text:
European COST Actions
I would like to ask if you think  the European COST Actions are interesting for researchers? Do you see any potential advantage to join any of them? If yes, I would like to ask you how I could join one action of my interest, they do not explain properly in the website.
Thank you very much in advance.

You can get involved in a COST Action through various means and steps, as explained in http://www.cost.eu/participate
In short, you can join as a member of a workgroup of the Action (wide open), as a management committee member (or substitute) - nominated by your country for an already accepted Action, as a proposal submitter - almost automatic nomination, as a (usually Ph.D. student) researcher participating in short-term scientific missions (STSM), etc.
If it is interesting? I think yes and that's why they are there (and receiving funding) for some 40 years now.
IMHO: Being involved as an external expert (e.g., to evaluate proposals) is the hardest path as your role assumes that you understand how the whole thing works so as to provide a fair evaluation. While there are guidelines in place to help you with this, having first-hand experience by being involved in some Actions is much more useful.


text:
Becoming an Engineer with a Math degree
I'm not sure if this is entirely the correct stack exchange for my question, but the career stack exchange seemed to have a different focus from what I'm looking for.  My question is:  Can I work in engineering (Aerospace), specifically in modeling/simulation/analysis, without an engineering degree?
There is a fair bit of background for this question so be warned.  I am sophomore Aerospace engineering student currently working through my 4th semester.  I'm taking 16 credit hours.  My classes are fairly challenging for me, as would be expected, but I can and do get A's in them so far.  I work for an Aerospace engineering company for about 30 hours a week with school, I've been with this company for about a month.  I've been hired on as year-round intern to do (obviously basic) modeling and data analysis.  My problem is that I really like doing the modeling/data analysis, and in school I have a hard time caring about my non-math and non-numerical methods classes.  If I switched to a math major, I would have a halved class load, and I would be able to take only courses on modeling and data analysis.
The obvious solution here would be for me to switch to CS, but every time I import 'system' into Python I die a little bit.  Its not something I personally enjoy, so I would like to avoid that if possible.  Basically, I want to focus on becoming more skilled at what I enjoy doing without doing unnecessary work.  But I don't know if I can continue doing what I enjoy in my future career without a degree that says "Engineering" on it.  I don't have enough information to make this decision so I'm hoping for advice from those that do. .

I don't know what you ultimately want to do academically before "work[ing] in engineering (Aerospace), specifically in modeling/simulation/analysis", but a former student of mine with a mathematics undergraduate degree (and a fair amount of physics, but no engineering) got a Ph.D. in Computational and Applied Mathematics at Rice University and has been an applied mathematician at The Boeing Company for over 10 years (see also this google search).

Seems a little hard to believe you could have a successful career in modeling and data analysis without importing modules in Python (or something far more onerous).  Many data analysts nowadays are expected to write code to interface with complex tooling and architecture.

Ditto to @Chan-HoSuh's comment about your allergy to importing the "system" module into Python... Having an aversion to this is, in many regards, in modern times, comparable to having an aversion to using the equals sign... And, seriously, Python is one of the handiest (scripting?) languages... Friendlier than Perl, for sure... though I did greatly benefit from learning Perl 30 years ago. :)

Note that in many places, engineering is a licensed and regulated profession. One of the requirements may well be a degree from an accredited engineering program. That depends on local laws, of course.
The aerospace industry employs a lot of engineers, of course, but not everyone there needs to have an engineering degree. It may well be that, depending on laws and the policies of an organization, modeling of various phenomena may not require such a degree. In fact, as a guess, it may well be that engineers (licensed) may only be required in the actual design and development process.
And, it might all be that a degree in math or statistics or CS might be a better qualification for some of the tasks required in the industry.
However, you are in an excellent position to learn the specifics for your case just by asking someone at your current company. You can get some pretty good advice by going to the employment office and just asking for a bit of guidance. Professors in your current program are also well positioned (or should be) to answer this question in light of local laws and such.

Also discuss with your current company whether not getting an engineering degree is likely to limit future prospects. You may be fine for the first few years doing modeling under the supervision of engineers, but find in 10 years that you cannot advance further, and take more responsibility, without an engineering degree.

+1 for "ask around where you are working now"

This pop up after 3 years. I've noted @Buffy answer which covers most part. @Trunk's Math angle is also in line
Noting the disjoint in the question's title and the content, I'll chip in the following.

... my future career without a degree that says "Engineering" on it

Depending on countries/institution, a degree can have 'engineering' appended to it.
Also, some organisations and countries can allow job title/nomenclature with 'engineering' affixed.
In some countries, the word 'engineering' or 'engineer' are regulated not only to practise but also in job title (so can't even refer a job title as one)
In some places, although 'engineering/engineer' is regulated, the word 'engineer' can still be affixed to a job title without the job itself regulated; hence one sees software engineer or systems engineer being use (without restriction).

So, depending on the organisation or country, your future career (in Aerospace engineering) is fail-safe. However, without being an engineer (licensed/registered), you won't be able to signoff a design/project/report.

On a sidenote, just as @Trunk has said, engineering students are grounded (or should I say drilled) in physical science. I recalled having to take a modern physics course (essentially quantum mechanics) during my undergraduate engineering program!

source: Stack Exchange

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

sort: votes


text:
Should I publish book chapters as standalone articles before approaching a publisher?
[Humanities - Post Doc Stage] Do you encourage the publication of chapters as articles prior to full book publication, with the aim to improve research profile? Or do you advise publishing a book of previously unpublished work? Or do you suggest publishing some and retaining other research? Please detail any experience of this in your response, with reference to approaching publishers if possible.

Some publishers won't republish existing work. And it is up to the publisher whether to publish something or not. Find a publisher and work with them.

As I understand it, in certain branches of the Humanities, typically the first publication is a book based on the thesis.  You are (if lucky) hired to an academic position, you work hard preparing your thesis for publication, and then that publication is the basis for promotion.  That was years ago.  Nowadays perhaps that "academic position" may be a postdoc, and that "promotion" may be a regular teaching position.

Publishers are going to look at your background before agreeing to a publish your work. Things looked at include:

Your citation metrics
Reviewers for your publication proposal
Your CV

Publishing some standalone articles will certainly improve all three, but you'd have less material when it actually comes time to publish a book (because the same material typically cannot be reused). So the question effectively becomes, "can I publish now or do I need a better profile?". Only you can answer that question, unfortunately.
If you don't know the answer either I'd suggest contacting a publisher now, and if they reject your proposals, then publish standalone articles first.

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


text:
What should a candidate ask in an informal phone call to Hiring Person in Department
Many positions, especially in UK, have an email or phone number for the Head of Department.
What should a candidate ask in these informal phone calls about academic posts?
Example:
For informal enquiries: please contact Professor --------------- on ------@---.ac.uk

To the head of department, ask only what is essential.

In the U.S., a departmental administrator will actually be the person reading many of the emails officially addressed to the department chair... And, in the U.S., certainly do not phone, but only email.

