being scooped will not serve you well in an academic career; there are no guarantees but if you demonstrate integrity and earn the respect of others, you will be in a much better place to address unfair treatment if it occurs.

First of all I just want to note that your school very likely retains legal ownership of any monetary profits that may result from your work.
As for students plagiarizing, it happens but I wouldn't worry about unless it happens and you need to deal with it. I've never dealt with a plagiarizer who was smart enough to continue fooling people once they were investigated. The main problems arise where they are two sides to the story, i.e. not overt plagiarism, but where both of you worked on the results. Then most of your ideas for how to protect yourself won't work anyway since there will be conflicting evidence to create doubt.
As for faculty stealing the credit, this is basically hopeless. The advisor indeed has the power to do everything you fear they might do, and you have no power to stop them. You are there to be taught by them as a subordinate. They are both your supervisor and evaluator. You need them to be on your side, where they think you are an asset and want you to succeed and get credit you deserve. Research is very much a social-network-based system so you need them for a lot more than just a fair supervisor. As others said, choose carefully.

In my experience (in universities in the USA), students have the same rights to inventorship as do their faculty; questions of inventorship are determined by US patent law, not university policy. My impression is that most universities divide the inventors' portion of royalties equally among the inventors (with no preference given to faculty over students). For example, https://www.umsystem.edu/ums/red/oipa/studentip-faqs and https://www.invo.northwestern.edu/invention-disclosure/student-inventors/student-invention-policy.html

@Argalatyr Inventorship is different than ownership; inventors commonly give their ownership rights over to their employers (as part of their employment contract) in return for resources such as funding and lab space. Hence students may have more rights than faculty, if the students is not being paid to produce the invention and is not using university resources. However in this case, the student is asking about work done in the faculty member's lab under the faculty member's supervision. Sounds pretty likely the university would claim ownership. Your links appear to cover all this.

What I saw in the OP seemed focused on academic credit, not so focused on ownership (which is where your answer seem to go). Therefore, I focused my comment on inventorship, i.e. credit for the discovery, but as you say the resources I pointed to also cover royalties etc.


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How does one know that the field of research they are in is the best fit for them if they are average in it?
I love computational materials science. I was an experimentalist and involved in some Computational work during my masters degree. I did not not enjoy the experimental part. I did not enjoy the lab politics, the dependency on others. Also, I did not enjoy the significance of the work I was doing. Most of the time, it was just reporting the experimental data without trying hard to find a theoretical reasoning.
On the other hand, I was fascinated by computational research. The only limitation was I myself. Implementation of ideas, thinking about the fundamental physics that's occuring, and getting to theoretically predict the results was exciting. Thus, I was extremely determined to do a PhD in computational aspect of materials science for this particular reason.
Fast forward 4 years, I am done with my PhD. And I have published some papers on my research area. However, I did not do anything substantial during my PhD. I did not get any awards, nor my research got any media coverage, applying for grants with my advisor was always a nightmare. Contrarily, my colleagues who work on experimental aspect of the research, find it much easier to publish, gets multiple awards, easily gets grants approved, have media coverage for every "groundbreaking" stuff they develop.
Now that I have completed my PhD, I sort of envy the experimentalists and regret not being one. I feel that being average in computational materials science is disasterous as compared to being average in experimental research. I feel that I made a wrong choice 4 years ago when I decided to apply for a computational PhD than an experimental one.
My question is: How does one know that the field of research they are in is the best fit for them ? And how to be content with one own's research field and not feel resentment that probably I am not a good fit for this field?

Do you enjoy doing the actual research?

Yes, I do. But, I feel dissatisfied with the quality of work I can manage. There are researchers who are leaps and bounds ahead in their Research. I will never able to match them. While, Research in experimentation is more about the resources one has. Even a mediocre experimental research receives more attention than a theoretical work.

Well, for the comparisons to others in your field, please see How do you come to terms with the fact that you might never be among the best in your research community? For your comparison with your experimental colleagues the saying about how the grass is always greener on the other side comes to mind, but sure, there's always the reality that some topics and approaches are hotter than others.

"I love computational materials science." End of discussion.
If you can do what you love you can have a marvelous life. If you can't do what you love you will have a harder time.
But, with time, hard work, and experience you will likely improve. There will always be people better than you at whatever you do. Don't worry about it. Don't envy them. But try to form collaborative relationships that might, in time, let you work with some of the superstars.
As to your colleagues who seem to have an easier time: they may feel quite differently.

Well, in my opinion, there is an element of chance to getting awards, grants, and recognition. Even citations have a bit of chance to them. Every now and then, a researcher will hit a lottery paper early in their career. They are working on the right problem at the right time. On the other hand, the field you work in might catch fire. Those researchers working on neural networks prior to 2010 were largely making contributions in a relatively thankless field. How that has changed.
I had a mentor put it to me very succinctly- Any given decent paper has a chance of being noticed by the wider community. Do enough decent work and you will be noticed.
But from personal experience-
I know the field I work in is the field for me because I gain a large amount of satisfaction from it. I enjoy writing papers and submitting them to journals. I enjoy reviewing manuscripts from those journals. I enjoy going to conferences and talking with other researchers in the field. I enjoy thinking about problems in my field. I enjoy talking with practitioners and policy makers about those problems and possible solutions as well.


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MS CS with thesis after online MS CS
Due to some family conditions during my undergrad days, I could not focus completely on my studies. As a result, I have a mediocre GPA (2.7-3.0). In order to overcome this, I have decided to enroll for an online terminal MS CS program which I intend to complete within 1.5 years.
Provided that I am able to excel in the online course, is it possible that I can leverage the degree to get admissions to a top 10 MS program in computer science with thesis option?

Certainly it is theoretically possible, but it may not be possible in practice. There are two issues to consider, even beyond your unknown performance in the online degree.
The first is that the probability of any single candidate getting in to a "top ten" program is effectively zero. There are too few slots and too many well qualified candidates. The competition for entry is intense. Most of those candidates will have near perfect academic records. You will need some "edge" that will appeal to any admissions committee. An online degree may not be that edge.
Second, an online degree usually gives you little personal relationship to professors and, probably, very little feedback on your work. If the online degree is largely "passive" (videos, readings, and exams), then no one really has an idea of your potential since you interact with them so little. There are a few programs that are different, of course, such as Open University UK, which does provide tutors for the students, but even there, little interaction with professors.
That doesn't mean the an online degree is bad for you and may be one of your only options. But if you set your sights on a very narrow target for it, then it will be very difficult to hit that target. Think about how you can widen your goals or, alternatively, choose a more effective path to them. Say a path that lets qualified people see your potential and give you great letters of recommendation.


