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What does "engineering experience" entail
I'm a rising senior in high school and i applied for this engineering exposure program over the summer. My application didn't include any practical experience in the field, which I thought was fine because, as advertised, it was an EXPOSURE program. Anyway, I got accepted. So it should have been fine.
But the organizers made us do a conference call before camp began, and now I'm getting the impression that I actually needed experience (they had us fill out a form that asked us stuff like if we knew how to use a 3d printer, [insert program I don't know how to use], coding, etc.
I technically took classes on C++ and Java, but my teachers were subpar, so I'm not really sure if that would be helpful. I was under the impression that I was accepted because of my experience with the sciences (I took AP Bio, Chem, and both Physics C's), but it doesn't really seem like I'll be using those skills.
Right now I'm guessing I should pour all my time into coding better before camp starts? What should I do?
I'm asking here because I feel like people here would know how much weight qualifications and exerience actually hold. and honestly the engineering forum looked kind of intimidating.

You need to read http://norvig.com/21-days.html and please, continue your studies. You are young enough to not be expected to have experience, but to have curiosity. And you will use your science skills (other than C++ & Java) during your career. BTW, I won't say that one or two years of a few hours of courses in Bio or Chemistry is experience! And no, you don't need to put all your time in coding.

I think the purpose of the form was to find out how much the students know so that the instruction can be given at the right level. The fact that the teachers are planning for the actual skill level of the students (rather than just throwing them into things) means that they will be prepared to help you at the skill level you are at and you will be fine!

The form was asking if you knew how to do those things, not saying "you better know how to do this or else!". A little preparation in those areas may be nice, but judging from the situation, you don't need to spend all your time coding.
Here's my thoughts on it: if you're going to do an "experience and learn" type thing, you want to be in a position to get the most out of it, right? For example, I'm in an engineering internship right now (I'm a little younger than you, and my situation is kind of odd, but what I'm doing is pretty similar to what you'll be doing, sounds like).
If I didn't know some math and programming, and some bare basics about electronics, it'd be pretty miserable for everyone involved. But nobody expects me to win a Noble Prize in my first week. Everyone expects that, hey, I'm learning, and I'm probably going to need guidance to solve a problem, and I might need instruction in how to use such and such program, or whatever.
So what I'd do if I were you: brush up on programming, trying to understand the basics. You don't know what language they're using, and you have some Java/C syntax experience, so maybe try a different, easier language like Python that's quicker to write (or do whatever language you're most comfortable with; I just happen to be a Python fan) and try solving some of the Euler problems online (not problems written by Euler; they're just called that) using programs you write. That's a good way to practice if you know what you're doing to some extent, but need practice.
(Don't be afraid to google "finding length of list in [language]" or "doing [thingamajig] in [language]". I feel like, especially when starting out, a lot of programming means: run into problem, google error, google function used to solve error, type into program and adjust for situation.)
You can also review math (algebra II should be sufficient; I assume you've already taken it) and a little of the physics you've done if you want. If you've ever used a CAD program, you can review using that; if you haven't, maybe try downloading Autodesk Inventor - it's free for the non-pro edition, or something like that - and go through some tutorials with it so you get an idea how to use it.
Maybe look up some stuff about electronics, or about circuit board layout programs (I think there's one called Autodesk Eagle that might be free like Inventor). I don't know what all your thing will cover, but you get the idea. If you think something'll be covered, try to get a cursory knowledge of that thing, so you know what questions to ask and you're confident in your ability to, at the very minimum, figure things out going into it.
In the end, it sounds like you're going to learn a lot. "The forum sounds intimidating." That means there's a lot of cool people and topics that you don't know about yet that you're going to learn about! That's pretty cool.
Also, feel free to ping me in chat or in the comments if you want any specific advice on resources for different things.


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Is it possible to get research experience between undergrad and grad school?
I will be graduating from my undergraduate with a B.S. in Computer Science & Applied Mathematics with a ~3.25-3.30 in less than 2 weeks from now.  I'm taking at least gap year and a half after I graduate and am planning on applying to PhD programs in CS in the near future.  I have a semesters worth at my institution as well as an REU from this past summer, though I wouldn't say they are terribly related to what I may want to study towards grad school.  Aside this, though, I've looked at a couple other professors more towards my area of interest that I was considering trying to do research with (NLP/ML/Performance Analysis), but didn't, partly due to me taking three graduate-level courses this semester while finishing up my studies.
I have debated working in industry vs. trying to bolster my application profile for when I apply, and want to be able to do research in the time between undergrad and graduate school.  I've seen this is common in fields like Bio/Neuro, but haven't seen too much for CS aside from a couple of positions in national laboratories, has anyone gone through getting post-bacc research in CS?

Why do you want to take a gap period rather than just apply to a doctoral program?

Honestly after 4.5 years of undergrad I'm feeling the need to take a break.  As I noted I'm currently taking 3 graduate-level classes, and while I'm not feeling as much burnout now because I'm graduating, towards the start of the semester I definitely was feeling it.  I do still plan on applying to PhD programs, but if I went straight in I feel like I would burn out quickly.

There are two issues here. One is what will enhance your future chances to get in to a program, I assume in the US. The other is burnout. I'll address them separately.
Burnout is a serious issue and you should take some effort to avoid it. But working in a research project isn't, I fear, different enough from what you have been doing lately to let your mind settle down and relax. I would suggest that a few months of travel (traditionally the South of France or Spain) would be a better solution. Get away from things. But 18 months is probably longer than required for this. Walk the Appalachian trail. Ride a bike from NY to FLA.
The other issue is about enhancing your application. In Europe, some research experience would be helpful because the European baccalaureate is much more specialized than one in the US, so more is expected of entering students. But in the US that isn't normally necessary. The doctoral program in the US begins with mostly coursework (or what I characterize as "warmup" research projects) and not the serious dissertation research seen elsewhere. Not every entering student will have any real research experience whatever, and little in the beginning curriculum requires it. There is a lot of coursework to enable you to pass comprehensive exams in the field. This is the "breadth" element of graduate study, followed, after a few years, by the "depth" element of dissertation research.
So, while a serious stint of research might offer a small benefit in admissions (in the US), I doubt that it is necessary.
But your topline question is whether it is possible to do this. I suppose it is, but it takes time and work to find a situation. A lot of places doing serious research will think you are unskilled, not yet having an advanced degree. You will be a "trainee" for a while. It probably won't be very satisfying.
Some people, however, find a way to stay on at their undergraduate institution and do some research with a professor or two, but otherwise only carrying a light load. This can be the best situation if you can arrange it. Another possibility is to have a current professor connect you with a colleague at another local institution to do something interesting. This might be a sufficient change of pace to avoid burnout and also keep you connected enough to academia to make for a strong application. Financing this might be a problem, unless someone has grant money.

I spent a year as as a "research student" in Japan doing just that; for me it was between my Master's and Ph.D, but you can also do it after your undergrad.
Basically you need to find a school that offers such positions (here is where I did it), find a faculty member in that school whom you'd be willing to work under, and send them a friendly e-mail to ask whether they can host you.

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What impresses more in a graduate school application for CS: an REU or an honors thesis?
I'm a prospective applicant (or will be in the near future) for PhD programs in Computer Science.  I recently did an REU this past summer at a top-ranked CS school and am seriously considering graduate school, albeit after a break so I can be certain which particular area I may want to go into.
While I have my REU as some form of research experience, I'm wondering how much more I will need before I apply to graduate programs.  In my department, there's been a couple who have worked in labs for maybe a year or so (but so far, nothing like two or three years like I have heard at other places), and others in our Honors program are required to do an honors project with a professor at the end.  It's more or less rare that undergrads publish so much where I'm currently doing my undergrad.
While I have done the REU, I haven't gotten much further as far as doing research at my own school goes.  I tried working with a professor one semester during my senior year, but I wasn't able to get much done before I had to stop due to a busy semester next semester.  Generally speaking, is an REU more impressive to graduate admission committees over a senior thesis or doing research at your own institution?

I don't think the question makes sense because you can do both.

@AnonymousPhysicist I also don't know how an answer would be helpful for the OP, as the OP has already done one.

I don't think that there is a definitive answer to the question as asked. It assumes "equal quality", which is unlikely to be easy to measure. Moreover, every reader of an application might favor one over the other, but in a different way from another reader.
So, I would suggest, treating them of equal "value" on the face. But what will be impressive to a reader is that the applicant has done "something" that required hard work and has high quality. You can achieve this either in developing a thesis or in an REU.
My advice would be to pick one that interests you and you are likely to work hard at, but also one for which you get some local support. An REU might be slightly favored on the latter idea (support) provided that the research is guided in some way. But even a thesis could be given support if the student meets regularly with a faculty member during development to get some feedback.
Do something hard. Do it well.

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Keeping in contact with professors after graduation?
I just completed a CS undergraduate at University A (top 50 rank for CS), and am taking a gap year after graduating.  This past summer, I did an REU/summer research at University B (~top 15 rank for CS).  I hope to get recommendations from professors within both universities, and I have been thinking of asking if there are any opportunities to gain extra research experience within the 1.5 years of gap year that I will have, hopefully to gain another recommendation that can speak with regards to my research ability.
Has anyone kept in touch with professors you've known since graduating, and how do people generally do so?  I was thinking of asking one of the professors how I can best spend the gap year time that I have, but I was wondering if people maintain academic contacts like this after completing their undergraduate.