At applicant stage
Avoid asking anything unless it is absolutely necessary. If you do have something to ask, keep it short and clear. It is likely that the head of the department is very busy and there are a fair number of applications to process each year.
At candidate stage
Is the head of department your main point of contact for hiring? If they are, then I would freely ask them everything you are concerned about (except, obviously, things you can find online). They are trying to hire you, so they will want to answer your questions. At the candidate (rather than applicant) stage, generally you are the "guest of honor", so to speak, and they are the hosts.
However, usually there is a main point of contact aside from the head of department, e.g., someone in your research area who wanted to hire you. (I'm not familiar with the UK.) If so, then it seems prudent to direct questions there first.

It is entirely acceptable to submit an application without contacting the head of department, if you don't have any particular questions.

@avid Yes, good addition. I assumed the OP was at candidate stage.

The text the OP quotes is found in most UK job adverts, see e.g. https://www.jobs.ac.uk/job/BZK348/lecturer

Thank you all for your answers so far. Just to clarify, this is at the applicant stage.

@mcwkeaveney Good to know. Updated.

Don't be a pest. Especially at the applicant phase. And use restraint until you have an offer in hand. The head is pretty busy.

They are trying to find the best candidate and the selection process is a two way street. They are as much trying to see if you are the best fit for them and also demonstrate to you why they are the place for you to want to work.


text:
How do you console colleagues that that attribute a bad experience to gender/race/disability?
There are some comments that appear on this SE as well as frequently on the academic subreddits, that mention how to deal with some situation because of personal trait X.
Here is just generally one such example:

How do you handle students who speak to you in ways they would never
speak to a male teacher? For example, I just had a Zoom meeting with a
student. I thought he wanted to ask content questions; instead, he
told me how the way I have my class set up doesn't work for him.

I do know there are studies showing problems with student evals being baised against women and minorities, so there is some difference in experiences.
However, when a colleague mentions this to someone of that group (i.e. female prof. complaining to male colleague, black prof. complaining to white colleague, etc.), what is an appropriate way, or the expected way, to respond?
On one hand, I wouldn't want to be dismissive of their experience and how they feel. On the other hand, I wouldn't want someone to feel that they are being targeted/treated unfairly for something out of their control. Having lived in many countries, it personally never felt good (and would often ruin my day) to think it was because of race/ethnicity that someone was treating me poorly, and I did find comfort knowing they were just in general a rude person to everyone.  However, my own experience may not be generalizable.
So the two extremes of the situation seem to be:

Respond by sympathizing, saying sorry this is happening to you, and leave it there. If trying to actually help and give advice on what to change, may seem like blaming the person.
Respond by letting them know its not just happening to them, implying its not because of their personal trait but rather the student/others fault in general.  This at the risk of seeming dismissive of their experience.

What would be a helpful approach to such a situation.

I'm not sure this is a question for academia. It occurs more generally.

Do you think it is happening because of their gender/race/disability or not?

@Buffy the larger topic of people being racist etc. happens, but the dynamics in academic settings (students, teaching, colleagues, research on the topic of student evals) seems pretty specific.

@gib I'm not sure. Maybe sometimes it is, maybe sometimes its exacerbated by it.  What I do know is, like the quote I provided, and the many times my colleagues raise this, I have experienced the same situation without their personal trait.

OK. I don't have an answer, other than be considerate and respond in each situation as seems appropriate. I hope people can discuss this question without being outraged at opinions that are different from their own.

You have, however, phrased it as a question of interpersonal relationships and communication, not as an academic question.

@Buffy I agree it can be broad, but I am asking about discussions between faculty colleagues, wrt academic settings.  i.e. not a colleague complaining about a sexist comment at the grocery store.  I don't think its much different than interpersonal relationship and communication asked in questions like:   https://academia.stackexchange.com/questions/118465/how-do-you-build-a-healthy-and-productive-relationship-with-your-supervisor

OK, maybe I'm blind. But the example you give does not display any bias that I can detect. Maybe there is such bias in the parts you did not quote? A student complaining about an instructor's methods is not, by itself, evidence of bias.

Agreed with Buffy - you have not provided enough specifics for that to belong to Academia.SE and not Workplace.SE. This is not to say the question is bad; it's great and I am very excited to read responses. You mention academic subreddits - maybe there are examples which are more evidently specific to academia you could ask about if you insist on keeping the question here?

Obviously it's possible that either one of these cases could happen: there may be cases where someone encounters a hardship/problem/frustration due to race/sex discrimination, and there may be cases where a person encounters a hardship/problem/frustration that is non-discriminatory, but they incorrectly attribute this to race/sex discrimination.  One of the things that makes it difficult to distinguish these cases is that the intentions of relevant actors are not usually apparent from a single case --- evidence of discrimination sometimes only emerges via statistical evidence over large classes of cases (and even then it's complicated to infer).
Since both kinds of case are possible, both kinds of responses you mention will be reasonable in different situations.  I don't think there is any way to create a one-size-fits-all rule in the abstract case because the correct response is ultimately going to depend on how plausible/implausible the assertion of race/sex discrimination actually is.  In each of these cases you are probably going to have to form a judgment on whether the causal-premise of the complaint is plausible or implausible, and act accordingly.
You seem to be concerned about the case where the causal-premise of discrimination is implausible.  There are definitely some situations where you know for sure that the complaint has a false causal-premise.  For example, there are cases where someone says something like, "People would never do X to people of type Y" or "Ys never have to put up with X" and you are a person of type Y and have regularly experienced X and/or seen X being done regularly to people of type Y.  In dealing with this type of case, it is legitimate (and even helpful) to push back on a false causal-premise of the complaint, but there is some nuance required to do this best.  A good method in these cases is to express sympathy for the hardship/problem/frustration, but augment this sympathy by injecting examples where people of type Y have experienced X.  You can also explicitly reject their causal view of the problem if you want, and it is fairly easy to do this as a short aside in the course of making a larger statement expressing your sympathy.  If you do this effectively then your examples will bolster your assistance by exhibiting empathy for the problem, but you are also giving some information that helps to correct the false causal-premise.  Give the person some time to absorb this contradictory information and let the discussion stay on listening to their problem.
Ultimately, there is no incompatibility between giving sympathy for a  hardship/problem/frustration, and helping to diagnose the causal basis for the problem (including disagreeing with them on the causality).  As you point out, sometimes people are comforted to find that the difficulties they are experiencing are common to others, and have been successfully dealt with by others.


text:
Are there guidelines that say if post-submission publications must be cited?
I can see from this question Can I cite a paper published after the initial submission of my paper? asking if it is okay to cite papers after submission is answered as, yes- and sometimes you need to.
Alternatively, the question here Recently published paper deliberately not citing our very relevant work -- anything to do? suggests an answer to not citing a paper was because it was found out during the revision.
I think the question is a bit tied to my thinking and past experiences that I have seen in which the idea of citing papers that were published after the submission easily leads to abuse through long reviews. Meaning, if a reviewer sits on a paper for a year while publishing related work, it becomes an easy argument to make that the paper is now outdated and does not have significant contributions.  Likewise, one could wait until their own paper is published first to then say in a review that there is some paper that is relevant and should be cited.
Besides the malicious aspect, it also seems to open the door to never-ending reviews. Say a researcher creates something, does an experiment, and compares against other work. Then during review a paper appears. A reviewer then asks to compare against this new work. The person compares against that new one, submits, and during review a new paper shows up and repeats the cycle.
I know there are guidelines and ethics statements that say a reviewer delaying a manuscript for their own benefit is unethical, but are there guidelines that look at it from a timestamp point of view (e.g., papers are reviewed on the merits at time of submission)?