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What is the name for the copies of a paper that you receive once it's been published?
After an article has been accepted, all edits finished and finally published, some (many?) journals mail 10 or so printed copies of the completed article to the author. Not full copies of the entire journal issue but just the single article. I believe traditionally this was done so an author could prove to their institution that the article was indeed accepted and published. This is still standard practice for journals in South Korea where I live. I'm aware of the Korean word used for them but colleagues have been asking me what to refer to them in English and I couldn't offer an answer.
Is there a special name in English for these copies?
The best I could think of was just "excerpt".
Other terms I've found that don't seem to fit: "advance copy", "proof copy", "galley proof", "final proof"

They are called offprints.  From Wikipedia:

An offprint is a separate printing of a work that originally appeared as part of a larger publication, usually one of composite authorship such as an academic journal, magazine, or edited book.
  [...]
Offprints are used by authors to promote their work and ensure a wider dissemination and longer life than might have been achieved through the original publication alone. They may be valued by collectors as akin to the first separate edition of a work and, as they are often given away, may bear an inscription from the author. Historically, the exchange of offprints has been a method of correspondence between scholars.

The name I know these by is "reprints" or often "author reprints" in the context of those printed for the authors' use and distribution.
These are prints in the form of the final published article (rather than a pre-published form which are typically called 'proofs' and are often not a completely final version; these in my experience are always digital).
Other examples:
Science
ACS
AHA
LWW
Although "reprint" seems to imply they are done after other publishing, in my experience they are offered immediately to authors, though many journals now simply provide authors with PDFs to distribute.

I agree with this answer. Phys Rev and Appl Phys Letters specifically called them reprints on their forms, at least in the 80’s-00’s when reprints were actually desired. Of course, other fields may have called them differently. One person I worked a summer with monitored the spread of Xerox machines by the steady decline of reprint requests through the 70’s. By the early 90’s one got to zero-reprint...


text:
Worth to fight examination office for English transcript of records?
I am finishing up my B. Sc. degree and thought it would be nice to have a fully English transcript of records (ToR). Although my university already offers an English version, the translations are picked from what lectureres have entered into the database. Consequently, some terms are missing. For example it shows:

Minor subject: Mathematics

Functional Analysis
Klausur: Funktionalanalysis(*)
Übungsleistung: Funktionalanalysis(*)

(*) denotes that English translations are missing

You see that it is even inconsistently translated. The overall second bullet point is in English while the "sub bullet points" for the exam ("Klausur") and the tutorials ("Übungsleistung") are in German.
How important is it to have a fully translated ToR for B.Sc. for applying internationally?
The question "Sending non-fully translated academic transcripts for US PhD admissions" is related, although currently my ToR is not yet printed. The exam regulations are in my favor. They state that I have the right to request an English copy. However, I have been told that people responsible for fulfilling them are not fond of translations.
Is it important enough to make the examination office not like me anymore?
Especially, if I stay for my M. Sc. at the same university.

If you are staying for the M.Sc., I wouldn't worry about the B.Sc. transcript, which nobody will look at, but about your M.Sc. transcript. And I guess with that one, you can be a bit more proactive and make sure that the english names are entered into the database correctly while you take the courses, something which usually is done by the professors or their assistants, who are generally more proficient in english than the administration, and who simply might not know that filling in the english name is important if the course is in German anyway.

"I have the right to request an English copy."  I am pleasantly surprised.  I thought students usually had to pay for a translation or certification thereof.

Your situation reminds me of this question. Hopefully your university will not cause you as much grief as they did to the OP in that question. In general an English transcript can be useful in the future - it’s hard to predict exactly when or where you’ll need it, and life takes us down unpredictable paths sometimes.

How important is it to have a fully translated ToR for B.Sc. for applying internationally?

For most English-speaking universities, it is essential to have translations to English.

Is it important enough to make the examination office not like me anymore?

In my opinion, it is fine to ask them to follow university regulations, even if they do not like it.  So, yes.

Is it really essential, though? I find it difficult to believe that a graduate admissions committee in the US would contain nobody who can read German or use Google Translate.

@JeffE The administrator who decides if the application is complete is likely to only check if the transcript is accompanied by a translation.  I won't claim nobody has been admitted without a translation.

I now got the official translation without any hassle (+ the database has been updated for all future students!). It just took me one polite e-mail mentioning the university regulations.

I cannot comment on the regulations at your specific university.
In general, however, I do not think a university is expected to translate its degree certificates and transcripts into other languages. If you need your certificates and transcripts to be evaluated by people or organisations in a different language, you should obtain a certified translation from a professional translator or translation service, and then send that translation with a copy of the documents in the original language (NB: some places demand that this copy be issued from the awarding institution in an unsealed envelope; most places, however, will be happy with a scan/photocopy in the first instance, followed by seeing the originals if/when you visit them in person).

I agree that universities cannot be expected to translate into every other language. But English is the de facto language of science, hence, I would welcome more universities providing in-house translations into English. Anyway, that's just my wishlist. Let's see what the examination office replies to my inquiries. It turns out that they already have escalated the issue among themselves higher than I expected.


text:
Lack of mathematical work during PhD and coping up with the requirements of postdoc positions
I am a recently graduated 31 years old PhD in a STEM field. I have been applying for postdoc positions for the past few months, and have received rejections from almost all of them, with few yet to respond. With the academic year coming to an end, I don't have any hope of getting a position and I will continue as a postdoc or Research assistant in my PhD group.
However, one common reason mentioned in all the responses to my applications was that I don't possess the required mathematical and programming skills to work on the research field. My PhD research involved using Fluent CFD software to model has flow in a nozzle. I did not develop any code for that. I used python programming to develop different nozzle geometries and used it to study the flow.
I did not take any Finite volume method or Finite element method course or fluid dynamics course in my undergraduate or graduate school as my supervisor told me to self learn the concepts. I have published 4 papers in decent journals.
However, all the postdoc positions I apply to require code development for CFD and having academic background with the numerical methods. And since I don't have any experience with code development, I don't know if I will be able to do the job considering my lack of formal training.
Is this dilemma expected after PhD? What should I do to improve my chances in getting a position?

Well, did you self-learn these concepts?

Yes. By learning, I mean I know how these numerical methods work. Did not do much excercises. But worked on some simple 1d-2d problems during the learning process. I think that's what is done during the coursework for these courses. But, research in the field requires expanding the fundamentals to complex systems like 3D or with complex boundary conditions. I have used commercial software, so I did not develop any codes in my research. The postdoc positions want tangible evidence showing the experience in such code development.

But so then their opinion of your application is justified: If they're looking for someone who has actual experience with code development and 3d simulations, then you're not qualified for these jobs.

If you have the knowledge, but not the "qualification" in those areas, make sure that your letters of recommendation say that. If you don't have the knowledge, it might be a bit easier to improve Python skills than math skills.
Alternatively, you might be able to get someone to tutor  you in the math area and make sure your advisor and other recommenders know to mention it in the future.
A third option is to focus your statement of purpose and other application materials on your knowledge of these things, rather than just listing courses.