Why not just start applying to research jobs?

I'm currently trying to do that at the moment, but not sure where to look.  I've looked at national labs and research institutes (some of the positions already require a MS/PhD) and it's hard to find research-related positions elsewhere.  Any tips on where else to look?

I don't know CS, but I would have thought to look at universities. Big corps like Microsoft and Amazon have research divisions but I have no idea if they hire fresh grads.

Yes, many people do this, and many professors appreciate it. Professors will often be interested in your successes, whether in academia or otherwise. Most will want to help you in your future, but if they have been reminded along the way then it is easier for them to comment and write letters. If you keep in contact with them they can also have better advice for you in questions such as you have.
It is especially useful to keep contact with anyone you considered a mentor and anyone you think is worth emulating in your own career. And a wide circle of contacts is useful for anyone, but especially for academics. Past professors can also put you in touch with people within their circle.
If you have been away for a while, unlike this particular case, it is useful to make a campus visit and look up professors who you think served you well. Thank them for what they did for you. Afterwards it is then easier to keep a conversation going.
But some very busy people and some others with whom you had very little contact might not respond. Don't take it personally.

Generally, how do people phrase things?  Is it often on the lines of "Hi, hope all has been well ... I'm taking a gap year and was wondering how I can gain more research experience for grad school ..." (something like this)

It would depend on your relationship overall. But maybe a bit about what you have been doing since graduation and a bit about long term goals. An in-person visit is a good way to do this.


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How to cite or refer to programming codes in a non Computer Science Master's Thesis?
I am writing my Thesis in finance field and I am using Machine learning methods. Therefore, I wrote many Python and R scripts for collecting data, cleaning it and applying some statstics.

should I reference my own code that I wrote? if yes can you please tell me how?
should I reference all the libraries that I've used during my work?

Thanks

The standard way is to upload the code in a public repository so that everyone can use your code. In the thesis, you can refer to your repository in the footnote/endnote.
What you really need to cite is the papers/books which introduce the used methods first. The need to cite a library is when it has a specific configuration and it is likely that it outputs different result, such as the method which requires a probabilistic sampling. Here, the output will be different based on the used method.
Back to your case and responding to your questions:

You can publish all the materials of your work in a public repository and refer to it by citing the link (preferably in the footnote). It is unprofessional to add the code in the appendix (unless it is short and in pseudo-code).
You don't need to cite the libraries but the papers of the methods that are implemented in these libraries. If the library has a specific configuration, you can mention it in the text or cite the library (very rare cases).

@corey979 Would you read the code? would you retype it? I am pretty sure that no one would do it. Maybe it used to happen in the past, but not with the existence of public repositories and other platforms. Usually, people add algorithms (and only when they are short and developed within the published work) but not programming codes.

@corey979 I don't agree that it is justified depending on the situation. I still cannot imagine a scenario where the prog. code is needed. If a pseudocode, yes it is justified (only under some circumstances). A prog. code needs more than just coding lines, rather other external info (e.g. vrsn of the prog. lang.). Also, prog. style differs from a scholar to another (Here, we are not talking about software developers) and in most of the cases, the code is understood mainly by its developer. For me, the justified situations are very limited and can be considered as outliers of the general case.

You should probably not append all you code, but some of the most important functions may be worth to be in the appendix. Rule of thumb: Put there the code, the reader may want to look at during reading your manuscript, so he can compare the description of the algorithms with the actual implementation.

Regarding citations, I beg to differ. In many cases, the developers of scientific libraries are practicing scientists who have chosen to share their code for the benefit of others. Check the homepage and/or code and/or documentation of the libraries and check whether they have citation information. Sometimes, it is a URL. The next good solution is to archive the code on zenodo/figshare so that it has a DOI. Some libraries have associated journal articles that I would recommend very much to cite.

As others mentioned already, publishing your code in a public repository and indicating the link in your thesis is standard practice nowadays. However you should talk to your supervisor first in order to confirm that there is no IP issue in doing so with your work (e.g. if you use a piece of code by somebody else in the team which is not under a free license).
Also you probably read a few Machine Learning papers when you developed your software; these papers can provide you with good examples of what you need to explain about your code in the thesis itself: not too much technical detail of course, but enough information so that a reader can understand the general method (and ideally reproduce it).
Some ML libraries ask users who publish work based on the library to cite a particular paper, this is usually indicated with the license of the library.

Your code is not your thesis. You are usually only required to publish the thesis.
You may publish your code as well and mention it in your thesis, if you like to do so, though.
If you use other (scientific) code and libraries, it is good to mention it, especially in sections which benchmark run-times and similar things.
There you should use the citation suggested on the homepage of the library, which sometimes refers to the source and often to papers which are implemented in the source. If there is no suggested citation, usually refering to the project with an URL is a sufficient solution. You may of course try to write a nice bibliography entry yourself for code that obviously deserves a proper citation, i.e. the authors actually wrote a new algorithm.

In a thesis, you can include your own code as an appendix. For standard libraries there is no need to cite them, but for other things it is a good idea to do so. This enables others to follow up on your work. If in doubt, give a citation.
If your code is too extensive to include, then you can post it to an archive and cite it there, though my preference would be to include it.
You could also cite your own code as unpublished work or work in progress, as appropriate. Anyone needing it would need to follow up with you personally, of course.


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Withdrawing from course in a PhD Program (i.e. W on PhD Transcripts)
I'm already in a PhD program and, just one week after Add/Drop, both my teaching and research loads increased due to unforeseen circumstances. I have a course which would be helpful for my area exam, but I'm confident I can just teach myself and am considering withdrawing from it since it would be nice to have fewer deadlines looming over me. It's this weird grey area where I could probably make it through the semester, but this would basically require I get less out of my other 2 courses (which are exactly in the area I want to specialize in), not be able to teach as well, not be able to focus as much on research, and just be overall slightly more stressed.
Are there any repercussions to having a W on my transcript as a PhD student?
The only thing I can forsee is maybe external fellowship applications, but I am in my first year so I'm hoping they'd be understanding (it isn't like withdrawing makes it so that I am taking fewer classes than most grad students).
Thanks!
tl;dr:
Would having a W on your PhD transcript be problematic in some way?

Did you end up withdrawing? I am in the same boat. I have a class I don't need but it's after the deadline. I can't figure out if I am allowed to just withdraw on my own or not? What happens if I just withdraw on my own, does it turn to an F?

@user117015 - Lupin hasn't been active here in over a year, so you're unlikely to get a response. You could post a new question if it is on topic. in this case, though, you're probably better off asking your academic advisor, since this pertains to your institution's rules rather than academia as a whole. In any case, please do not post anything in the "answer" box that's not an answer.

I withdrew from a class when I was a master's student: no one has ever cared why I did. I was later accepted into multiple PhD programs and a post-doc.
I would have a prepared answer for why you withdrew from a class. "I withdrew from Ballistics 782 in order to better focus on my research. I produced two papers that semester."
If you ever think you would have a chance to go back and complete the course in another semester, withdrawing is even less of a risk. One W will matter little in the long run. (And likely even in the short-run).

I withdrew from a course as a Ph.D. student because it wasn't working well with everything else that was going on at the time. However, I did finally take the course. It was the entry point for a lot of what I ended up doing. I don't think anyone really cared about it in the long run.


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Are ideas related to a finished project a distraction from my current project?
I'm a new postdoc in a sub-field of mechanical engineering that is different from the sub-field I did my PhD in (I did my PhD in ML for combustion and now I'm doing a postdoc in ML for general fluid dynamics). I'm noticing an interesting phenomenon -- as I get up to speed with the literature in the new field and learn new things/concepts, I constantly get ideas on how to tackle old problems that we never solved with my PhD advisors. For example, I'm now studying convolutional neural networks for the first time, and certain concepts from there brought me new ideas on how one could improve an aspect of my PhD work. I seem to be getting many more ideas related to my past work than related to my current postdoc project. My PhD work was really fascinating to me which could explain why my brain still keeps thinking about it. But I'm wondering if those ideas are actually a distraction from my current project given that I don't have time (or only very limited time) to pursue them now. I would like to be making progress in my postdoc project because it's new and interesting to me.
It seems to me that I have three options when one such idea arises:

Ignore it and try to bring my focus back to my postdoc work. Perhaps with time my brain will learn to generate only ideas related to the current project? (Something like mindfulness, but applied to research :))
Don't ignore it, note it down in my ideas notebook, with hopes that maybe in 2, 5, 10 years I will have the resources to explore it.
Pursue means to dig into that idea asap if my past advisors think it's a good idea. For example, I could chat with my past advisors about it to find out whether they think it's a promising direction, and then together we could try to find researchers who could help us do the work.