The author in your example may need to learn the phrase "that is beyond the scope of our current work".

@Anyon in this example, I am saying it is not necessarily out of scope. Maybe one example that came to mind is; someone designs a new type of battery and mentions it improves storage by 1% of the state of the art.  After 1 year review, there is a new paper that beat the same SOTA by 1% as well, so now its to compare against this one, or run additional experiments and improve slightly more.  Cycle repeats.

But there is also a "temporal scope". At some point the author has to draw a line between the current work and potential follow-up work. And, at least in fields I'm familiar with, journals tend to limit the number of allowed review rounds, which means this never-ending review scenario is unlikely.


text:
Can Master's Thesis at a different institution be applied towards a PhD Dissertation?
I am a computer science student in the USA, and I could not find any information about this online.
Say one were to pursue a research based Masters, and they completed a Master's Thesis. If they later wanted to pursue a PhD (at a different university) would they be able to use the publications in their Masters Thesis as part of the PhD Dissertation in order to further shorten the time to graduation (beyond just the waived coursework)?

Are you envisioning a "stapler dissertation," which comprises essentially n papers pasted together to make a dissertation, of which your master's publications would be a part?

@AzorAhai-him- I never heard of that term before. Is this common in Computer Science in USA?

I have no idea.

Not automatically and maybe not in the way you intend. It would depend on too many factors to make a prediction. Many, maybe most, doctoral dissertations in CS in the US are a single complete work, not a collection of papers. If the advisor agrees and the work extends the masters work in a significant way then it might work. But, as with all such scholarship, an earlier work can be quoted and cited but not "included" in a later one.
A dissertation need to be a new and significant work, even if it extends earlier work.
And whether the masters is at the same or a different institution probably doesn't figure in the equation, anyway.
Note also, though you don't ask the question, that in most places the coursework is there to enable a student to pass comprehensive exams. It isn't that it is "waived", but that the student has learned the material sufficiently elsewhere.
Some places might have required advanced coursework  but in many cases (including mine), there were two requirements for the degree: pass comps and write a dissertation acceptable to the faculty.
Also, having a gap in your education works against your specific plan, since others may have followed up on what you did earlier, leaving little yet to be done. You might have to embark on a different problem altogether. And an advisor might require that in any case.
So, it might work out as you'd like, but don't bet your career on it.

Every (European) declaration to sign when submitting a dissertation I've ever seen included a phrase like "The material presented here was not previously submitted in fulfillment of the requirements of a degree." Is this not customary in the US?

@Arno, yes, it is pretty  common here too, but the research can be extended, as I'm sure, is also true in Europe. But the OPs use of the phrase "part of" is a bit ambiguous.

At least when I did my PHD at Manchester in the UK the presentation of thesis policy said I had to either declare that no part of the work had been submitted for a previous degree, OR declare what parts had been submitted for a previous degree.


text:
Do less selective institutions have a lower workload for Ph.D. students?
Is the standard for graduating lower at lower-ranked institutions? How large of a difference is this?
Computer Science, USA specifically

The 'standard' is dependent on your supervisor(s) and the community he/she is part of.  I have a colleague who demands that his/her students achieve at least 5x the official requirement.  Otherwise, he/she refuses to sign-off on a student's thesis.

Can't say about CS specifically, but in my experience this isn't a meaningful way to think about things.
PhDs involve a much different kind of "workload" than an industry job or undergraduate school work. The reason is that a PhD is very self-driven. Your success, or not, is largely about whether you can commit yourself to doing the work necessary. If you can't remain motivated through struggles and setbacks, you won't get anywhere. If you overwork yourself, you may burn out and be unable to continue.
If you want a PhD just to get the degree and then get a job, then yeah, all that really matters is graduation. If this is your goal, then make sure a PhD is actually what you want to do. It probably won't be a net financial benefit, but if you want a job that needs a PhD then you need one. If, on the other hand, you want to continue in academia post-PhD, then graduation is only the bare minimum. Your success on the job market will be primarily based on your research output. If you do the bare minimum to graduate, even at a top institution, your resume won't look very good against those of other applicants you compete with.
Sure, there are external expectations, too. Principally these will be driven by your research advisor, but advisors come in different flavors at all kinds of institutions. Statistically, you'll probably find more people who are most highly driven themselves at top institutions, and they may project those expectations on their students, but statistical averages don't matter much for an individual student that has an individual advisor.
Read about the programs you may attend. They likely have public guidebooks that explain the specific expectations for graduation. Talk with prospective supervisors about their expectations. Talk with current grad students (and alumni if possible) to get their viewpoints, including those who are students not just at the same institution but who have the same advisor.


text:
Tips for finding chill PhD programs and advisors to apply to?
I'm in industry now. I'm applying to PhD programs but don't want to be under a lot of stress so that I can have time to slowly think deeply about problems and explore stuff without having pressure to deliver papers and results. And I want to be able to do other things. Any tips on finding universities and advisors that aren't too stressful? In industry it's generally well known what companies work their employees hard (Amazon) and what companies are more chill (Google).
Any university recommendations?
Computer Science, USA

We do not recommend universities (this would be a shopping question, which would be closed); I suggest you rephrase. "How to find such advisors" might be on-topic.

That said: I suspect doing a PhD might not be aligned with your goals. Academia's publish-or-perish culture is well known, and that includes grad school. Finally, I am surprised at the suggestion that Google is "more chill"; my (limited) knowledge is that all the FAANG companies require rather extreme effort/hours (but offer many perks in exchange).

There are definitely good advisors and bad advisors, and a very important step is finding an advisor that you get along with and can work closely with for several years. Having said that, I am quite confident that not one person I know who has gotten a PhD would describe the vibe as chill.

@cag51 People often joke that googlers work from 12 pm to 2 pm. I'm going to do phd to solve some interesting and tough problems, not get involved in academia's nonsense at publishing every incremental discovery and fooling people into thinking it's super useful.

@Andrew I went to some open houses and met some folks who said they were chilling.

Please explain the meaning of "chill" to us.

Well, I feel like this comment is not going to have any effect, but if you already feel that way about academia and you haven't even started grad school, I think you may want to take a step back and think about if there are other areas where you can find interesting problems. I don't mean this in a judgmental way, there legitimately are interesting problems in lots of fields. To me it sounds like you want to commit yourself to a situation you already know you won't like. ... Not to be depressing, but I've heard people say what you are saying now, and I have seen it not work.

I'm just trying to be helpful. I actually left academia for reasons related to what you are currently saying you don't want. You aren't going to change the system. I'm just trying to save you time in realizing this. But, it's up to you what you want to do.

@Andrew It's all about working the system, rather than changing it.

You're in the wrong line of business. Graduate programs are populated by those people who were at the top of their class as undergraduates, and professors were at the top of their class of graduate students. These are the people who are inherently competitive and driven in what they do.
That does not mean that every research group and graduate supervisor is toxic. For sure, some research groups are riding their graduate students pretty hard; others have more humane approaches. But in the end, every faculty is evaluated on the number of papers and grants they get published and funded, and that does put inevitable pressure on graduate students as well.
In other words: You will neither be successful nor happy in graduate school (or academia in general) if you are looking for a "chill" environment.