I think I have the necessary knowledge to do the job but I never had to work with theoretical development before. So, I don't know for sure if I will be able to do that. But, I thought, once I get postdoctoral position with the job description, I will have a definite goal to apply my whatsoever theoretical skills I possess.  Isn't a postdoc supposed to learn new things during their job?

This. It sounds as though you do actually have the skills they're after (you understand the numerical methods, and you can program), but you don't have a way of providing evidence of this. That's awkward, but perhaps better than not knowing the stuff.

To improve your chances of getting a postdoc position you should apply for positions for which you have the technical skills that are required. It sounds like you've applied only for positions for which that isn't the case. In such cases it's difficult (but not impossible) to get the position.


text:
How do I know a paper is indexed by SCI or ISTP from the query result of Web of Science?
I learnt from a blog (here, IN CHINESE) that we can tell a paper indexed by SCI or ISTP via IDS Number. More specifically,

SCI: IDS Number beginning with digits, such as 334VK
ISTP: IDS Number beginning with alphabets, such as BF1NB

Is it correct?
As an example, I attach the full record of a paper (here),
Record 1 of 1
Title: Network information flow
Author(s): Ahlswede, R (Ahlswede, R); Cai, N (Cai, N); Li, SYR (Li, SYR); Yeung, RW (Yeung, RW)
Source: IEEE TRANSACTIONS ON INFORMATION THEORY  Volume: 46  Issue: 4  Pages: 1204-1216  DOI: 10.1109/18.850663  Published: JUL 2000
Times Cited in Web of Science Core Collection: 3430
Total Times Cited: 3843
Usage Count (Last 180 days): 6
Usage Count (Since 2013): 90
Cited Reference Count: 14
Abstract: We introduce a new class of problems called network information flow which is inspired by computer network applications. Consider a point-to-point communication network on which a number of information sources are to be mulitcast to certain sets of destinations. We assume that the information sources are mutually independent. The problem is to characterize the admissible coding rate region. This model subsumes all previously studied models along the same line. In this paper, we study the problem with one information source, and we have obtained a simple characterization of the admissible coding rate region. Our result can be regarded as the Max-flow Min-cut Theorem for network information flow. Contrary to one's intuition, our work reveals that it is in general not optimal to regard the information to be multicast as a "fluid'' which can simply be routed or replicated. Rather, by employing coding at the nodes, which we refer to as network coding, bandwidth can in general be saved. This finding may have significant impact on future design of switching systems.
Accession Number: WOS:000088206200002
Language: English
Document Type: Article; Proceedings Paper
Conference Title: IEEE International Symposium on Information Theory
Conference Date: AUG 16-22, 1998
Conference Location: MIT, CAMBRIDGE, MASSACHUSETTS
Conference Sponsors: IEEE, Informat Theory Soc, Natl Sci Fdn, NASA, USN, Off Naval Res, AT&T, Motorola, Qualcomm, Lucent Technol, Bell Lab Innovat
Conference Host: MIT
Author Keywords: diversity coding; multicast; network coding; switching; multiterminal source coding
KeyWords Plus: MULTILEVEL
Addresses: Univ Bielefeld, Fak Math, D-33501 Bielefeld, Germany.
Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong, Hong Kong, Peoples R China.
Reprint Address: Ahlswede, R (reprint author), Univ Bielefeld, Fak Math, D-33501 Bielefeld, Germany.
Author Identifiers:
Author  ResearcherID Number ORCID Number
WANG, HUAN  A-1155-2009
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publisher Address: 345 E 47TH ST, NEW YORK, NY 10017-2394 USA
Web of Science Categories: Computer Science, Information Systems; Engineering, Electrical & Electronic
Research Areas: Computer Science; Engineering
IDS Number: 334VK
ISSN: 0018-9448
29-char Source Abbrev.: IEEE T INFORM THEORY
ISO Source Abbrev.: IEEE Trans. Inf. Theory
Source Item Page Count: 13

You have to make sure that you are searching the paper of the intended Journal, not the paper which cites that work. This is sometimes misleading.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
How to know if a paper is allowed (by publisher/journal/conference) to be put on arXiv?
I am a 2nd-year PhD student. I have published two conference papers, and now I want to upload a copy to arXiv. I am aware it is common (flexible) for researchers in some areas (e.g. machine learning) to upload their papers on arXiv; However, it is uncommon in my research area/targeted publications, but I think it would be useful for wide-access (my research area: algorithm-hardware co-design for machine learning)
I wonder how to know If a paper is allowed to be put on arXiv?

Do publishers have rules against that? Or It is the Journals/conferences have rules against that? Where can I find them (generally)?
Are there any rules on the version of the paper that is allowed? e.g. pre-publication, camera-ready, post-publication etc.

Thanks.

You can look it up at https://v2.sherpa.ac.uk/romeo/ Enter the ISSN of the journal where the proceedings will be published, and read the conditions there. It's made to be clear and easy to understand.

Does this answer your question? What journals do not allow open access to published material?

Check the publisher's website. They should have policies for putting papers on arXiv.
For example here is Elsevier's policy page, and:

Authors can share their preprint anywhere at any time.
If accepted for publication, we encourage authors to link from the preprint to their formal publication via its Digital Object Identifier (DOI). Millions of researchers have access to the formal publications on ScienceDirect, and so links will help your users to find, access, cite, and use the best available version.
Authors can update their preprints on arXiv or RePEc with their accepted manuscript .

So for this publisher the answer is "yes", you are allowed to put papers on arXiv as well as update them once the peer review process is complete.

I wonder how to know If a paper is allowed to be put on arXiv?

You can put papers on arXiv before signing any copyright waiver, then papers are always allowed. (Albeit some venues - surely very few, if any - may refuse to publish papers already on arXiv.) When a paper is already published, you need to check the publisher's rules, which vary between publishers.

Thanks. Do you mean "before signing any copyright waiver" with the publisher? How could I find out if a venue refuse papers already on arXiv?

@LeiXun Copyright waiver with the publisher, yes. To find out if a venue refuses papers on arXiv, read their website.


text:
Preparing for careers outside academia
I'm currently beginning a master's program in physics. I intend to pursue a PhD after this. I am interested in theory and at this point I think I want to explore high energy or stat mech and/or its applications. I understand that it can be quite difficult to get a good faculty position even after a few years of post-doc work. I am also interested in fields like economics and finance, and I understand that a number of physics (and math) PhD grads end up working in fields like quant finance, corporate finance or consulting. I've taken some basic courses in economics and finance (all online), but  I would like to know how to actually prepare for such careers. I'd definitely love to work in academia but I'm also a little scared (and realistic, maybe) because of the sheer competition there is, and how uncertain it seems to be.
Preparation could be in terms of taking on extra courses, or taking up licenses/certification exams. If there are internships I need to do, how would those work out? I'm quite clueless at this point, but I hope I'm not too late.
Thanks!