So far, I've been doing 2. and occasionally texting my PhD advisors to see what they think. Some of those ideas they said are an interesting direction. But it never goes beyond that small brainstorming with them and jotting some more detailed notes in my ideas notebook. So the result is that my notebook keeps growing in size as I keep reading new literature in the new field, but it never leads to me pursuing an idea. What I need right now are ideas related to my current postdoc project, and those aren't so frequent... (Yet?)
What would you recommend I do? 1., 2., 3., or perhaps something else? In case you think that I can keep doing 2., would you say that every idea is worth jotting down, or perhaps I should develop an idea-filtering strategy?
Extra question: Do you think that more ideas related to my postdoc project will keep coming as I make more progress in the new field?
Some more info:

I'm officially/unofficially mentoring two new PhD students of my past advisors, so I might have some ability to introduce a student to one of the promising ideas. But I'm also aware that they already have a defined PhD project and I'm not their advisor. I would also never force a student to do a specific thing, because they have the right to organize their PhD work themselves. They might find my ideas not interesting or rewarding to pursue and that's okay.
I plan to stay in academia but I have no intention to come back to my PhD field (combustion) in the future. Currently other fields interest me more as a long-term research plan. I wouldn't mind doing a small project related to combustion in the future, but I wouldn't center my research proposal or a grant around it.
My PhD advisors seem to be happy to keep collaborating with me in the future.

I fear that this is an individual choice and different answers apply to different people along with what opportunities they have.
But, my preference, especially in the early career is for 2. Keep a notebook, well organized and up to date on each project. Set aside an hour or two each week to review the notebook(s) and update them whenever you have a "bright" idea.
I'd supplement that with a small deck of index cards that I'd carry everywhere, along with a pen. When I'm on the bus, or whatever, and get an idea for a project (even waking up in the morning), jot down a few words.
Sometimes you get stuck on the main project. Rather than fighting it, you may need a mental break. Go to the notebooks or index cards to "clear the mind" a bit.
If you have a bunch of potential projects you are in a good place to advise students, say, doctoral students.
And, you don't need to wait several years. Some projects "ripen" and are worth following up when that key insight hits, maybe over coffee with a colleague.
When one project winds down and there is little left do that is creative, scan the notebook for the "next big thing."
If you use electronic "notebooks" be aware that your backup media (or cloud providers) may not exist in 10 years. Take precautions.

Thank you, it's useful to hear your perspective. My notebooks are all paper ones ;) Good idea to have a deck of index cards with me! Would you also say that I should learn to steer my focus towards my current project, or are those ideas popping up actually a beneficial thing?

You are currently being paid to do work pertinent to your postdoc. Whether it is your PI or a fellowship, doesn't matter. You should focus on the work that is at hand.
It is tempting to lean back into your PhD research because that is a comfort zone. You feel competent, and now that you have some separation post graduating and likely more clarity on the topic as a whole (after writing a thesis, defending etc), you are naturally getting all sorts of ideas.
Save your ideas, see if you want to pursue them independently. I know I saved mine when I was in a similar situation.... and guess what, when I went independent, those ideas went in the trash, because I had broader experience and bigger ideas, and making derivative work to my PhD was no longer that thrilling.
Also keep in mind. If you end up with a mediocre postdoc because you were very distracted, your odds of continuing in academia will suffer, and so will any opportunity to revisit those ideas.

As a research administrator, I want to share that I agree with this based on what PIs have confided to me. A common problem we have right now is that postdocs don't want to do the projects their PI is working on. The PI is paying you to do the work in their lab. If you want to work on a new idea, you should write the grant that pays your salary. You will quickly find that this is a very gruesome prospect, and it's much easier to endure a couple of years with the PI's project even if less exciting. Unfortunately we don't have money for everyone's pet projects. The money we have is specific.


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What does "M'YY" mean in a researcher's short biography?
I just encountered this in a short author bio at the end of a paper from 2003:

What does the "M'99" and "M'74" mean? It doesn't seem like it's the year of obtaining a doctorate. These researchers are from Australia, if that's any relevant.

The critical fact that is alluded to in your question but not explicitly stated, is that the paper appears in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). It is common in IEEE publications to indicate whether an author is a member of the IEEE and if so, to include the year in which they joined the Institute. The purpose is to highlight their long-term association with the organization and (at least indirectly) suggest that the person has had a sustained commitment to the fields of electrical and electronic engineering.

Good answer.  I could imagine seeing "M'74" in some other publication, where it would mean something associated with that publication or the organization that publishes it.

Beat me to it. To add some detail, SM = Student Member, M = Member, S = Senior Member, F = Fellow, and LM = Life Member. Not sure when they stopped using that format (would require a review by year of articles), but they now are more explicit and use "(Member, IEEE)" or the other variations, and omit the year.

Further, the change started in 2020 (for one IEEE Transaction journal I looked at). And there is now the category of Graduate Student Member apparently as well.


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What title to put in CV if you do research but unfunded?
As the title suggested, if you have been doing research consistently with a professor, can you write RA as your title in CV? If not, what should be the title to put there instead to show that you have done research in that lab? Thanks a lot.

Do you need a job title? Just list the positions you previously had, probably stating the last one with "independent researcher".

If you are a student at a university it's probably unwise to claim to have a title there if you don't have it. Simply putting 'student' is probably better. On the other hand, many departments have unpaid, "zero hour" appointments if you really want an official title.
If you're not at a university and you fund yourself I suppose you can technically give yourself whatever title you want, but "independent researcher" would seem like a fitting description.


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Starting over six years again after Ph.D.
I graduated with Ph.D. in 2012 from SUNY-Albany College of Nanoscale Science and Engineering, with B.S. in Physics. Then I could not find a related job to this day.
In 6 years, I managed only to get two different full time jobs in entirely different fields, and they did not last.  I believe one of the major obstacle in my goal is that I am Deaf, and the employers do discriminate.
So, now I am enrolling into community college to try to get in an internship program in Computer Science/Engineering in Spring 2019.  One of my major defects was that I did lot of modeling and simulations on a platform, but without a computer program language (C++, for instance). Another major defects: the program was not ABET certified, did not have any undergraduate engineering courses (AutoCAD, statics, etc), exhausted references.
As I was working on this course of action, I realized that most college and universities tend not to admit people who has advanced degrees (both undergraduate and graduate programs).  Granted, the community college will provide me with additional training and coursework to cover some of the defects such as basic engineering courses, programming and possibly one more math course.  But how do I get back into advanced research and coursework, or at least do advanced research (postdocs generally requires recent graduate within 3 years)?

What specifically is your question?

This seems like a question for workspace. You want to work in industry, not academia, correct? I would suggest coding courses and informational interviews, not community college enrollment, but the people at workspace should know better.

@FábioDias: The last sentence seems to form a pretty clear question, which I think is on topic for this site.

Are you profoundly deaf or something less? Does it affect your speech as well?

@Buffy I am profoundly Deaf and do not speak at all.  My primary language is ASL.

@Dawn What I wanted to do is to continue my learning and performing advanced research, and that is usually in academica world.  In some cases, it would be federal labs, or some type of advanced private labs, but they usually require extraordinary level of accomplishments, coursework, and references.  So, I am believing that I would need to 'reset' my academic background, so to speak.

To the close voter and any potential close voters, this site is for helping Academians. The OP is a deaf PhD and needs help. And we close the question?

First of all, you don't need a job at most colleges, you just need one of them. So don't let a bunch of closed doors bother you. Many others are still open.
You can definitely still do postdocs. Some schools have strict rules, many others do not, treating it as a generic at-will employment job with whatever name the prof wants to give the role. I knew someone who came back to a postdoc after over a decade in industry (they left again in a few months for another industry job though). I know others who have stayed in the role for way too many years. There are also similar jobs with other names like research scientist that you can get in academic labs. It's kind of wide open if you are willing/able to relocate. Pick some big schools and monitor their job opening list.
You can also take classes at many (perhaps all?) major public universities via some variant of an open university system, requiring little more than permission of the instructor (and some cash). There will likely be a limit in the number of classes you can take this way but it can get you started. Ace a few classes and you will have a much easier time moving to the next step.
Lack of ABET certification is not a huge deal, by the way. It's a lot of paperwork and many universities don't bother with it. It's more important that the school is regionally accredited. Then we can trust (at least somewhat more) that you were actually taught what your transcript says you were taught.

True!  I had no idea postdocs were that flexible.  Thank you.  As for ABET certification, it was to my understanding if I wanted to become licensed engineer, I would have to graduate from ABET accredited program.  However, that might be a question for workspace, instead.

@Dr.PaulKennethShreeman I think you're right that you cannot become a licensed engineer currently because you don't have an engineering degree beyond the fact that the department wasn't ABET. This may be state-dependent. You would need experience in the field if you don't have an engineering degree.