This doesn't answer the question

@JobHunter69 I'm pointing out that there is no answer to your question.

Consider the worst grad program in the world. It's not going to be populated by people at the top of anything, so your proof is incorrect

@JobHunter69 Look, smartypants. If you want to argue with everyone here, go somewhere else. You're asking for the opinion of people who have actual experience. You don't have to like it, but the arguments you're bringing forward are just not helpful. Even in the worst graduate program, the people there are still better than the 90% of people who don't go from undergraduate to graduate studies.

what a joke. a ton of grad students at top schools wouldn't even pass basic industry interviews. Most smart people wouldn't choose to be an overworked slave in academia. You're the one being unhelpful and your arguments are clearly wrong.

I guess I'm outta here. I've got better things to do in life.

As a thought experiment, let’s pretend for a second that there was at some moment in time a reputable CS grad program in the US that was “chill” like the google environment you’re describing — a place where people can just have a fun, stress free time working on the research they love, knowing that expectations in the program are low enough that they could get out with a PhD even while putting in minimal effort.
Well, what do you think is the next thing that would happen? Everybody and their cousin would be applying to this program, that’s what. After all, your preferences aren’t really that unique — there are a lot of people out there who like chilling just like you and dislike stress, just like you. And that includes some very smart, passionate people who actually would turn out to be very hard workers even when you don’t apply a lot of pressure on them.
So, the next thing that would happen after that is, the faculty running the program will find themselves inundated with a veritable bonanza of smart and extremely accomplished applicants to pick from. So, getting into the program will become insanely competitive. Once in the program, students will suddenly find themselves constantly comparing themselves to their other also very accomplished peers, and suddenly feel very motivated and driven to work hard so as to distinguish themselves in such a high-achieving environment. The faculty, realizing they have a great group of grad students on their hands, would realize what a tremendous resource that is to advance the research they are passionate about, so would raise their own expectations and encourage the students to work even harder. Doing anything less than that would just be throwing away the amazing human capital they’ve been put in charge of managing.
And that brings us to precisely where things stand today: grad programs are highly competitive environments where highly motivated, passionate students work extremely hard to meet the very high expectations imposed by the program and the academic discipline they are operating in. Sound familiar?
Well, good luck with your applications anyway, I hope you find what you’re looking for.

I'm sure your'e an ardent believer of the efficient market hypothesis.

@JobHunter69 market inefficiencies do exist, and the market for CS PhDs also has small inefficiencies you could exploit by doing your research and optimizing your grad program search for the things that matter most to you. But an inefficiency of the size that I think you’re looking for doesn’t exist. I wish it did — my own grad school experience, in a far away time and place, was actually relatively chill, so it saddens me that US STEM grad programs today don’t make such an experience possible, unless you are exceptionally lucky or brilliant.

Well there you go. There are inefficiencies but I disagree with you to the degree. Efficient markets occur when knowledge becomes common and everyone is rational. Grad applicants do not rationally optimize their work to time ratio. Most grad students don't even think look for chill programs. They care for prestige of the program, funding, advisor work area, etc. Furthermore, there is no common knowledge about what programs are more or less chill. If it was known which programs were more chill, possibly your effect would be realized.

And your deduction that the program becomes tougher when more people apply is very debatable. It could instead attract a ton of lazy students thus making the program even more chill. Google is quite prestigious and known to be chill, yet we are not seeing any changes in culture, except at gcp which has always been crap.

@JobHunter69 yes, anything’s debatable I suppose. Well, good luck, and please report back in a few years about the outcome of your chill PhD search…

It's always nice to see people who have no inside knowledge of a system debate whether that system works this way or that way. Sometimes the right thing to do is just take the word of people with decades of experience as truth.

This isn't the answer you want to hear, but it's the answer that's true: there's just no such thing as a "chill" PhD program. There's lots of variation in the amount of pressure that different programs place on students, but no matter where you go, you've got to work hard. The process of obtaining a PhD is notoriously difficult, and there will, let me repeat, will, be occasions where you're clocking in long days and long nights to make your research and writing deadlines. Getting a PhD is exhausting, difficult work and there just is no way around this. If you don't want to put in that level of work ethic, you're just not going to make it in academia.


text:
I've pigeonholed myself into machine learning and I'm applying to PhD programs
I'm applying to phd programs after being out of school for a couple of years working as a software engineer. The problem is that all my research and work experience has been in machine learning, but I'm not that interested in this field. Not only so, there's too much competition in this area for me to get into a good program. What should i do?

Look for professors who are interested in applying machine learning (ML) techniques in their areas.

These are two different issues. If you do not mind doing an AI-oriented PhD, there are some programs that are interested in the SE aspects of AI - how to design AI architectures for convenient use etc. They are not common, but this does exist. You also can bring in your industrial experience, some programs are interested in applications. However, if you really do not much care for AI, well, then it's simply supply and demand. Find a program that covers what you are interested in. Chances are there will be fewer applicants, too, in non-AI fields.

what field do you want to do a PhD in?

What degree(s) do you hold, and what country are you interested in? With a BA/BS in the US there is no real issue at all.

@Buffy only bachelors

@cag51 no idea. was hoping a phd would give me the opportunity to explore areas.

@JobHunter69 While you don't have to do the PhD in ML, you better have an idea of what field to do it in... It is a rather big endeavor and you can't really swap fields as easily as in programming industry. Doing some applied ML in different fields might be a more reasonable option to find a field you're more interested in, breaking ties with ML would be very hard though - for whoever gets you under their wing, your main value is ML, and not wanting to do it anymore is a tough situation to find yourself in because you'd be competing with way better qualified people with big head start.

Why do you think you are pigeonholed? Many people will do a PhD in a different area than their undergraduate (masters). People will do postdocs and become professors in different (but related) departments than their PhD degree. Assuming your undergrad is in any hard discipline (engineering, math, physics, cs, etc.) you can basically do a phd in any hard discipline.
When applying to a PhD program you are going to be evaluated based on your potential, not based on what you've already done.

I don't know if that's true. What will make a professor want to take on a student who has no experience in his area? And from waht I know the qualifications of a grad student is way different than undergrad. potential was what they were looking for in undergrad. grad is looking for concrete evidence that you can do research in that specific area

The answer is correct. I completely changed fields for my PhD, from ecology to cardiology. Professors understand that the most fertile area for growth is where one field meets another. A student with skills that people in the field do not usually have is very useful to have around. You're not the finished article as a PhD student, you're still learning, that's why you're still called a STUDENT. It's not about knowing everything about a subject. It's about being able to contribute to it.

With a bachelors in the US, starting doctoral study doesn't have you pigeonholed at all. In fact, if you have some research experience in pretty much anything then you will be a good candidate, other things being equal (grades, letters...).
Doctoral study (which I'd recommend over a MS, here) leaves you lots of time to choose an area of specialization. The only thing you need to be clear about is the general field, such as Math or CS, say.
The early program is filled with advanced coursework and probably only an introduction to research. The first hurdle is (most places) comprehensive exams. Only then do you need to be real specific and choose a dissertation advisor.
The situation is a bit different in some lab sciences where you need to join a lab earlier, but form most fields you are a "free agent" for at least a couple of years.
I advise doctoral study since you can get funded as a doctoral student (as a TA, perhaps) and have tuition forgiven. That isn't as likely for an MS student.
But since you've been out of school a couple of years, try to reestablish contact with old professors who can verify your skill and dedication.


text:
What age is too old for research advisor/professor?
I feel like I wouldn't want to work with >70 years old professors because they're too old and have less chance of coming up with new ideas. is this a reasonable concern?