This is off-topic here since you are asking about jobs outside academia.

Learn to code -- being able to put your mathematical ideas/solutions into something that can be physically implemented will make you very valuable.


text:
Planning for post PhD career
I'm currently a Master's student in physics and I will begin my PhD apps in the next few months. I should graduate from my Masters in Spring 2022. I'm looking to do theoretical work. I'm applying to places in Europe - specifically UK, Germany and France, and the US. I'm leaning towards a European PhD because of the length of the PhD in the US and because I don't particularly see myself living in the US in the long term. Within Europe I'd prefer a PhD/job after that in the UK because I think my girlfriend may also be getting a relatively stable job there.
My question is the following.

I understand that there is a disadvantage to apply to the US for postdocs and such, with a UK/European PhD. How bad is this?

How likely is it that I can get some non-Academia job in the UK after my PhD (if I pursue it there, or elsewhere in Europe)?

I guess what I'm worried about is getting a European PhD and neither being able to get jobs in academia nor in industry (either of which, preferably in the UK). My first preference (at this point) would be to do a post doc somewhere in Europe but I'm reading a lot about the job market in academia and I'm realizing that a stable, permanent job in academia might be a lot harder than I used to think, so I'm just weighing my options here. By industry jobs I also mean jobs outside of physics- such as those in finance and data science and what not.

Please ask one question per post.  Questions about non-academic jobs are off-topic.  Access to the US job market is mostly a matter of visa availability, which could easily change during your PhD.  Predictions are useless.


text:
How does taking the Physics GRE (and the General GRE) affect my PhD apps in 2021?
I'm a Master's student in physics and I will be applying to PhD programs in the US and Canada (and other places, but that's not relevant for this question) for Fall 2022. Generally, I understand that I need to take the GRE and the Physics GRE and submit these scores as a part of my application. However, some schools decided to waive this requirement before the pandemic, and because of the pandemic for many of my friends who applied for the 2021 admissions cycle, they were not required to take the GRE or the Physics GRE. For the 2022 admissions cycle, many places in the US and Canada have made it optional or 'not required.'
I would like to know how my application would be viewed if I send my Physics GRE scores. My main motivation to do so is because there are some subjects that I have not done very well on, and doing well on the Physics GRE might help balance that. However, some schools on my list want me to 'explain why submitting the Physics GRE score is beneficial to my application' so it's almost like they don't want applicants to take the test? But their formal policy is still that it's 'optional.' So I'm very confused how to proceed.
tl;dr Will I be adversely affected if I choose to send in GRE and Physics GRE scores, or would I be worse off by not sending them in?

If the system is fair, which I can't guarantee, if the GRE is optional then it won't be used, formally, to distinguish between students. But it is hard to say what goes on in the minds of individuals on a committee.
But in particular, it shouldn't (in a fair system) be held against you if you don't submit. That does make the other factors more important in their decision, of course, since they have a bit less information to go on.
If your other factors are superlative and your GRE's are not, then don't submit them. But if you think you need a boost and your GRE's are great then submit them. But I can make no guarantee.  Mostly people try to be fair, but the pandemic has disrupted a lot of things.
I think that some people are starting to question the predictive power of the GRE exams in choosing researchers. In the US and maybe Canada (no experience in the Great White North), letter of recommendation are probably better predictors when sent by people who know you well.


text:
Why I should prepare a presentation for each journal paper I have?
My supervisor asked me to prepare a presentation for each journal paper I have with him. He asked the same for each other student he has (PhD and postdoc).
This seems to me (and to all other students) strange and nonsense. Why would you ask your PhD students and postdoc to prepare a presentation for each journal paper they have?
I asked my supervisor and he told me because I told you so.

I guess I'm a bit surprised you don't already have a presentation for each journal paper, but I don't really see the point of speculating. It seems like there's a pretty serious breakdown of communication with your supervisor which is a lot more important than the reasoning for doing this.

Well, or the students who need to go give interview presentations if they want to get jobs in the future...

If you are producing twenty papers each year this seems over the top.  I would say preparing sides for the best four or five papers is plenty.  How many papers are we talking about?

@EdV Please post your comment as an answer.  It's the right answer.

@BryanKrause whether you have any need to present journal papers varies heavily with field.  Certainly in my bit of experimental physics you've got a good chance of a presentation related to one or more paper(s), but this could either be  a preliminary step, or a summary of several papers as easily as it could be a 1:1 match

@ChrisH At a minimum you should be presenting to peers in your own institution, faculty in your own institution (your advisor and thesis committee, at least), and at least preparing to present to anyone you want to hire you in the future. Sure, 1:1 may not always make sense but it seems OP's advisor thinks it does.

@BryanKrause our plentiful internal presentations during my PhD were either a sort of rolling update (often tacking slides on to the end of a previous set which could be referred to as required - anyway these mapped to projects rather than papers) or practising for conference talks.  Things are similar here, though the internal updates are a little more formal.  My last group was small and our internal stuff wasn't really presentation style. With our work, 1:1 doesn't make sense, but of course you're right, it might in the OP's group, even if only in the advisor's head.

"he told me because I told you so" -- well, there's your answer, isn't it? What are you expecting from us - to read your advisor's mind?

I think the real question you shd ask is, how many slides per paper.

@lalala Why is that? Why supervisor should micromanage the number of slides? PhD student  is an independent researcher to decide. One should not normalize everything. And the supervisor gives him/her this freedom.

@yarchik you can also ask for how long. It doesnt make sense to prepare 100 slides for a 5 min overview presentatione, neither does it make sense to prepare 10 slides for a 1 hour plenary talk. To frame is absolutely vital, and the researcher can not decide since usually one is bound to the format of the venue.

What I find a bit surprising about several comments and answers (and also about the supervisor's suggestion) is that they apparently take it for granted that one should give the same talk multiple times. Apart from the obvious benefit (time saved during preparation) this has also multiple disadvantages, and I would rather recommend against it.

Academics give a lot of talks. Having a presentation ready to go for each paper is very unlikely to be a waste of time. You might not end up using the deck "off-the-shelf," but once you have a bunch of good slides, it's easy to slice-and-dice them as needed. Further, learning to make good slides and give good talks is one of the goals of grad school, so there's a good opportunity here to learn from your advisor.
In fact, one "trick" I've learned is that instead of e-mailing someone a screenshot or screensharing a plot during a meeting, I'll take the time to copy and paste it to a slide and add a few bullets explaining what the result shows and what the takeaway is. Then when I need to form a slide deck, I already have a few key slides ready to go. This almost never turns out to be wasted effort.