This is a bit orthogonal, but let me describe a project that might give you some ideas that you could conceivably turn in to a career. Not exactly in this form, but you might want to think about whether some variation on it might suit you.
A friend of mine started a project in New Mexico to take young people with no seeming future (poor, gang-bangers, dropouts) and start up a combination educational program and software development house using Agile Software Development principles. I met some of his students/workers a few years in to the project and they were productive, hardworking, and articulate. They were also fantastic software developers. The Road: Reinventing Education - pdf download.
Dave West was the principal person here. He both taught the "kids" how to do software development, found grants to support the project, found real projects in local businesses, etc.
It occurred to me, reading your question, that if you are in a large enough place that there are others like yourself nearby, a project that is part education and part workforce might be something you would be interested in.
The education part isn't enough, as you learned in your own life, but a Studio Workshop that provides also a workplace in which the workers are trained by other, similarly situated, people might be viable.
It does require a fair amount of governmental support, but I imagine that can be found, though it is hard to maintain. A relationship with a sponsoring educational institution also helps. The workshop was not a charity in any sense and it produced real software for businesses. It helped a lot of young people turn their lives around.
One major challenge, of course, is that building software requires communication. Pair programming especially depends on a lot of communication. Someone wanting to do this with profoundly deaf people would need to replace chit-chat with visual communication, of course. But it would be a major contribution for someone to do this well.

Is "deaf and dumb" current vernacular? How about "deaf and mute" or just "deaf".

I really enjoyed your "orthogonal" solution.  Unfortunately, it is not direct answer to the posted question, but still an excellent option to consider, and I find the concept very attractive.  By the way, the Deaf community considers "Deaf" to be sufficient description, and that other two terms, (dumb and mute) is considered to be demeaning terms.  It's interesting, tho, because ability to speak and ability to hear is two distinct and separate abilities which 'deaf and dumb/mute' supposedly help convey that concept, but is no longer viable (or at least proper term) to be used.

@Dr.PaulKennethShreeman, thanks for the education. I worried about my phrasing, actually. I lost most of my hearing as an adult due to disease. No hearing on my right and vastly diminished on the left. It didn't affect my speech, I'm told. So I'm "deaf" but not in the same sense you are. I'll make an edit here.


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Is it okay to choose a non-peer reviewed research paper as Master's thesis topic?
I am interested to work and improve on one of the research papers which published on https://www.casact.org/pubs/forum/  but I found out that, research paper published on Casualty Actuarial Society, CAS, E-forum is a non-refereed and not peer-reviewed by any of the CAS committee as stated in the E-forum. So, is it okay for me to choose a non-refereed research paper as my Master's thesis topic ??

This is a question for your advisor to answer. But in general, yes, there is no reason why you can't take ideas from anywhere you find them. You should be pretty sure, however, that if you want to accept the conclusions of the paper as your starting point that you can establish their correctness for yourself.
In fact, even if the paper is a poor one, it may still contain an idea or two worth pursuing.
Also, you don't know why it doesn't appear in a peer-reviewed place. It is possible that it is intended by its author(s) as work in progress to be followed up later.
But, first, ask you advisor.

The wording of the question (and the title) "choose ... as my Master's thesis topic" suggests to me that the plan is to write about that unrefereed paper, not to use it as a starting point for further research. (But maybe I shouldn't give so much weight to the exact wording.) And writing about that paper could mean explaining it, or refuting it, or various things in between.

Yes, of course. I don't see a distinction, however. The conclusion would be the same. Just do it.


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Receiving gift from student before grading MSc thesis. Is it ethical?
As a follow up on this question I am wondering whether it is ethical to receive gifts from students before grading their MSc thesis (or any other project where students feel like they need to thank you for).
Lately I have encountered this situation where a student gave me a present before I was able to fully grade his work. The student had to go abroad and wouldn't be able to drop by after grading. The gift was rather small, just a few bottles of good quality beers which are not that expensive where I'm from. He also said: "you can drink this when grading my work, ha ha". We got along quite well, so at that time I didn't feel like it was some sort of bribe (which I still don't feel like it was).
Generally, I don't have any problem in accepting gifts as they tend to be rather small. However, a month after receiving this gift and finishing my grading for his work I was starting to think whether I have made the right decision by accepting his gift.

The nicest gift I ever got from a student was very inexpensive, but bought specifically with me in mind, and given after she had graduated as a thank-you.  I still tell people about it.  The note said, "Thank you for staying on my back."  You just can't beat that.

Regarding "it was rather small": https://www.nber.org/papers/w18543 for a video summary, see https://rationality-and-competition.de/research/videos/schmidt/ tldw; small gifts are more effective as bribes than larger gifts

@HRSE: that's an extremely interesting study!

In my opinion you are asking yourself the wrong question. The important problem is not if it feels like a bribe to you, but if it could look like a bribe to others.
Let's say you have another student whose thesis you are grading at the same time and he ends up with a worse grade. This might have been an objective decision, but still, if this other student now hears about the gift you got, he will start to wonder if maybe giving you a nice gift would have gotten him the same grade.
Since the gift is quite small, you are most likely legally in the clear, however in my opinion, ethically it wasn't the right thing to do. It is probably to late to return the gift right now, but for similar future situations, it is probably better to decline gifts until the grade is set in stone. Not only from an ethical point of view but also since it will give you an aura of fairness and incorruptibility at the low cost of a few cheap beers.

Our place has a clear-cut declaration policy and a (quite low) upper limit of acceptable value above which you have also to hand over your gift to the school. This makes it easy for me, even for students from cultures in which gift-giving is virtually obligatory: I decline any gift, because it means that I do not get to keep it plus I have to carry out extra paperwork. So, I explain that I do not get to enjoy the gift, and I get burdened with a chore.

Great answer; additionally I wonder if the question should not be reversed: is it ethical for the student to give a gift to their professor before grading? From the professors' point of view, since the gift has little value, it's not really a bribe but more a sign of good will from the student. In this case, even if the professor refuses the gift, the student has achieved the intended goal (which was to make himself look nice and be considered differently than the others). So there really is nothing the professor can do about it. But I agree with the importance of the way it looks .

@Kerkyra, good suggestion. I was indeed thinking the same after I posted this question. Maybe it will be indeed nice to contemplate about this in another question using another 'setting', so to say.

In cultures where gift giving is "almost compulsory", there is often the expectation that you will receive a gift in return, and accepting a gift but not giving one in return is equivalent to a personal insult. That is not a situation you want to be in, while grading academic work!

@Kerkyra: I'd say it's a question both ways, and where I am it's off limits from whichever perspective you're looking at it. (Small gift after everything is finished would be OK). However, here (Germany) the official policy is far more heavy on the professor because a) of the perceived difference in power and b) professors are public officials, and particularly in exam situations. A few bottles of good quality beer would here be outside the "insignificant" range for school teachers, and the fact that a single student who is yet to be graded gave it alone would cause it to be unacceptable.

I've anecdotally heard of a similar situation (although I suspect the gift may have been more substantial) where the teacher then took the student aside, handed it back and explained that also for the student this can lead to serious trouble wrt. attempted bribery (again: public official - so policy is directly related to anti-corruption laws for public administration etc.).

Most students know that you grade according to the marking scheme and they offer the gift unconditionally.
It is the "other" students who you have to be careful of, and you get a "feeling" about those - a rare case usually.
Edit based on comment:
There are policies dealing with this in some institutions, where, if the value of the gift is below a given amount then it is fine and accepted by all parties including management.
However, if the value is above that limit then it must be declared and the line manager or line manager +1 makes the decision as to whether the gift can be kept or it has to be returned or held by the department etc.

I usually very much like your suggestions, but this one is dangerous. As they say (and said above): "Caesar's wife must not only be faithful, but must also be seen to be faithful." Do not create ambiguity.

@CaptainEmacs It is not a question of ambiguity, but of policy. There are policies dealing with this in some institutions, where, if the value of the gift is below a given amount then it is fine and accepted by all parties including management. However, if the value is above that limit then it must be declared and the line manager or line manager +1 makes the decision as to whether the gift can be kept.

Better, thanks. In our dept., we have to declare anything (except, of course, thank you cards, these are always welcome).

@guest2 some of us have to write the marking scheme before the students even take the exam - one type of quality control...

I'll give you a corporate point of view.
Many companies are required to have compliance programs, which include establishing clear policies for many situations, make the documents for such policies accessible for everyone (sometimes public even for people outside the company), and ministering presentations for all employees (required to sing an attendance list).
So, you can probably check one of these policies from a company whose reality you believe is representative of yours.
A common rule in corporate compliance is that you can accept gifts from bidders. It would often sound rude if you rejected them. But there is a limit to the likely value of a gift you can accept. Where I work it is 100 dollars. And the case is pretty much analogous, if we're talking a bidder, this person represents a company whose offer you'll need to evaluate. Though usually you need to pick a winner, rather than grading his proposal.
If a gift is known or discovered to surpass the limit value, one option it to auction the item and donate the value for charity. Of course this is expected to be done without the gifter's knowledge.
Sometimes there are specific policies against accepting alcoholic drinks, but this is not so usual.
Up until here, I would said you pretty much should have clearance to accept this gift. And I would accept it if I was a teacher, given one last condition:

How fair and objective is the grading system?

Could you be accused of favoring the student's grade because of his gift? If you are a math teacher who practices binary grading (i.e. each question is right or wrong, only the final result counts), no one would expect a test grade to change over a gift. If you are correcting essays which are related to subjective topics, the type where student would often argue that better grades are attributed if "guessing the teacher's opinion on the topic", then care should be taken.
Even for the latter case, further trouble could be precluded by formally delivering a grading reference to the students, showing their graded papers/tests/homework such that any unfairness, if suspected, could be pointed out, clarified and corrected. Which sounds like good practice to me.
In the end, don't put yourself in trouble, have decent practices and nothing wrong should happen for accepting a small gift.