No …………………………..

If a person has seen the world, all its beauty and many of its warts, and is willing to share his or her opinions, that’s a person I want to have a beer with. Now the fact is—you never really know how deep another person’s experience runs, but that’s where you roll the dice.

I would say 75. After that most people will decline even those with very active minds. But experience may vary.

@Mandrill Maybe, but the key here is "most people". Professors are not "most people". It is well-known that keeping body and mind occupied slows down the inevitable decline of both, and professors often are very active until a very high age. I have often discovered academics who wrote their most significant books after retirement, sometimes age 80+.

One thing to consider: if you plan for a PhD under their supervision, keep in mind their health may be more fragile; you should have a Plan B for what happens if they are not able to continue supervising you.

I had a friend who graduated as a last PhD student of a professor emeritus. While the professor had some health issues towards the end of my friends PhD, I heard my friend describe his supervisor as "A mind of a 20-something trapped in the body of an 80+ year old. I could barely keep up with him". Besides, there's this: http://phdcomics.com/comics/archive.php?comicid=2031 :)

No. It is a bad idea to make assumptions about a person’s productivity and level of creativity, in the context of academic research, based on their age. This seems to me like an example of using the “fast” (aka System 1), heuristic-based type of thinking described in Kahneman’s book Thinking, Fast and Slow, to form judgments, instead of the more deliberative, slow, “System 2” mode of thinking. Kahneman describes many examples of this type of fallacious reasoning and the ways in which it can lead us astray in decision-making situations.
Each professor is an individual. Some make better advisors than others, but you’d have to estimate how good they are based on actual details about their personality, recent and less recent track record of success in research and in mentoring, and other relevant factors. Age can only be relevant insofar as it relates to someone’s physical health or an imminent retirement. Many academics in their 70s still produce excellent research and successful PhD students.
Don’t make assumptions, and don’t use heuristics in making important decisions like choosing a PhD advisor.

Seconded. Some profs dry out on receiving tenure. If they are still active after that, you are probably fine (just kidding). The Fields Medal for math has famously limited its recipients to the age of 40 or below - when Andrew Wiles proved Fermat at the age of 47, this was a major embarrassment for them because they could not easily award him the medal and had to find a way to substitute for it. In short, "don't make assumptions". +1

@CaptainEmacs Why was it a major embarrassment?  I've never heard this.

@Kimball wouldn’t you be embarrassed if you were in charge of a prize claiming to be the highest honor in mathematics but found yourself unable to award the prize to the mathematician who solved the most famous open problem of the last century (or two), due to an outdated and blatantly discriminatory technicality in the prize rules? I know I would be…

@DanRomik Not if I believed the purpose was to recognize younger mathematicians, rather than honoring the best results or body of work.

@Kimball If you want to develop younger researchers, there are channels for that. But if you are the top prize in your field, limiting it to young researchers only becomes discriminatory. If you had started out as a prize for developing young researchers and turn into the top prize because most top results are achieved by these, and you are unfortunate enough to miss out on a major breakthrough of an older researcher, your prize sends out a message of prejudice and stereotype instead of an encouraging one. The IMU felt embarrassed enough to create a special prize for Wiles.

@Kimball if the people behind the Fields Medal want to market it in such a way, that is their right. However, they shouldn’t then be surprised when other prizes such as the Abel Prize become equally or more highly regarded by many than the Fields Medal, or even worse, when a situation emerges in which no single mathematics prize can hope to match the Nobel Prize in its cachet and public recognition as a canonical, ultimate honor. This confusing state of affairs is the legacy of the Fields’ age limit.

@DanRomik Excellently put. James Gleick's book on Feynman has a very crisp explanation of the issue, I paraphrase: a prize builds up reputation by excellent recipients no less than recipients, esp. excellent ones, get reputation by it; one of the reasons why the Nobel is so successful - not only was it early, but it gave, from the beginning, the prize quite consistently to outstanding contributions with only few blunders. It is in the interest of a prize as a signal of excellence to avoid false positives as well as false negatives. Fields messed up in that respect.

@CaptainEmacs: For what it's worth, it wasn't John Charles Fields himself who messed this up, see https://www.nature.com/articles/d41586-018-00513-8

@MarkMeckes Interesting find. To clarify, I intended "Fields" to denote the institution, not the person themselves.

I'm quite a lot closer to 80 than to 70, but if you made a proposal to me that was in my lane, or accepted a suggestion that I made for a research project, I'd serve you pretty well. I have a lot of experience and with that, a lot of ideas.
However, I'm retired, so that would be a potential obstacle and we would need to get the university to make a decision. But even if I were not quite yet retired, that would be an issue. I also enjoy the fact that I currently have very little professional responsibility and can pretty much do as I please. Some of those things are actually fairly "academic" though.
I'd be useless to you outside my lane, of course, but that was probably always true, though I was able to give some guidance to people with quite different research directions. Not as advisor, but as a committee member.
Some of us old folk still have a functioning brain. Some of us still have an interest in field, even if we don't publish, ourselves, anymore. But it is an individual thing, and not one to make generalizations about.
It might be worse to have an advisor who was so young and active that they had no time to give you when you need it. Every case is different.
There are a lot of things that go in to making a good advisor. One of them is the attitude that you are an important person and that they will do what they can to extend your education and advance your career. That probably isn't age related, but it might be.

Wow, I read most of your answers and for some reason I assumed you were on your mid-thirties...

@Mandrill, My kids are in their fifties.

Fascinating -- I would have assumed you to be in your late 40s or 50s. Also fun to learn something about the personal details of a long-time contributor on this forum :-)

So long as an academic is not suffering from cognitive decline in old age (and I speak here of serious cognitive decline; e.g., dementia, alzheimers, etc.), I wouldn't think there is any reason why they would lack ideas for research.  In fact, you would probably find that the opposite is the case --- by the time they are at the end of their career they have probably stocked up so many research ideas over the years that they have more paper ideas than they could possibly complete, giving their students plenty of possible topics they could take on as papers.  I speak here as someone in my early forties, and I already find that the rate at which new ideas come to me is faster than the rate at which I can turn them into publishable papers.  Consequently, I already have many many half-written papers and jotted down ideas, and I'm not confident I'll ever finish all of the ideas I've started.
It is possible that there might be some drawbacks to having an elderly professor as a supervisor, but I wouldn't think this would be one of them.  An older professor will also have some advantages in terms of breadth of knowledge and experience, and I can certainly think of a number of professors in my own field who are now in their seventies who are absolute giants in the field; any research students would be lucky to have them as supervisors.
Finally, you should also bear in mind that research supervision usually involves a "panel" of multiple supervisors, and while one is usually the primary supervisor, there is also support from others.  It is not unusual to have a mix of supervisors with different levels of age and experience (and academic level) and this will usually help ameliorate any disadvantages of younger or older advisors.
If an academic is in their seventies (or whatever advanced age is "too old") and feels that they can no longer do a good job supervising a research student, most likely they will just self-select out of the supervisory pool and only take on a supporting role on the panel, if that.  Others will self-select out of supervision roles completely because they are close to retirement and they don't want to take on a multi-year commitment of seeing a research student through grad-school; they have earned the rest after all.