I asked my supervisor and he told me because I told you so.

Well, that's unfortunate. I see three explanations here. One, and the most optimistic, is that this was a bit tongue-in-cheek; i.e., you will soon see why we're doing this, so there's no need to explain now. Another option is that your supervisor is just dismissive and rude.
But a third option is that your supervisor thought you were being dismissive and rude of him; i.e., he made this perfectly reasonable request and in response, the term is demanding explanations and second-guessing his judgment. (I assume that the downvotes on your question are because others here have also detected that attitude in your question and are responding accordingly.) If this happens to be the case, I would suggest re-evaluating your relationship with your advisor: you are, after all, there to learn from him (or you don't trust his judgment and should seek another advisor).

In general, I agree the supervisor should answer reasonable questions; if they have some reason for not doing so (like being annoyed at OP's tone), they should address that separately. But this is just one report of one brief interaction, so I'd hesitate to say that anyone is "failing at their job."

“(or you don't trust his judgment and should seek another advisor)” I think the question comes from a place seeking to understand if this itself is a red flag and a reason not to trust the advisor’s judgment. Which seems plausibly reasonable; refusing to explain things is an unexpected teaching style...

That's a good interpretation, and the interaction described here is indeed troubling on both sides (the student thinks the advisor's advice is "strange and nonsense", while the advisor tells the student "because I said so"). All I can say is that this particular request does not seem strange or nonsense to me; without more information, I could not form an opinion about the advisor's judgment.

Other good answers. Check.
I'd guess that there is the implicit issue that "preparing a presentation" doesn't mean just "being able to stand at the front of a room and explain things on a whiteboard or blackboard"... but means "prepare some slides, in advance".
So, yes, preparing typeset slides is a task. Yes, there are formatting and other issues in addition to the scientific/intellectual issues.
Still, apart from the formatting issue, I do think it is worthwhile thinking about content, big points versus small, and a time constraint, to "sell" your work. Extreme case (as someone mentioned) is the "elevator pitch", where you have a ridiculously small amount of time to "sell" your work to some big-shot who can offer you a job or otherwise affect your career arc.
Job talks are a thing.
And, yes, if you want your advisor to "promote" you when they give talks, it is reasonable for you to give them "promotional material". :)

I'll focus on why it is valuable to do such a thing. A paper in some fields, such as math or theoretical science is very detailed. The detail is essential, but getting lost in the details doesn't necessarily lead to insight. What is the "deep meaning" of this paper? Why is it important?
Having written the paper, it may not be immediately obvious what the answers are to such questions. Reviewing the work and thinking about it again can be valuable if you focus on the important questions. Insight can even lead you to ideas you missed earlier that might lead to future work.
A short presentation "about" the paper needs to avoid the detail to be effective and to focus on the insights that it leads to. For that reason alone it is worth doing, never mind that offending your supervisor is a bad career move.
My previous group never asked students to do this, but we did ask them to prepare an "elevator talk" on their research: something that would explain the essence and importance of it in two minutes.

It's probably so that you (or him) can present at any opportunity.
You might be thinking: "If there's already a paper why bother presenting it? Can't people just read the paper?" Some people are more likely to go to a presentation, more likely to pay attention to a presentation, and more likely to remember you as a person when they watch you present. Self-promotion is very important in science, and doing good talks and presentation is a great way to get your name out there and network.
It's also a way for you to get some practice presenting things in general. Incidentally, when you do your PhD defense and/or apply to jobs, you will be asked to present your research, and a good presentation can go a long way. So your advisor is helping you get started on preparing for this.

As every other answer here as noted, all the other answers here are great. But I'm worried about this pattern of communication between your supervisor and you:

I asked my supervisor and he told me because I told you so.

Let me suggest some follow-up questions for you to ask your supervisor, best by email so that you have a documentary trail:

What format should these presentations be in? (PPT, PDF, etc.)
What audience should I prepare these presentations for? (introductory, subject experts, translational outreach to industry, etc.)
How many slides should I prepare for each paper?
Should I prepare independent presentations for each paper, even closely-related ones, or should I bundle my research into a few thematic presentations that cover multiple papers each?
Would it be sufficient for me to simply email you a soft copy of my slides, or are you asking me to prepare as if I were giving an actual oral presentation? (i.e. working out the script, patter, timings, etc.)

And finally (perhaps in a follow-up email):

If this occupies all of my time for [insert number of work-weeks this will take], should I be doing that instead of [insert regular work]? Why?

If your supervisor gives you work requests that seem unreasonable, it's not your job to work out what their internal motivation is. It's your job to defend and document why it's an unreasonable work request, and it's their job to convince you that it is reasonable.
While there are many good reasons to prepare a presentation, it is a process which takes time. Every minute of a formal presentation takes between ten to sixty minutes to prepare from scratch, half of which will be oral rehearsal and subsequent changes. A good academic presentation of twenty slides will usually fit a half-hour talk, and will therefore take between five to thirty hours to prepare. Let's say it takes ten.
At my current career stage there are about six half-hour talks that would really sum up and showcase everything I've worked on up to now. Preparing those talks, from scratch, would take me about sixty hours of solid work (at ten hours per talk), which after the usual procrastination factors would occupy two to four weeks or work while I dropped everything else. Therefore, if I were faced with a request like that from my supervisor I would not entertain it, because I can't afford to spend an entire month on a relatively unproductive activity, and I would document that decision to explain it to whatever committee I need to explain it to.
(Having said that, I have actually been presenting my work regularly, so I do have a good cache of slides built up. I'd have to do very little preparing from scratch. If I really were asked to put all my work together into a mega-presentation, I think it actually would take me two or three days to do, so it wouldn't actually be that great an imposition.)
So, over to you. Work out how many slides you are being asked to prepare and estimate how long it would take you. If you run the numbers and find that you can finish it in a day or two, it may well be easiest to just get it done (and move on as soon as possible). But if you find that it would take out a significant chunk of your time from your work then defend your work and tell your supervisor -- all in writing -- that without a very compelling motivation you're not willing to jeopardize your research progress. Be ready to fight if you must.

My leader once asked me, not to prepare slides but to write yet another project proposal. I responded with an e-mail containing all my current tasks in numbered bullet points, noting that I had prioritised the tasks myself and that those numbered higher than 15 were not going to happen. I asked him to re-prioritise my tasks, if he disagreed. The new proposal-writing I believe was number 21. He did not answer. I got off the hook.