The funny thing is I checked our policies and previous schools and there are no written policies I could find about gifts from students. There are policies for gifts from vendors and people with financial interests, and gifts to admission personnel, but none in the context of grading. Unlike a company, usually a instructor has the sole right to assign grades, under the rights of academic freedom. It may not be changed by the administration.

No, this is not ethical; don't accept such gifts.

Whether it is ethical to receive gifts from students before grading their MSc thesis

It is not. A gift influences the receiver in favor of the giver. It also carries an implicit indication of the assumption the receiver will give a high, pleasing grade; you wouldn't gift someone who stuck it to you in grading and made you appear incompetent, would you?

(or any other project where students feel like they need to thank you for).

This is the more serious problem. The gratitude an M.Sc. candidate feels towards his thesis graders/readers/examiners is not the kind that should translate - in practice and in their minds - to personal gifts.
I would try to reflect upon why that is that such gifting seems like a reasonable thing to try and do - to students, and apparently to you. I would then think of how to educate students and faculty that this kind of gratitude should be expressed by, say, contributing to the faculy/department; volunteering for some academia-related cause etc. - something roundabout and diffuse in a larger community of people.

Lately I have encountered this situation where a student gave me a present before I was able to fully grade his work.

You're implying that it matters very much whether it's before or after. This is part of the work you are (hopefully) paid to do, and part of your duties towards the larger academic community. You're not doing a favor here.

The gift was rather small, just a few bottles of good quality beers which are not that expensive where I'm from.

So, multiple bottles of somewhat-expensive alcoholic beverage. Totally inappropriate, even if you're in a beer-drinking culture.

He also said: "you can drink this when grading my work, ha ha". We got along quite well, so at that time I didn't feel like it was some sort of bribe (which I still don't feel like it was).

You should have told him: "I appreciate the sentiment, but you know, there is at least the appearance of an ethical issue here, so please don't be offended, but I have to decline. I suggest you bring the beer to your thesis presentation" [assuming you have that custom, where people give a seminar-style talk about their thesis] / "farewell party."


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Publishing editorial work on arXiv
I have made an edition of handwritten notes of a physicist X (of the past century). What's the best way to submit it to arXiv?
I have seen two examples of editorial work in arXiv:

On one hand, the submission is made by the editor and also as author (e.g. https://arxiv.org/abs/1705.02601)
On the other hand the submission is made by the editor but he puts the original author (e.g. https://arxiv.org/abs/math/0206203).

I think the two are founded. But I would like to know what is the best way to do this.

arXiv has guidelines for how to publish a translation of someone else's work, and I assume this would be similar.
You, as editor, should submit with your name in the "Author" field, but include the original author's name in the title; e.g. "Lise Meitner's Notes on Uranium Decay".
Of course, there is a separate issue of making sure that either the copyright has expired, or that you have permission of the original author (or their estate), which is also mentioned on the link above.


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PhD or postdoc salary in Denmark according to the cost of living. Is it OK?
I´d like to know if the average salary for a PostDoc and a PhD student is sufficient for a middle income expectations in Denmark.
What I mean for middle income is for the two of us (1 PostDoc and 1 PhD) to rent a 1 bedroom flat, spend in public transport, go to the supermarket without worries and travel on vacations once a year.

To my knowledge, postdoc and PhD salaries in Denmark are among the very best in the world.

In the Netherlands (sadly about 30 years ago) that seemed to be the case for myself (post-doc) and the PhD students. Although the students took vacations more than I did, oddly enough...

Cost of living is high, particularly in the Copenhagen area: rent, food, transportation, etc. But already with a PhD salary you will get by no problem and you will have plenty of extra money at the end of the month. Two salaries will allow you to rent a nice small apartment, so no problems. People with kids do PhDs in Denmark, so that should give you an idea, if you have no kids it's plenty enough.

The average PhD and postdoc salaries are higher in Copenhagen too, aren't they? Some numbers can be found here. Whether the difference is more or less than the difference in cost of living, I don't know.

@Anyon it depends on the source of funding.

This answer is about the København/Copenhagen/Kööpenhamina region.
Taxes
As a foreign postdoc it is possible to get a flat tax rate, at the price of losing all deductions. This might or might not be worth it financially, but certainly makes planning easier.
Apartment
Renting an apartment is terribly expensive. First, it is difficult to find one that has a reasonable price. Being a foreigner does not help. We (two adults and a child not of school age yet) had to first live in a far too big and expensive apartment before finding a cheaper one. A couple just moving in are renting an apartment with three rooms. Cheap apartments do not exist and finding one of reasonable price is not trivial. Both of the examples here were of Nordic couples/families, and the latter could read Danish fluently and write it intelligibly.
You should have savings. It is typical to pay three months' rent when moving in; the first and the last months of the contract and one more just in case.
It is typical that the walls of an apartment and newly painted and you are supposed to paint them again when leaving. This, too, is expensive. Try to avoid this at all costs when making the contract; it might be possible with a short one, but might be difficult with a longer contract. Be very diligent when making the move-in report and take detailed photographs of everything, just in case.
Life
My family lived with a single postdoc salary. After getting past the initial shock of settling in, we did not have problems, visited museums and places for children and used the public transport.
We travelled back to Finland for Christmas and summer vacations.
Some caveats: We did not eat out (though I did eat at the DTU cafeteria), but also did not save from ordinary food expenses, eating plenty of nuts, for example. We do not drink alcohol. I walked and biked to work, so we did not use the public transportation daily. We did pay for the daycare, which is an expense lacking from you. We tend to buy things used and I tend to not buy many non-food things.
So, given a reasonably frugal lifestyle, we did not have problems living with a single postdoc salary. I did have enough savings to not worry about it anyways. We were there for little less than a year; a longer stay would have made things easier.
PhD salary is quite comparable to postdoc salary.
Eating out
It is unusual to eat frequently at a restaurant in Denmark (and Finland and Norway, so extrapolating to all the Nordic countries might be fine, too). It is something done on special occasions, not every day or every week, for most families. It is also expensive, as the staff has reasonable wages and there are taxes.
Eating out seems to be bizarrely common in some other parts of the world.

If the PhD is done while employed in the industry or public sector, the salary will be comparable to employees with regular positions in the company. It is for example quite common for medical doctors to do a PhD while  employed as interns at a hospital. Post doc salaries in Denmark are quite good, but usually public sector has lower salaries than the private sector.

@Noah That is because eating out is considered much more of a luxury here (especially compared to in the states), though to some extend it is also related to the generally higher wages which end up making it expensive to run a restaurant while paying your staff a livable wage, which is the standard rather than having waiters have a major part of their pay be the tip (tip already being included in the price, which is what makes Danish tourists such bad tippers).

@TobiasKildetoft Most of your comment only applies to the US vs. Denmark, but Denmark is very different from other rich Northern European countries in terms of restaurant culture  (which is why my comment included a large mix of countries, and not just the US).  I mention it because it'll be a bit of a shock to anyone who isn't Danish (or perhaps Scandinavian?), and it's relevant to budgeting.   You'll be paid enough to live comfortably, but not enough to eat out at a rate that one might be accustomed to in similar countries.

@NoahSnyder Right, it is definitely a thing to be aware of in case you are used to eating out frequently (or even once a month, which would be more than most Danes).

I added a note on eating out  to the answer.

@Tommi Thank you for a very helpful answer. If you do not mind, I would like to know how much you paid for a rent/flat per month. I am in completely the same situation as you, that means, I am going to move to Denmark as a postdoc with my wife and a kid not of school age yet. So far I have not been able to find a good, affordable house. I wish to know if it is realistic to live on a postdoc's salary while paying 13k-15k rent. (We also do not drink and eat out often)

First we paid exorbitantly for a huge university-provided house while searching for something more affordable. I had savings, but I presume we consumed some of them. 13 k kroner maybe? Then we found an apartment in a block house, just the rent 7500, other stuff on top and the total was 8655 kr/month. This was in 2017, mind.


text:
Should I take the GRE physics subject test for a chemistry PhD?
I plan on applying to top chemistry graduate programs (MIT, Caltech etc.)
I took the Chemistry subject test, score isn't in yet but I think  it's with high expected value (because I knew everything) but also high variance (because I worked...sub-optimally...and maybe made a ton of stupid mistakes) so it's a bit iffy.
I also noticed that I can answer most (~80%) of the questions on the Physics subject test and decided to sign up for that one too. It won't be a high score - I obviously can't compete with physicists - but just want to showcase my decent physics background (deeper than most chemists).
Is it in any way beneficial to send chemistry graduate programs also a mediocre physics score? Should I give it up and try to retake the chemistry test?


text:
Better chances of getting in if university would like to review my incomplete application?
I had recently applied to a somewhat niche Master's program (~100 applicants for ~20 places per year, according to the University's statistics) at a top university (top 5 QS in various disciplines)¹.
One of the reasons I hadn't considered this program seriously is because some of my professors limited the number of letters they could write. Given this constraint, I wanted to optimize my chances of getting an admit by applying to other less-competitive programs which also didn't require 3 recommendations while still being a good fit. So, I just filled random information just so I could submit².
A few days later, as expected, I got an email stating that my application would not be assessed. However, I now received another email stating that the admissions committee would like to review my application if the references are received.
My question is (assuming I'm allowed to edit my references):
Does the fact that the committee would still like to review my incomplete application mean that I have a good chance of getting in? i.e. I would like to know if it is worth it to "spend" 3 recommendation letters on this program now?