It is possible that there might be some drawbacks to having an elderly professor as a supervisor - Yes, such as a greater chance of health issues and not being able available to provide secondary support for you down the line (e.g., getting you conference invitations, advice after you graduate, etc).

@Kimball - you would be surprised just how many retired academics (and industry folk) are closely associated with conferences, national-level review committees, and so forth. They are highly valued because of their experience and insight into the whole field.

I for one can understand your concern. BUT it also depends on your field, no?
In computer science I would trust an 80 year old professor who hasnt been working in the industry for 40 years less, than a professor who is 50 and still had some experience with rather modern technologies.
On the other Hand I believe a 80 year old professor of biology, psychology or medicine to be just as fit as the 50 year old professor. That is because usually professors still work in that field.
In the end it always depends on the person honestly. Had professors talking about how great they were in the 70s and are completely disconnected from the modern breakthroughs in that field, but had also professors in their 50s telling about how they worked in a really really big company just recently and worked with all new advancements but were just bad at teaching and I felt like they didnt even understand the new advancements.
Also had really great and up-to-date professors that were about to retire and it actually was sad when they retired as I would have loved to learn more from them.

Actually there might be significant advantages to working with an older professor. Consider that an older professor is more likely to be well-known and respected in the field. Reputation is a very important currency in academia. Your advisor's reputation could open doors for you.  E.g.

You want a job after you graduate?  A letter of recommendation from a very well-known professor will carry much more weight than a letter from a new professor that no one has ever heard of.
You need access to some specialized equipment?  A well-know professor probably has friends at other universities or national labs that would let you borrow it.
You need funding to complete some portion of your research?  An older professor probably has many contacts at various funding agencies from over the years.  A few phone calls might get your research funded.  A new professor just getting started won't have as many contacts.
You want to get your work published in a top tier conference or journal?  An experienced professor knows what it takes to make that happen, whereas a younger one may not.

As the other answers point out, this will be dependent on the individual.  Just because a professor is old, doesn't necessary mean they are well-known.  Evaluate each specific potential advisor.

I can't comment if a professor that is older in age is necessarily less capable to be productive from a physical/psychological perspective, but an issue to consider are the regulations regarding mandatory pension after a specific age. Depending on the country of the professor, they may be forced to leave academia after a specific age (in my country it is 67).
Having your advisor leave academia for a pension in the near future may be detrimental to your future carrier for many reasons:

If they leave before you have completed your PhD, you will need to change advisors, which may or may not delay your diploma.

People that are going to exit imminently are likely to not be as motivated as someone who has potential for future promotion.

If they are in pension after you have completed your degree, and you are looking for a new job or a promotion in academia, they won't be able to participate in any department meetings that would create a position for you, or in electoral committees to actually have you elected/promoted, so you are likely to have fewer allies in these key roles. A younger person will be able to help you for many years after you complete your degree, if you maintain a good relationship.


text:
How do you get better at self-learning by reading research papers?
I find it very hard to learn new things through just reading, especially research papers. Previously when I was taking classes I had homeworks to help me learn. I found it particularly helpful to work through some practice problems. Now, when I read something I'll think I understand what it's saying but because I don't have practice problems I tend to misunderstand or not fully grasp the topic and will also have a much shorter memory for what I learned.

Go through the line of argument yourself, fully working it out. Compare with other approaches in other papers.

Different sorts of papers require different strategies.  Are these papers summarizing experiments?  Short theory papers?  Hundred page papers in pure math?

This is a bit late, but hopefully it will be helpful. Learning by reading from papers can be difficult. At a baseline you need to have enough background knowledge to understand what's going on. I'll assume you do have this knowledge. From here, you can take some steps to improve your comprehension of almost any paper.

Take notes/highlight/summarize. More generally, make sure you are reading actively. It can be helpful to print the paper, or open it in a program that allows for marking or commenting. This will, if nothing else, help you quickly refresh yourself on the paper in the future. It also ensures that you are critically thinking about what you are reading.
Talk about the papers you read. If you are still affiliated with a university in some way, there must be others in your field who are interested in the same papers as you. There may also be a journal club of some kind. Either way, this would allow you to discuss the paper and hear other perspectives. Again, you're forcing yourself to think critically about it, with the added benefit of outside interpretation.
Pick papers that are directly relevant to something you are doing. This may be obvious, but if you read papers that are interesting and immediately relevant, it can help cement whatever you "learned" from it. This is as close to homework problems as you can get in the real world.
Consider informally "reviewing" the papers that you read. There are many templates floating around online that can help guide a critical reading. Again, this is all about active engagement with the material.
Related to the above, develop a consistent way you approach papers.
Accept that you may need to reread papers. Sometimes putting a paper aside and returning with fresh eyes can help with comprehension. I sometimes notice things on the second or third read that I missed on the first, even if I read it carefully from the start.

If you still find yourself struggling with comprehension or retention, it may be worthwhile to do some self reflection. Why do you feel you misunderstand and forget things? Is your misunderstanding a result of weak fundamentals? Maybe you need to brush up on the basics. Are you actually "forgetting" what you read? When we are in school there is a lot of external pressure to memorize facts for tests and assignments. Just because you can't recall a paper line by line doesn't mean you didn't "learn" information.
All these steps can help you improve your paper-reading skills, and it is a skill. The more papers you read, the better you'll get at reading them.


text:
What to do about PhD when one is interested in multiple areas?
Do you have any tips for students interested in 2 or 3 areas in the same department but not in the same area? For example, I'm in computer science phd admit in the USA interested in both cryptography and natural language processing. I need to choose now which area to pursue, so it's difficult for me to make a decision. Any tips?

Related, possible duplicate: How do I deal with diverse interests when applying for a PhD program?

See also: As a prospective PhD student, is it bad that I have interests in multiple areas of my field?

Why do you need to choose now? That is unusual in US unless you've been there a while.

Note that, while you may need an "academic advisor" early and may need to pick one, you are normally free to pick a different "dissertation advisor" later.

Pick an advisor you like to work with, and work in whichever of those two areas that advisor works.
In general I think interest in broad fields is overrated, you'll be able to find problems that interest you in most fields. If you like it well enough to be considering the field then you'll certainly like it well enough to find problems that appeal to you. The only other factor I'd consider is whether one field is significantly better for industry job options, but since CS isn't my field I can't speak to that.