Previous answers are good, so I won't reiterate. I should also note that, in some disciplines (e.g. computer science), most publications come from conference proceedings and workshops, which, you guessed it, involves giving a talks.
I should also note that you should be submitting to as many conferences as you possibly can. The best way to get eyes on your research is to present it to a captive audience. This helps develop your academic reputation and lends credibility to your preparedness as an academic. Also - you don't want your job talk to be your first academic presentations. I have colleagues who ran into this issue, and it didn't go well. Giving a good talk is a process of trial and error. Do it early and often. I strived for about one presentation per month while in grad school.

As pointed out in the other answers, having a already prepared presentation (slide, or notes for a talk on the board) is everything but a waste of time. If at the moment you prepare it, you will ask yourself "why I am preparing a presentation that I might never give?", here are a first (down to earth) reason.
When you will defend your Ph.D. and want to stay in academia, you will have to apply for post-docs or permanent position. You will be more successful if you give talks and if you are "famous" (not like a super star, just that you already met and people saw you in action). Usually, you do not have so much time to prepare such a talk, for the following reason:

the delay between your invitation (or your self-invitation) is short.
You may be busy at this period (teaching, grant applications, revisions of a paper).

Having an already prepared presentation for each paper you have is beneficial because:

You can choose the topic in function of the audience or the position you plan to apply.
It is easier and much faster to update some slides/notes than to start with a empty page.
You can make the community aware of your results and you can go everywhere to present them.
The more ready presentations you have, the more talks you will give and the more used to communicate in front of an audience you will be.


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Is it better for me to audit or enroll in a class for independent research?
I plan to conduct independent research on different forms of early childhood education. I have a B.A. in Early Childhood Education but no formal education in research methods or statistics. I was hoping to enroll in a statistics class at a community college (I specifically chose this one because the professor is by far the highest rated and helpful in showing us how to actually conduct research) but the waitlist is full and I probably won't get in if I hope for someone to drop the class. Since I'm not working towards a major (currently, though I do eventually plan on doing a Master's in psychology), would it be best to audit instead? I'm not in a rush so I can wait to regularly enroll next year, though I'd prefer to audit now if it won't make a huge difference in terms of how it'll look to have an audit instead of a grade when I eventually apply for Master's programs.

Officially audit, or just sit in the class unofficially?

You should check whether you can audit a full class. There literally may be no room for an auditor.

In general, auditing a class provides somewhat close to zero information for anyone considering your application in the future. At the very best, it shows you were interested in the subject even though you would get no credit for it. Its not much different than taking an online course with no grade, studying on your own, or just showing up to a class without being enrolled. At least in the US, auditing doesn't even require you show up to class, much less do any work, thus why it has little signal meaning.
So I would suggest that if you audit the class, do it for some other reason than what people looking at your application will think of it. It is reasonable to try to audit if you want to improve your training, prepare for a more advanced class (or just taking the same class next semester), just want to do it for fun (I personally plan to audit stats classes in the future, but that's because I'm at a point that no one cares what classes I take so its just for my own utility and interest), want to get to know the professor a bit better to see if you'd like to work more with them or take other classes by them, etc.
If programs you are planning to apply to strongly value or require quantitative/statistical training, though, auditing a class generally won't do it. This completely depends on what sort of program you apply to, as some won't really care about stats preparation anyway, while others will demand a lot more than 1 class in stats and research methods/design. Now would be a good time to look ahead at what sort of programs you are applying to, what they say they like to see, and plan your courses accordingly.

I agree with @BiranH. Auditing just shows that you were enthusiastic about a topic. If knowing that topic is important for the selection committee, then the question for them is probably how well do you know the subject. Based on my personal experience, most students auditing classes usually skip a good number of classes and do not do any homework or project. Hence, their learning is not significant compared to enrolled students. Therefore, I suggest auditing a class only if you want to get familiar with the topic or you need the knowledge to do independent research.
PS #1. I have an engineering background, but AFAIK research methods and statistics are important courses in humanities and covered by almost every humanities curriculum. So, I think auditing or enrolling in those courses before your starting your MSc studies is just a plus point. Hence, not being familiar with them should not be a negative point.
PS #2. Personally, I audited about ten courses during the last year of my undergraduate and graduate studies and they helped me a lot later in my research, projects, and teaching. If you are near the end of your graduate studies (probably doing your thesis), I think it's a good idea to audit courses. However, you should not rely on it as a hiring plus. It's a personal investment.


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Numbering sections in a two-part paper
How do you number the sections in a two-part paper i.e. a paper that is published in two parts?
I wrote an expository paper for high school students and it got accepted into a magazine, only that it will be published in two parts (because the magazine has a limit on the maximum number of pages an article may have). Now, after I have split my paper into two parts, I wonder how should the sections be numbered. The original paper consisted of three sections, which I've split as follows: in part 1 I have sections 1 and 2 and in part 2 I have section 3. Should section 3 still be labeled as section 3, given that it will appear in a different issue? I believe that it should, because I clearly state that part 2 is a continuation of part 1, but I would like to know what the practice is in such uncommon cases.

The magazine may have a standard. Otherwise, Roman numerals might work. In any case, the editor is your best source.

@Buffy I see. I thought that there was some well established practice, that's why I decided to ask this.

Should section 3 still be labeled as section 3, given that it will appear in a different issue?

No.  Since the journal/magazine has decided to publish your work in two parts, you should make each part as self-contained as possible.  Number things in a way that will not confuse someone who only has part 2.

Thank you! So, what basically matters in such a case, is that the second part be as self-contained as possible so that someone who only has that one may still understand most of the things in it. I understand that the numbering isn't that important as long as everything is clear to such a reader, right?


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Working towards an academic career that lets me do research in two (largely) unconnected fields—is this even possible?
In undergrad, I did a double major in pure mathematics and linguistics. I ended up loving both fields, and wanting to pursue an academic career. The only problem is that I couldn't decide between them. There is certainly some overlap between the two fields, but not especially much, and this makes interdisciplinary work somewhat rarer and the choice between the two fields feel much more discrete. After a few years of thought, I started to feel like the only option that would really make me feel satisfied is to at least try to seriously pursue research in both fields, even if this project turns out to be a total failure. I have gotten cautions from just about every source telling me this is not very plausible, but I am somewhat dedicated to attempting it anyway, in at least some capacity.
After graduating, I applied to grad programs in both fields. I got into a PhD in linguistics at a top university, and better yet, it offered the chance to pursue some math-heavy research topics. I ended up accepting this offer after much deliberation (I made a post about it here a few days ago!) and it looks like that's where I'll be headed in the fall. However, I've been second guessing my choice, because I feel like there is more room for someone with a math background to find their way into linguistics research than vice-versa, and I am really deeply loath to give up on the possibility of doing any pure math research.
With all that said, I'm asking everyone here a very open-ended question: what steps would I go about taking to make this pipe dream a reality? Or at least, to approximate it as closely as possible within the constraints of time and institutional pathways? Any thoughts are appreciated.