¹ I mention the ranking only to provide context while keeping the question general.
² I know it was pointless, but I had to "submit" because of reasons I cannot disclose. I thought that since it was incomplete, the admissions committee wouldn't need to waste any time on it.

This is not really a question that can be answered here, as it depends on individual factors. I think this is a decision that you have to make: how much would like to get into this program? Is it worth to YOU to spent the recommendation letters? This might also be dependent if you are already accepted somewhere else.

To me it seems to signify only that they don't have enough obviously qualified candidates and seek to expand the pool. Better than nothing, but only they can say.

Now I'm curious how big people think "niche" is.


text:
Difference between ACM's print and online memberships
I would like to inquire about the difference between ACM's SIGACT online membership and print membership.
The group's main page showing both of the membership choices
https://www.acm.org/special-interest-groups/sigs/sigact
Background:
I am a sophomore computer science student interested in computing topics with emphasis on mathematical rigor, particularly, computational complexity theory and quantum computing. Subscribing to prestigious ACM gaining latest developments in the field and a chance of connecting to others seems promising.

Have you checked whether your university library already carries these journals?  You might not need to subscribe to anything.

ACM SIGs (Special Interest Groups) generally publish things like conference proceedings and newsletters. A print subscription implies that they are sent to you in print, usually a few times a year. An online subscription gives you access to the same materials only online with a login. Other than that, the memberships are the same.

I have received an official e-mail from ACM confirming your reply:
Dear Mustafa,
Thank you for contacting us at ACM.  My name is Nancy and I will be happy to assist you today.
SIGACT Membership includes a quarterly newsletter SIGACT News. The only different is that you get this newsletter in print for the SIGACT print membership and it’s online only for the SIGACT online membership. All other membership benefits are the same.
If you have further questions and/or comments, please do not hesitate to contact me.  Have a wonderful day!


text:
What can I do if the reviewers' comments on my manuscript are not correct?
I sent my paper to one journal, which took about 3 months to respond to me.
They decided to reject my paper, and gave me some comments and reasons why my paper was rejected. The first reviewer said a little about my paper and he/she wants to reject my paper because I do not have co-authors with me. I did the paper by myself.
The comments of the second reviewer seemed disrespectful and misinformed.
His/her comments were written in a way that suggests that I am stupid and what I did is just rubbish. He/she gave me some comments (the reasons why he/she wants to reject my paper). When I read the comments, I found that all the comments are useless and wrong. For example, at two simple points (very known in the area of my topic), she/he said these points are wrong. All researchers in this field know that what I wrote is completely correct. All other comments were just written with very low respect.
What can I do? I did this hard job alone, so why do I need to find someone to be a co-author? I feel that they rejected my paper because my name is not known in this area (I am a student).

Is there anyone at your university that you can talk to about this, and show them the paper and feedback to get a second opinion? Is there a reason you didn't go through them for help getting this published in the first place?

They may be suggesting coauthors because your paper is not up to standards in the field, which suggests that you haven't gotten the right kind of advice on the work. Even if you do solo work, having an academic advisor help with the publication process is very important for students new to the process.

It seems like this has been asked before, but I can't find the link. I have found several questions where there was a revision decision and "wrong/rude" comments, but not one where there is a reject decision.

Related: https://academia.stackexchange.com/questions/72449/is-it-normal-to-get-an-angry-review-that-does-not-address-any-point-of-the-work?rq=1

Also related: https://academia.stackexchange.com/questions/5865/what-to-do-if-reviewers-reject-a-paper-without-understanding-the-content?rq=1

I'll add a possibly related note: If the paper is written in the same style as your question and comments, then I will agree that having a co-author with better writing skills would definitely useful. In general, any author -- but in particular younger and inexperienced authors -- are better off if they show their manuscripts to experienced authors and reviewers.

"All the authors in this area know that what I said is completely correct" - Did you cite the previous research that shows what you said was correct?

I did a proofreading for my paper by a professional editor.

@Bryan Krause yes, I cited the previous works.

What field are you in?

@Bryan Krause Statistics.

Though it seems to vary a bit between more mathematical versus applied statistics, sole authorship seems fairly rare in statistics outside of software implementations or more opinion/argumentative papers that are typically by authors already respected in the field. I went through the CV of several graduate students in statistics at my institution and did not find a single one with a single-authored paper.

Far a way fro selfish, I was setting with one very famous expert in my area and I told him about my ideas. He said to me that I am thinking at the same level at the professors. And he said, you are one of the most rare student that I meet in my life.

Another professor want to join me for my topic because it is so important, but my supervisor refused that!

Whether they are right or wrong, the editors are in control of what they will publish and you don't have any control over that. You aren't likely to be successful with an argument with them.
You have two options, at least. One is to change the paper so that they are satisfied with it. The other is to try to publish elsewhere.
However, I will guess that the comments of reviewers aren't as invalid as you think they are. Even if you decide to publish elsewhere, you should go carefully through your paper with the views of the reviewers in mind and see what you can do to make it better.
No one is required to take all of the advice of reviewers, but generally, they are expert in the field and so have valuable things to say. You don't need to respond to every advice, but you should, at least, consider every advice.
Among other things, I wonder why they suggest a co-author. Is there something in the paper that suggests that it would be appropriate, or are you in a field in which sole authorship (especially by students) is rare?
And don't take the comments personally. They aren't criticizing you when they have doubts about the paper. They are focused only on the work itself.

Thank you for your answer, I have already sent it to one very important paper in the same area, but they rejected it because they are not interesting in my data. However, they said what I did is very reasonable and good.

My supervisors read it and said it is a very good work. Also, they asked me to add their names, just because they are my supervisors but I refused that. Because they did not do anything for it, just read it at the end. Before that they said they are busy and I have to do my job alone!

I asked my supervisors to join me with any contributions even to help me to find a good data, or add extra simulation section but they refused.

@F.Thomas This is important: Supervisors belong on the list of authors. Without your supervisor, your probably wouldn't have any entry point to your research area. They provide you with feedback. This is an almost universally accepted standard. Refusing to list your supervisor as co-author is not a good idea.

@Ian, this is only true in some fields. Not all.

@Buffy Okay, my experience is limited to MINT subjects.

@Ian No, this is utter nonsense. Supervisors belong on the list of authors if they did any actual work (supervision of this specific work counts, of course). It’s common that supervisors get a free pass but this is blatantly unethical.

@Ian What do you mean by providing "an entry point to [a] research area"? That doesn't sound like a criterion for co-authorship to me. Supervisors usually are closely enough involved with their students' work that they should be co-authors but that should require a specific contribution to the work reported in the paper.

The first reviewer said a little about my paper and he/she wants to reject my paper because I do not have co-authors with me.

Are you sure that's why they want to reject your paper? It seems much more likely that they rejected your paper because of deficiencies in it, and suggested that bringing in co-authors could help you rectify those deficiencies.

His/her comments were written in a way that suggests that I am stupid and what I did is just rubbish. He/she gave me some comments (the reasons why he/she wants to reject my paper). When I read the comments, I found that all the comments are useless and wrong. For example, at two simple points (very known in the area of my topic), she/he said these points are wrong. All researchers in this field know that what I wrote is completely correct. All other comments were just written with very low respect.

I would say taht your response to the referee is written in a way that suggests that they are stupid and what they did is just rubbish. Your response seems to have been written with very low respect. A little hypocritical, no?

I feel that they rejected my paper because my name is not known in this area

While there is some bias towards accepting the work of well-known researchers as being interesting and worthy, mostly they rejected your paper because it wasn't good enough and, it seems, because they felt it was technically flawed (at least in places). You have a paper that has now been rejected by two journals: this should be a huge wake-up call but you seem completely unwilling to accept any criticism of it and insist on blaming everybody but yourself. If you just had one referee who wanted to reject your paper then, sure, maybe you were unlucky and got a bad referee. But it sounds like both referees at the current journal rejected, plus however many at the first one. Can you see a pattern here?

In addition to the above, "I feel that they rejected my paper because my name is not known in this area" - isn't it usually the case that referees are not shown the name of the author?

@MartinBonner This varies between fields, so I assume the asker's field, statistics, is only single-blind. (Pure maths and theoretical CS are usually single-blind.)

@MartinBonner No, this is highly unusual in most fields. Double-blind peer review only even exists in a few fields and even in most of these it’s the exception.

I did this hard job alone, so why do I need to find someone to be a
  co-author? I feel that they rejected my paper because my name is not
  known in this area

If you believe that this is a major reason for rejection, you could try submitting to a journal that uses blind reviewing, i.e. identity of the author/s is concealed from the reviewers.