If you entered with a bachelors only, then you will have plenty of time to narrow it down. Your first task is likely to take the advanced coursework that will enable you to pass qualifying exams. You don't really need to pick a topic until you are done (or nearly done) with that task. Look at a lot of faculty as potential advisors and choose on more than just a narrow area. For example, the helpfulness of various potential advisors.
You might also be able to take a course in each area and perhaps with those advisors.
If you enter with a masters it is much harder as the time is shorter, but take some time to look around first.
You can always change your research focus later if you are able to obtain permanent employment. Your dissertation need not determine your life.


text:
Would it be better for Ph.D. graduate school admissions to compress my undergraduate years for a Master's Degree?
I would like to go to a strong graduate school. Currently I have a somewhat high GPA at about 3.8. However, there is a program at my university where we can spend an extra year to obtain a Master's Degree.
I initially intended on spreading my workload and graduate on time by taking about 3 classes per semester. Would it better for me to take 4 classes per semester and graduate about half a semester late with a Master's degree? Currently, the workload is very hard, so I know my GPA will drop a lot, maybe 0.3 points or more if I take 4 classes.
I would like to attend a strong graduate school in Electrical engineering, so which choice would be more suitable?

There is no rush.
Admissions won't give you bonus points for finishing early, so you're having to compete with people who took more time on the same amount of classes.
From my personal experience, I rushed and completed my undergrad a year early and my masters a semester early, but it didn't gain me much. In fact, my GPA took a beating.
Also, I wouldn't call it late if you're completing the masters in one additional semester, that would still be one semester early since it sounds like a 5 year program (4 + 1).
If you want the best chances of getting into a top school: take your time. Either graduate with your bachelors or spend the two additional semesters getting your masters while attempting to get good letters, some research experience, and maybe even a publication. Trying to rush it further isn't going to help and gives you less time to do the important stuff for admissions (e.g., research and letters).

My initial impression is that the master's degree won't count for too much in your graduate admissions unless it is giving you a substantial benefit in some way - i.e. access to more research experience, or a depth of knowledge in an area tangential to your undergraduate work but applicable to the graduate work you want to do. Since you are describing this as something you can fit in with your undergraduate work, I don't get that impression.
I would get some advice from faculty at your current institution - an "add-on" 1 year masters sounds a bit sketchy to me - if it isn't a full masters program it sounds like just an add-on, and is probably intended more for people who are ending their education there.

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


text:
What do top Ph.D. program admissions in Computer Science think of students who worked after undergraduate?
I'm sure if I work in industry for a couple of years and then apply for grad school, I would not be disadvantaged compared to straight applying to grad school from undergrad.
What if instead I go work in industry for 5-10 years?
Specifically top Ph.D. programs in CS, like CMU, MIT, Berkeley, Stanford, etc.

I work at the first "etc." in your list of CS departments, and I regularly evaluate graduate admission applications.
Rather than guess at the answer, I looked through my department's actual Fall 2019 PhD applicant database, and read the faculty comments on the applicants I found with degrees granted more than five years ago.  The non-traditional applicants that we offered PhD admission all had most or all of the following features:

They had excellent academic records from strong undergraduate programs (but not necessarily in computer science).
They did not have embarrassingly low test scores.
They had significant recent course work in computer science, typically as a non-degree student, with excellent performance.
They had strong reference letters from academic sources, either their old professors (who still remembered them) or from more recent instructors from non-degree classes.
Most importantly: They had worked in a research capacity during their time outside academia, either within their company or collaborating with academics.

(The first four points are not that different from successful traditional applicants.)
Non-traditional applicants that missed one or more of these features were viewed with more caution.  In particular, some otherwise strong non-traditional applicants without recent CS coursework (or equivalent work experience) were recommended for admission to our MS program instead of directly to the PhD program.  Again, this is not that different from traditional applicants.
So here's my advice: If your industry job does not have a significant research component, you are probably better off applying to MS programs first, as a stepping stone to a later PhD.  (Keep in mind that there are two types of MS programs in computer science: course-based/terminal/professional programs, and research-based/thesis programs.  You want the latter.  All online master's programs are the former.)  Even before shifting back to graduate school full-time, you should carve out some time to take one or two advanced courses as a non-degree student, and to interact with the instructors enough that they can serve as good references.
Always remember: The main thing that PhD admissions committees at top CS programs are looking for is compelling evidence of research potential.  As Buffy says, being a code-monkey at Microsoft or Twitter won't give you that.

Why is it so much more important for nontraditional applicants to have research experience vs undergrad applicants?

@Hey A weak undergraduate record (either attending a weak undergraduate program, or getting sub-excellent grades in a strong program) can be partially compensated for, as you suggest, but only partially. Some people will view any applicant with a weak undergraduate record with suspicion, not matter how well they did later. (I'm not sure what you mean by "private research", though.  If you want your research to provide evidence of research potential, you need to make the your research public, even if only on your own web page.)

It probably would depend on what you do and how current you are in the field at the end of that period of time. A lot can change in CS in five years. If you stay current through your job or otherwise and can demonstrate it then you are probably fine. But a job in industry isn't usually about research and a doctoral program is. A masters program would be a bit simpler.
But like anyone you would need to make the case in your admissions materials that you are a good candidate for success in the program. And you will have a lot of competition from a lot of people who are pretty current in the field.
But, after five or ten years your goals may change. And going from a well paid industry job to the life of a poor student can be quite a change. But if you keep evaluating options over a period of time you can probably be flexible in your needs and goals.
The direct path is probably simpler overall, of course, provided you can manage it. If you can gain admission now, it might be worth doing it. If you can't get in now, it is hard to see your chances improve except via very special work experience. Being a drone at Oracle won't help a lot.


text:
What happens to PhD applications that are missing recommendation letters?
For your department and university specifically, do you still consider applicants when one or two of their letter writers never send in their letters?

Your question misses an opportunity to learn something. Why the restriction, unless this is a research question? The practice of the departments of a few users here doesn't give you anything actionable.

@Buffy Oh I just wanted some concrete examples.

It has happened before that an applicant was offered a PhD position although one of their recommender didn't send the letter, and it has happened before that an application was rejected because a recommender did not send a letter.

You may find useful to add information to the specific situation you have in mind to find anything actionable. There may be a polite way to remind the recommender to actually send the letter, or to ask them send it by email to the selection committee directly if the letter upload deadline has passed. There may be a way to change the recommender to another person in certain circumstances. Etc

@ojfewowmx I've just heard of people where their professors forgot to send in the rec letter in time. I'm deciding if I need to find a fourth recommender just in case, or if the phd committee will still review me if i miss a letter

Then, again, specific answers to the specific question you ask won't help you at all. Your case is specific, not general. Knowing how "other" departments handle it says exactly nothing about how those you apply to will. If you update the question you will get more useful help.

If you really want to know how you can be proactive in case one of your letter writers fails to write the letter, then ask that. Vladhagen gives some hints to a solution.

Usually, if a candidate is only missing one of three, we will still review the candidate. This accounts for the fact that recommenders are forgetful and not paid to write letters.
Candidates with no letters are not reviewed. Unless a candidate was internal, a candidate missing two letters is often not reviewed. The reality is that we have more quality candidates than open PhD spots usually.
In some special cases, if we can see that a candidate may have large potential, we might ask them to obtain another letter if they are missing two.
The bottom line for us at my institution is that a candidate might not get one letter because the person they asked to write one did not hold up their end of the deal. We will excuse that, all other things on their application being quality. But two or more letters? That tells us that the candidate themselves was not on top of things enough. That's not someone we want in our program.