Sure, it’s possible. It’s also “possible” to win a Nobel prize, to become an astronaut, to become a billionaire, and to do other fantastic things. The steps one should take to achieve each of those things are reasonably clear, it’s just that it’s a near certainty that one would not succeed. The goal you are setting for yourself is maybe a bit less outlandish, but only a bit.

@DanRomik Well, I would think that one of the ways it may differ from winning a Nobel prize is that (presumably) winning a Nobel prize requires exceptional talent, whereas (my hope is) my goal only requires exceptional dedication. But maybe this isn't true, I don't know.

I think the alternatives are pretty clear: (1) find a specific area/problem at the intersection of the two fields and work on it, or (2) come to terms with the fact that just because you love both math and linguistics doesn't mean you need to actively pursue research related to both. It sounds like your choice is the closest that you can realistically get to your ideal without having a clear idea of which topic precisely you would like to work on. I wouldn't recommend spending much time second guessing what is clearly a very good starting position for you in the pursuit of a chimerical ideal.

@M.Sperling my main point was that the question “is it possible?” is not a helpful one. Yes, it’s possible. But the vast majority of people who start working towards an academic career soon discover that becoming successful in just one discipline is already enough to challenge them to the very limit of their abilities (whether it’s talent, dedication or whatever you want to call it). Most do not achieve even that seemingly modest goal. Anyway, just something to keep in mind in your career planning. Good luck!

I think the key question here is: what kind of linguistics work interests you. Can you clarify? As you say, some parts of linguistics do overlap with math -- particularly language modeling, computational linguistics, etc. -- are you interested in such topics, or is your linguistic interest more along the lines of historical linguistics?

@cag51 Both, actually—I'm interested in working on quantitative topics in historical linguistics, e.g. improving computer phylogenetic models. Sadly this is somewhat distant from the math topics that interest me most (alg topology, knot theory), but it is none the less math-y.

Maybe I'm biased because I work with search engines, but I regularly come across papers that are equal parts linguistics and mathematics.

It makes for bad branding - there are a lot of people and knowing one thing about them all of them is impossible, so why learn 2 things about one of them? One person's polymath is another's dilettante. That said, Chomsky managed in linguistics.

Become an economist! http://individual.utoronto.ca/carroll/cv.pdf

You don’t seem to understand how difficult the job market is. To be successful in one field will require your full effort, and even if you’re dedicated, we’ll-prepared, and talented you still probably won’t get a research job in academia.

Math and linguistics are not as unconnected as you think they are.

Warning: this answer is primarily just my opinion, based on my own experiences.
In general, if you're interested in doing research that consists of "applying mathematics to X", I believe it is almost always better to focus on studying mathematics first and X second.  I will give two (certainly debatable!) reasons for this:

The most difficult part of understanding "mathematics applied to X" is almost always mathematics, not X.  So getting a formal education in mathematics and then studying X on your own is more helpful than the reverse.
A mathematics degree is often more versatile, so if you don't find a job in the narrow subfield you hoped for, it is likely to provide you with more alternatives.

I received this same advice when I was considering options for graduate school, and in my experience it turned out to be correct (though it is impossible to know where the alternatives would have led).  Of course, I may be biased as I am an applied mathematician.

+1: "The most difficult part of understanding "mathematics applied to X" is almost always mathematics, not X"

Thank you for the answer. I think you're right, but for better or worse I think the "mathematics first" ship has sailed for me: I picked a linguistics program on the grounds of funding, which none of the math programs offered me, and this was a factor that ultimately swamped everything else. What I'm mostly asking about is how to make the most of my current position in pursuit of the sort of career I am aiming for.

@M.Sperling I understand completely, and as I said this is all debatable.  In your shoes, one thing I would try to do is take a lot of math courses during the PhD.  Hopefully you can find an advisor who supports that.  I see that there are books on mathematical linguistics, so hopefully you can get from those (or from people in the linguistics department) an idea of what kind of math courses will be most useful.

@Our That statement puts me in mind of "Nobelitis" or https://xkcd.com/793/  -- e.g. "The most difficult part of understanding 'mathematics applied to dairy farming' is the mathematics. I mean, after you apply the spherical cow approximation, the fact that they're cows can basically be ignored."

I would be very wary of trying to pursue an academic career in two fields unless you can find a way to leverage both in some interdisciplinary way. The amount of work required in the current academic market (especially at the PhD and postdoc stage) simply doesn't allow you to split your efforts between two subjects, even with "exceptional dedication" - there are only so many hours in a day, and everyone around you will be exceptionally dedicated as well as fully focussed on one field.
However this needs not mean that you abandon one field. Things you can do:

Cultivate "consultant collaborations" - contacts with people in the other field whose work has interdisciplinary leanings but lacks the contribution of an expert. This would allow you to maintain a network and some academic footprint in the other field while you concentrate your primary research programme in a single field. I've seen this work well for statisticians, programmers, physicists (my own field was too far from linguistics so I don't have any direct experience in that direction)
Remain active in a non-academic role. I knew several biologists whose academic work had turned entirely molecular, but who kept their interest in ecology/nature (often the thing that had drawn them to biology in the first place) through involvement with environmental and conservation efforts. I still do some science outreach, although I've not done anything to do with the research I talk about in years.
Park it for a while and go back in a few years. One of the functions of a PhD is to allow you to sharpen your focus into a topic to the point that you can add something genuinely new to existing knowledge. Some degree of single-mindedness is part of the package. Past the PhD stage and especially once you start establishing your own research trajectory, identifying where novelty may lie becomes more important. At this point, having a few years of focus on your primary field under your belt, you can turn to your other field for inspiration.
Interdisciplinary work. I've kept this last because, although it's the obvious choice, I would only recommend it if you find the actual interdisciplinary questions interesting, rather than a way to keep sitting on the fence indefinitely. Otherwise you risk committing to work that is neither fish nor fowl and not quite satisfactory in two directions.

Why not apply to a computer science department and do research in natural language processing. This is math + linguistics, and you'll have plenty of options afterwards in either research or industry.

Modern NLP has little to do with either mathematics or linguistics.

^That. It's more like scientific alchemy.

Parts of theoretical linguistics are fairly close to math: I had a class using Partee’s “Mathematical Methods in Linguistics”(here: https://link.springer.com/book/10.1007/978-94-009-2213-6) that was basically an abstract algebra + theory of computation class where people occasionally said “noun”.

As a linguist with computational interests, I think that the possibilities before you are endless. There are many directions you could go in applying mathematics to language, both in the applied and theoretical realms.
Pace David Ketcheson's answer, I tend to think that linguistic expertise would run out before mathematical expertise would. That's because computational linguistics is still in its relative infancy. The math doesn't have to be very advanced before you'll find that no one has applied it to linguistic problems yet—or at least not in a compelling way.
(Now, if by doing computational linguistics one means applying a bunch of machine learning algorithms to data that happen to come from speech corpora, then yes, in that case mathematical ability might become the limiting factor.)