When I read the comments, I found that all the comments are useless
  and wrong. For example, at two simple points (very known in the area
  of my topic), she/he said these points are wrong. All researchers in
  this field know that what I wrote is completely correct

In that case, the simplest option is to provide a cite to where some of those other researchers have made these points. It's frustrating having to cite what seems obvious, but not everybody has the same idea of what's "obvious".
You might also check how you have explained those points. On my most recent paper, I got several reviewer comments that were incorrect. The reviewers had misunderstood my paper. But even though their suggested changes were wrong, the feedback was still useful because it helped me identify areas where my explanation wasn't clear. By improving the explanation, I was able to satisfy my reviewers.
Beyond that, as Buffy and David have suggested, consider your reviewers' comments very carefully. It's not impossible to get two clueless reviewers, but it's unlikely.


text:
Resume Question: How do you put mastering out of PhD on resume?
I am currently in my 2nd year in a PhD and going to master out in May. Should I put "leaving PhD" on my resume? Or just Masters? My field is in Computer Science where mastering out is quite common.

Does "mastering out" mean getting an MPhil rather than a PhD? (Note that an MPhil is somewhat different from an MSc.)

My suggestion is to list the degrees you have earned. You don't need to list or mention the ones you haven't.
But be prepared to be honest in any interview in which you are asked. There are a lot of reasons for leaving any degree program.
In any application process stress the skills you have and your suitability for the position.


text:
Where to put proofs in a thesis?
When writing mathematically oriented thesis, e.g., math, cs, engineering, I am wondering where would be the most appropriate place to put your proofs.
There are several ideas:

put them right after the theorems/propositions
put them separately in each chapter's appendix (i.e., a new section at the end of chapter)
put them all in an appendix

Can someone chime in which practice is superior than the others?

There's proofs in engineering theses?

This really depends on how mathematically oriented - whether the proofs themselves are actually important or not.  Ask your advisor.

@AzorAhai-him- definitely.  Lookup theses on signal processing or control theory.

I've seen #1 and #3.  For #1 I would sketch a proof if I require the reader to have some intuition about a lemma/theorem that I will then use in my solutions.  This is a judgement call based on whether a statement is easily understood, and whether you require a reader to go thru' a proof to understand the next bit of your thesis.

How long are these proofs?  I would never want to see a short proof (say one page) banished to an appendix.  Twenty pages is another matter.

This typically depends on whether the technique of proof assists in elucidating the topic under discussion or not.  If the details of the proof contributes substantially to ellucidating the topic under discussion then you would keep it in the body; otherwise it is useful to relegate them to an Appendix.

The ultimate goal is for the paper to flow smoothly. Therefore, my favorite style is to place some proofs right after the propostion, while some others in an appendix, depending on how much insight the reader gets from reading the proof.
If only the result of the proposition is important and the reader is better off reading the next paragrah and skipping the proof on the first read, then place the proof in the appendix. The reader can jump to the appendix now, but you're giving a hint that it's better done later.
But if the proof elicidates the material and you do want the reader to read it before going on to the next paragraph, then place it right after the proposition. A good practice I wish I saw more of is to have an outline of the proof after the proposition and the detailed version of the proof in the appendix.


text:
Is scientific progress hindered by page limit and page format?
There is a trend in STEM: things get more and more complicated over time.
There seems to be two things that are not matching up with the pace of our time: page limit, and page format.
Page limit: for example, to me this is anti-interdisciplinary. As results concern more disciplines, it is necessary to introduce background of many disparate fields. But due to the page limit, how can one reasonable do this? A picture is worth a thousand words, but how can we fit these pictures into our publication if there is a tight page limit?
Page format: for example, suppose you have very long equation (that runs across an entire page) or very large amount of data, how is it we are suppose to fit them into, say, two columns?
Does anyone have similar concerns or have seen how publications deal with them?

Your data comment suggests it's common in your field to publish all your data in the paper?

This seems to be an invitation to a discussion rather than a precisely framed question.

Physical Review Letters has a page limit. Physical Review B does not. For a given article you choose the appropriate journal.

"suppose you have very long equation (that runs across an entire page)" Is it ever really necessary to an equation that long? I would argue that in such a case the onus for a clearer presentation is on you and not on the journal.

Yes.  In particular, page limits have caused many authors to design terrible figures that contain many tiny, unrelated graphs packed close together.  This makes scientific papers harder to understand.

In my area usually page limits do not involve figures, and are in fact often word count limits.

@ChristianHennig In physics there is usually a word limit and a formula for computing the number of "words" for each figure.

You choose the appropriate journal for your research. In my experience, and field, journals with page limits are for rapid dissemination of results. The article would usually have deferred a lot of methodology to other papers or the put the details into a supplementary section which doesn't count towards page limits. More in depth and longer papers end up in different journals. If when writing a short paper I realize I need more space than is available I would just reconsider which journal to publish in.
At the same time, there is a skill to writing a short paper and sticking to the point. You have a message you want to convey to a reader so stick to it. Many papers I've read just keep going and going and really should of stopped at an earlier point.
You ask about the figures. Have you considered whether you need so many separate figures? Plots can often be consolidated and perhaps if you thought about your data differently you would need less figures. Or long equations? Either it's important to the paper so you include it, or it's not that important and you don't include it (perhaps just referencing another work where the equation is important).
Why put lots of data in a paper? Show a short summary and point to an online storage system (like Zenodo) which can store the data for you in machine readable formats. One of the most annoying things I find is people putting long tables in papers that a) serve no purpose to the narrative b) can't be easily copied from the final PDF. When I'm reading your paper I don't need to see the tables showing you did lots of work. I only need to see the tables if and when I'm reusing your work and that will occur at a different time to when I'm reading your paper. So don't make me have to skip over lots of data when it's not needed.

In addition, nobody has time to read lots of long papers. Scientific progress is probably greatly enhanced by enforcing page limits.

"page limits are for rapid dissemination of results" PRL has long claimed that, but if you look at the data it's actually a slower journal.

"Plots can often be consolidated"  Can be but it's not reader-friendly.

Hence the qualifier often not always. And this doesn't just mean stick all the curves on one plot just think about the data differently. Maybe you don't need to plot every curve, maybe there's some quantity that summarises the curve that could be plotted as a single point instead etc.


text:
Objectively speaking, are STEM jobs more difficult to acquire than STEM graduate degree?
I've recently been doing some (non-serious) job search. My background is STEM with a focus on computing.
What I have noticed is that the requirement to get a job with many tech companies seems to be much higher than the requirement to obtain a graduate degree and even after getting a PhD it does not seem that you would even match half of the requirements that these companies are demanding.
Does anyone else feel the same?
For example, I am currently looking at a company called Groq. For one of their few non-senior roles, it says: requires 2-10 years of experience in machine learning or software engineering, knowledge in hardware accelerators, familiarity with a subset of: linear algebra, Python, computer vision, natural language processing, C,  reinforcement learning, FPGA, recommender system, C++, among others,  and preferably publication in top-tier machine learning conferences.
I can firmly say that even PhDs whose primary research is in ML do not have these backgrounds that the jobs are looking for. This job description just doesn't seem to make sense in terms of what actually happens in school. A computer vision researcher is unlikely to be doing reinforcement learning and FPGA programming at the same time. A Python programmer is very unlikely to be somehow doing C programming at the same time and vice versa. Different people fundamentally uses different tools. Nobody designs integrated circuits while doing linear algebra (of any depth) at the same time.
This is just one job description out of hundreds I've seen and heard from other people. The numerous stories of STEM PhDs who are jobless or can't break out of academia seems to corroborate with my concern. I wonder if it is really true that it is harder to get a job nowadays than a graduate degree (or even a PhD) in STEM.
Can anyone who has been on both sides chime in on this?

To (mis)quote C. Northcote Parkinson: the ideal job advert has a sufficiently obscure set of requirements that it only attracts one applicant, removing the need for a time-consuming selection process.

What makes you say the job description doesn't make sense? It requires 2-10 years of ML experience, which any ML graduate will have. It asks for knowledge in hardware accelerators, and then the rest is "a subset of". So you can know C++ but not Python and still apply. For example, I'm no expert on ML, yet I can still say I know linear algebra because I studied quantum mechanics.

This is an apples/oranges question. The two aren't comparable. VTC.

Job requirements in IT are total bs and it's a well-known thing, and there are many kinds of it - small companies tend to post a magical unicorn requirements (be able to train NNs and write FPGA code at the same time) while big tech does whiteboard programming interviews which are utterly unrelated to the actual daily job process. Still, the job market is ever-shifting and somehow manages to handle all that.
The secret? In large, people in STEM-related industry use references instead of job postings to find jobs.
And to answer the actual question - yes and no. Academia does not prepare one for the industry job from day one as well as someone well versed in the industry can't just enter academia and thrive there. These are just different sets of skills.
In ML particularly, unless you're aiming for a "guru" consultant position, a single really successful model can become a business, so I'd say requirements are fairly similar: it's just how communicating results and requirements that differs.
If you ever consider taking the industry path - what matters is the now-acquired ability to learn and quickly sift through references (being able to do a cursory lit review in a day or less is a big boon!), job ethics, extracting valuable knowledge from experience and applying it to new problems... These things are universal, really, but one needs flexibility and agility rather than laser focus.
Both academia and industry like people who can solve problems, it's just that the latter has many smaller and commonly ill-defined ones whereas the former likes to go in-depth, as a general rule. And the one is not necessarily harder than the other.