As a software engineering grad who studied mathematics and (basic) linguistics at the same time, I agree strongly.  The intersection is an extremely interesting place for new research.

I'm writing this from the perspective of ecology, which is a very interdisciplinary field, and with complete and total ignorance about linguistics, let alone how math plays into it.
In ecology, we have a lot of people whose research primarily entails taking existing tools and theorems and applying them to answer questions about different systems. But we also have a lot of people that do less applied work and more theoretical research (in general with the hope that their work will hopefully lead to new tools for the applied folks). I enjoy mathematics as well and have been involved in at least one project that took a fairly old mathematical topic that was basically unknown in my field and developed a whole new set of tools for ecologists based on it. Presumably, there are tons of other mathematical theorems unknown to ecologists just waiting to be applied in some way.
As a soon-to-be Ph.D. student, you're in a good position to do the same type of thing for linguistics; expanding the applications of mathematics for linguists. Now, that's not quite what you seem to be hoping for, which appears to be researching new mathematical theorems, but here's the thing, eventually you could end up in a situation where you start to hit the limits of the mathematical topics you've been applying. This means you could be in a situation where you have to start developing new mathematical theorems to answer new questions about linguistics (or maybe just improving on existing answers). It wouldn't be the first time mathematical theorems have been inspired by real-world questions.
Now, you're getting to do what you want, and you have whatever funding opportunities linguistics offers to back you. The caveat is that it may take a long time to reach this point. But, as I mentioned before, I'm also completely ignorant about linguistic research, so maybe this isn't as realistic as it may be for other fields.

"Presumably, there are tons of other mathematical theorems unknown to ecologists just waiting to be applied in some way." I am so happy to see a person from an application area of mathematics say this! Often people only look at mathematics that is known to have applications.

There certainly are some people who have made outstanding contributions in one area after having done a PhD in some other. For example, Harish-Chandra did his PhD in Physics and then went on to do outstanding research in Mathematics which is of some interest to Physicists as well. So there are exceptions to David Ketcheson's answer and you need not "give up" on the possibility of learning/doing Mathematics after joining a PhD programme in linguistics!
The principal difficulty is "keeping up" with Mathematics while doing a PhD in linguistics. Others (like Ottie) have pointed out various ways of achieving this.
A juggling analogy may help you plan your approach. The first task with a ball that one learns is to throw one ball up and catch it. Most people stop at that point. However, some people learn to throw and catch two balls by keeping one in the air at all times. A yet smaller number manage with three, and so on. You are trying to be in the smaller set. It requires practice, but is, for many people, not impossible to achieve. You need to juggle life, linguistics and mathematics which should be possible once you gain some confidence with the first two!
Most active Mathematicians are aware that there are areas of mathematics that they will never be able to study properly. So, do not worry too much about the fact that you will not do graduate courses in Mathematics. There is no harm in picking one topic in Mathematics that particularly interests you and then following up on it. One of the big advantages of the way mathematics texts are written is that self-study is possible. You will, in addition, be at a good university. Thus:

You will have access to a good library and good internet services.
You may be able to get some help when you get "stuck" (as does happen to all of us!) from people on campus.

Be aware that there will be naysayers.

I think the answer to what graduate degree to pursue is down to whether you ultimately want to be a mathematician or a linguist -- what is the focus of your interest, the mathematics or the linguistics?
Yes, I am suggesting that you will have to have a primary focus, a subject "hat", if you will, that determines the lens, perspective and methodology of your research, even when looking at the same research questions.
I am a pure mathematician now, but I studied both theoretical physics and mathematics and for the longest time could not decide what to ultimately focus on. Now, these fields are (from what I can tell) much more closely interwoven than maths and linguistics, but even then, there is a pretty clear distinction between the mathematicians and the physicists interested in the same things (even though the mathematicians will know a lot of physics, and the physicists will know a lot of maths). The two communities interact quite frequently, but have different ways of thinking about problems and are often interested in different aspects of the same questions.
I became a pure mathematician (geometry, with some string theory inspiration) after my first year of PhD, and I think that is about the latest feasible time to make this switch (without "losing" time). Realistically, it is very hard to do mathematics research that is recognised as such by other mathematicians if this is not what you do full-time (as always, there are exceptions.)
And if you want to do pure maths research specifically, I do not think you will be able to do that if you are not fully in that field. (This may be less true in applied maths; I cannot really judge.)
Modern maths research is extremely specialised, and at the start of your career, you'll have a hard time getting up to speed in one area, let alone multiple at once.
In your PhD, you will (by the nature of how research works as a beginner) focus on a pretty specific question in a pretty limited area. Yes, you'll learn a lot of general things, but your research will be specialised. And how this specialisation looks will, I think, be very different depending on whether the project is set and supervised by a mathematician or a linguist, even if they ostensibly deal with the same subject matter.
People who make fundamental contributions to different areas of research usually do so later, broadening their expertise after having first specialised.
What you do not want to happen is that mathematicians think you're a linguist and linguists think you're a mathematician and ultimately neither field really engages with your research (or neither department/neither mentor feels you belong to them, as a student).
(This is advice I was given when I was choosing PhDs, and even though I did not listen to it right away, it became clear that it's a valid warning.)
This all is not to say that you should abandon linguistics -- mathematics is not the ultimate abstract uber-science that everyone has to do. There is obviously huge value in specialising in a different science that merely uses maths as a tool, rather than building the toolbox.
So maybe the question is: Do you primarily want to

build new tools for a broadly applicable toolbox and try them out
a little on specific applications, or
take tools and use them to
really get into the weeds of a science question, with the focus on
the question rather than the tool?

Ultimately, there is no one right career path, and every decision you make comes with the cost of of something else you do not do; that's simply how it is.
Practical considerations Re: funding & degree: Why don't you give the linguistics PhD a shot, if you do not have offers for funded maths PhDs? That way, you can see how you like it, think things over, and if next year you decide that you actually want to be a mathematician, you apply to maths grad school again?

I don’t have the reputation to upvote the other response or  can’t put a comment on here, but someone I went to undergrad with did undergrad and master’s in linguistics than built a company around semantic search. I have no idea if he was a Ph.D student that dropped out. Then the company got sold to Microsoft and he became a mid/upper manager in Microsoft over several other data science projects.
I am also reminded of some science fiction (Asimov?) that described creating a way of rating language automatically to detect bias, misleading content or something like that. I would really like to be able to tell Facebook or Google to stop giving me search results or posts that represent highly political, fraudulent or controversial information. I want to see kittens and babies, not conspiracy theories.
Any system that quantifies language could potentially leverage math on the back end.