Objectively speaking, are STEM jobs more difficult to acquire than STEM graduate degree?

Not in general. Individual jobs may sometimes be difficult to get into (for example, getting some jobs at Google or Facebook may indeed objectively be more difficult than acquiring a graduate degree), but most employment statistics I know agree that STEM graduates, to a large degree, get relevant jobs after graduation.
In that sense I am a bit suspicious about your claim:

numerous stories of STEM PhDs who are jobless or can't break out of academia

I have worked and taught in STEM for 15 years now, and from the top of my head I can't think of a colleague or fellow grad student that remained "jobless" for more than a few months after graduation. Not all of them scored great jobs, certainly, but everybody found something within the industry.
It's possible that the Machine Learning field is different since it definitely feels a bit overheated right now, but if you "can't break out of academia" with a decent ML degree you may be a bit too picky with what jobs you apply to.
Further, I agree with what Allure says in a comment. Your example job posting really doesn't contain anything that an applied ML candidate shouldn't have:

requires 2-10 years of experience in machine learning or software engineering, knowledge in hardware accelerators, familiarity with a subset of: linear algebra, Python, computer vision, natural language processing, C, reinforcement learning, FPGA, recommender system, C++, among others, and preferably publication in top-tier machine learning conferences.

Basically, if you did your PhD in computer vision, NLP, reinforcement learning, or recommender systems, you should have about 5 years of experience in ML, experience in at least one of the listed fields, probably quite some practical experience in Python and/or C++, and you probably have at least some experience working with hardware accelerants, plus some publications (if these are "top-tier" is always a subjective matter, I would not read much into this). All in all, you are in fact checking all the mandatory and even quite a few of the optional boxes. I see no reason why you could not apply to this job.

...And I could provide quite a number of anecdotal arguments to the contrary, most of them dropping out of academia and remaining unemployed before the PhD defense though.


text:
Should I cite or credit images I found online for a conference presentation?
I am going to do a conference presentation on so-called Smart Cities
As you can imagine, the concept of a Smart City is best conveyed using pictures (it is worth a thousand words).
I found a picture which I think can capture this concept

There are others like it,

Since I didn't create them, therefore technically I think I should credit these images, but it is a lot of extraneously and unnecessary information for the audience.
I also see that many people do not credit images when they are presenting, and I would wager a guess that most of those images are not generated by themselves.
Should I attempt to credit or cite this image?

(Not an IP expert, just a researcher who has struggled with the same question).
Even citing them may not be enough. Fair use doesn't extend as far as most people think it does: for the exception to apply, you have to be using the materials in a "transformative" way, not in the same way as the original work. Further, the conference may be considered a commercial activity even if you personally are not benefitting financially. Note also that the copyright holder may not be the author, but the journal in which the figure was published.
Thus, I suspect the "legally correct" answer to your question is that you should ask the copyright holder for permission to reproduce the image, and also ask them if they want to be attributed.
As you say, most people just use images willy-nilly, hoping that the copyright owner will not complain. In a conference talk in which the slides are not publicly available, that seems like a safe bet.
Note that for more mundane pictures (e.g., a picture of a dog for a computer vision project), there are some sites that specifically waive copyright and do not request attribution. This may be a good way to reduce the number of pictures that you need to cite and/or try to get copyright permission for.

"Safe bet" unless the owner of the images is attending the conference as it is the topic they are interested in...

What about permission to post the images in the question as has been done?


text:
Graduate advisors: what are some qualities that make a graduate student difficult to supervise?
I am asking this question to seek some perspectives from graduate advisors.
My question is: what qualities of a student makes him or her difficult to supervise? It is all the more valuable if this is based on actual experience.
Note that "difficult" is open to interpretation. The student may not necessarily be a bad student or poor learner; after all, most of the people who are admitted to a graduate program has went through some rigorous examinations in their lives. Maybe a student is such a genius, that he/she won't listen to you, and hence that presents a difficulty.

The challenge with this question is going to be that, aside from trivialities such as a student who does not have the necessary knowledge, my "difficult to supervise student" may be your "once in a lifetime awesome student". It will very much boil down to work mode preferences.

Strange question, but here you go:

Knowing better than the advisor (in reality or imagination) and hammering that point in to the advisor
Knowing better than the nature of the matter at hand and continuing to hammer at it without it sinking in (thanks to Darkwing and computercarguy for the original suggestion)
Being disorganised
Having to be told to do the same thing repeatedly, without effect, without proposing an alternative, or without explicit (justified) refusal
Being unable to write, even while having results
Being a brilliant writer, making weak results look better than they are
Being perfectionist to the point of ineffectiveness
Being sloppy, so that everything that the student does needs to be double- and triple-checked for correctness; sometimes, reintroducing errors after they have been corrected already
Being afraid of success and/or one's own greatest enemy

One thing that does not constitute a difficult to supervise student is a genius who doesn't listen, but gets results and writes them up. It may give a dent to the ego of the adviser, but, like a dent in a Jeep, it's a dent worth having.

It's a good list, but re (1) I love students who know more than me, and (5) can really be a skill of its own as long as they are still willing to improve results.

@xLeitix Note my "dent" comment. Point 1 is not about the student being better than you (I very much prefer them to be better than me than weaker ;-), but constantly harping about that. However, most of the time, when they do so, it's their imagination that they are better, because the really brilliant ones I found not to do it. But I know from colleagues that "genius" students let them know how much superior they were - and even iff (!) that were true, it is a pain to supervise them. Why didn't they pick a supervisor that matches their ever so superior skill? And to 5 (contd.)

... to 5. the point is that they write so brilliantly that they are in danger of falling in love with their own results. In other words, it can become very difficult to convince them that their results are not as good as they look by virtue of their grandiloquence. Of course, if they are critical enough and do not fall for their own words, great writing skills are a gift.

@CaptainEmacs As I don't want to write a new answer just for one (and a half) point, a suggestion to extend the list, if you feel it fits: "'Knowing' better than the advisor what the PhD topic should be about" and/or "Trying to focus on a very specific topic/procedure at the very beginning" (like "so if I apply that to this then I'll be done, right?!")

@Darkwing Hmm, I wonder if that qualifies unconditionally. They may have a good idea about the topic and they may be right with the specific procedure. It can go wrong, but I am careful with that particular case - I would rather subsume its ramifications under 1 or 3, if these would apply. Or do you have a particular scenario in mind? Perhaps your case can be sharpened?

@CaptainEmacs Well, as many of your points, it's something that is essentially a good thing at its core (having some idea of what you want to do like begin somewhat perfectionist in getting things right), but can be overdone/done under the wrong context. At the very start you often don't have a totally clear picture of what exactly you are going to do (because you might need to adjust once you make some initial findings) and as advisor you might not know what are the strengths of your student, thus feel at some point to either direct him, e.g. towards more theoretical or more practical work.

@CaptainEmacs It's getting problematic if a student is too rigid, perhaps out of insecurity, defensiveness, ego or some fixation with some topic, to adapt either due to findings or due to what they are good at. Overdrawn examples "But I want to work on solving N=NP, it's way more prestigious than this little sub-problem!" "I know I've got no clue about physics and have a hard time grasping it, but the initial topic draft had application of quantum physics to solve Y in it, so I better spend the first year getting into it instead of trying to apply Z from biology, I do understand, to solve Y."

@CaptainEmacs It might qualify as a sub-category of "Knowing better than the advisor" though I assume you meant that with regard to technical knowledge.

@Darkwing Ah, you mean the "crackpot mindset" - yes, that's a good one, although I interpreted that to be part of 1, to not be so unkind as to list it as a separate phenomenon.

"It is hard to fill a cup that is already full" might be included in point #1, but it might make sense to put it as it's own reason.

@Darkwing and computercarguy? Are you happy with the changes? I obviously tried to keep the textual consistency...

@CaptainEmacs works for me, and it's your answer anyway ;)

Grad students who do not communicate their problems / issues in a timely and effective manner can be tough to supervise. (I include the provision of incomplete information to the advisor in this category)
With such students, the advisor has to actively "interrogate" the student to find out what's really going on, and very often this is just not feasible. It means missed deadlines, results that are not trustworthy, and delays all-round.
Note: Students can be taciturn and still communicate effectively.

And this is the number one problem managers have with staff...

It is not obvious why checking in with your students--I'd prefer not to describe managing a student as "interrogation"--is often "just not feasible."

The amount and time spent on asking questions is one major point.
There are students who come to your office almost every day and want to have every little detail explained to them, and there are students who you don't see for months, and if they talked to you earlier you could have told them right away not to waste their time on X.
Both extremes are problematic, and student and advisor should aim to find a middle path, e.g. agree on a fixed meeting date/time once a week.

As Tolstoy said, every unhappy student-advisor relationship is unhappy in its own way.