I will add that I have occasionally seen applicants missing a letter because the writer never submitted the letter. The applicant always let us know before hand that they were having issues contacting the writer. If, for whatever reason, one of your recommenders is not submitting a letter, always contact the affected institutions. I've personally been known to give a few extensions for candidates that take initiative to let us know. In our system (and in most systems) the applicant themselves can see who has submitted letters and who has not.
Every application missing two or more letters was an abandoned application that had many other components missing as well.


text:
How do researchers keep up in the area if they're in a hot area like machine learning?
I'm wondering how researchers would keep up with all the new works if they're in a fast moving area like machine learning. There's significantly more research being published, so it would seem to be a major disadvantage to continue working in that area because you need to read so many paper that you wouldn't even have time to think up an idea and work on it.

We don't.  I have specific/narrow topics of interests, or open questions.  I only track these topics and questions.

Frankly, you just accept your limitations at some point and find a healthy pace. It is utterly impossible to keep up with everything. Personally, I have found that having a schedule for reading literature routinely helps: do it, say, after breakfast and then move on unless you need to look up something specific.
In pre-Internet era, people independently discovered ideas all the time. Guess what? They still do. There is no shame in that as long as you put a reasonable amount of effort in. But the "reasonable amount" varies person to person. Find an amount of literature absorbed daily at which you are productive and try to keep it up.
Furthermore, consider doing it in stages: there is some research in well-known venues which helps you stay tuned and connected, skim that. There are some of your own ideas: pursuing them costs time and money, so look them up to see if someone has had the same idea before. It is essentially a cost-efficiency analysis: sometimes you might spend a week chasing something you could read about if you could find it before, and that is fine. After all, you have probably gained something from doing it yourself, after all. Spending a few months the same way? Ouch.

A lot of the work even in a fast-moving area like ML is pretty derivative and incremental.  If that's your area of expertise, you can probably scan and dismiss a lot of it pretty quickly as not that special.


text:
How does the proof process in Elsevier work?
I have an article 'in press' with a journal in Elsevier. Having done some searching, it seems there are a few very similar instances/complaints that ran into the issues I am having with them.  What I can't find out is: why is it so problematic (I have asked the journal manager and copyeditor, but they ignore that question).
What is the actual process used by Elsevier to take a .zip of a LaTeX project and convert it to a proof? I would think they use LaTeX, but somehow my figures get mixed up, algorithms end up with figure captions, references get removed, equations are changed, etc.
Is it someone copy-pasting and ctrl-r? There are these 'Q's that say "you didn't reference this figure", but it was referenced, with a hyperlink, the same as the other figures. So I started wondering if there really is no system, and its someone manually typing things again (which seems so unrealistic for a huge publisher).
Some of the similar questions are many years old, and it seems there is a new SkyLatex platform Elsevier mentions. I thought I would be able to make edits there, but I guess the specific journal doesn't have this option. This is also motivating my question, how or why do these multiple journals end up with different LaTeX templates than the final version and then use different backend systems?

I think my favourite part about Elsevier copy editing was when the journal editors forced me to re-do my submission, originally in LaTeX, in .doc format, after it already passed the first substantial part of the review (and was near accepted)... Broke my fingers getting the equations right. All equations fell apart during copy editing. I was asked to check all equations and the copy editing interface encouraged entering the corrections for complex equations as LaTeX code.

Yeah the same things have happened to me a couple of times.
Most of the copy editing is outsourced and I think some employee just copy pastes your latex code into their template and does this in a very rushed and substandard manner. Occasionally they may correct a thing or two but I'm sure they do it because the typeset document looked obviously incorrect or the document did not compile with their version of tex.
The best experiences I've had with copy editing is with journals that do not use LaTeX. You are simply supposed to send your draft as a PDF and tables in MS Word. All the figures are dumped towards the end of the document and captions are placed somewhere else. Here is an example of an "Accepted Manuscript": https://joe.bioscientifica.com/view/journals/joe/aop/joe-20-0437/joe-20-0437.xml I don't even know how reviewers read this and not lose their mind when they're trying to understand Figure 3 for example. The caption is on a separate page, what the actual figure 3 is remains unknown and the location where Fig 3 is referenced in the text is 10+ pages away. So in such a scenario, the proof is actually miles better that what you had when you prepared your paper and everyone is happy :)
So yeah, going back to LaTeX typesetting, I think its just an incredibly manual process, there is no elegant "system" or automated typesetting pipeline. There are some web based typesetting clients I've seen (https://smartproof.cenveo.com/smartproof/login/sg). You see a markdown-like version of your paper but it is easier to spot mistakes, change links etc. Not sure how many people use this though.
In my view, LaTeX journal templates are just so that reviewers can read your article properly and digest it. I don't think it makes a difference when it goes to the typesetter.


text:
Academic integrity question on self-referencing and changing a paper after acceptance
The day before yesterday I got an acceptance letter for a conference paper, with the ability to make some minor revisions over the next week.
This will be my first conference for my PhD so it's a fairly important milestone.
The thing is, I submitted some work in progress to a small workshop half a year ago, got accepted, and presented that WIP there. There were no proceedings, so apart from the presentation (powerpoint slides) that I gave, no materials were ever publicly released to this day.
The conference paper was written very last minute and hastily, based on some results, and I asked my supervisor what I had to do with the workshop abstract. Typically for him, he replied "whatever". So I didn't do anything with the abstract while writing on the conference paper, and just left it to gather dust on my laptop.
Right now, I feel like I could use the extra "publicity" that 2 extra entries on my scholar profile would give me, but I'm not sure what to do with the workshop abstract. It's not exactly building on the same method, but does use the same data, and has an interesting conclusion, that wouldn't hurt to mention in the conference paper. However, that would change the narrative a bit (the improvements over previous state of the art would be less significant, even though that's not entirely the point).
I probably made a mistake by not archiving and referencing this work in progress in the conference paper in the first place (do you think so?)? That being said, what's done is done, and I want to proceed in the most ethical way possible.
If I archive the workshop abstract, I feel like I ethically have to cite the abstract in my conference paper, because otherwise I pretend that the improvement is bigger than it is. But then, I would suddenly add new references to the paper citing my own work, that was never seen by the reviewers. And that feels very unethical to me.
If I don't archive the workshop abstract, I might still use the results in later follow up work. I think this is the proper solution, since it was never published.
What should I do? Should I ignore the existence of the workshop abstract and take the hit in visibility in the scientific community? Or should I cite it in the conference paper? Is the latter ethical?
I would talk to my supervisor, but he is totally not approachable about these things. He usually says "don't bother me with this trivial stuff" rather than helping, if it's not a question directly related to my research. So I have no clue what is right to do.

By my understanding:* You've presented some work-in-progress at a workshop, without proceedings. You have a conference paper accepted and you've been invited to make some minor revisions. The workshop presentation is built upon data used by the conference paper, but the methodologies are different. The workshop presentation drew a conclusion that you're contemplating including in the conference paper, albeit, that would change the narrative a bit. You feel that you made a mistake by not [citing the workshop presentation] in the conference paper. You're also concerned that not citing the workshop presentation would mean that you pretend that the improvement is bigger than it is, albeit, you're concerned that adding a new citation, which reviewers haven't seen, is very unethical. You're considering building upon your workshop presentation in the future and publishing that work later (and you consider this as the proper solution).
My thoughts:

You are under no obligation to cite your works-in-progress, especially those that are unpublished. That said, you may choose to.
You should not extend your conference paper to include new ideas - e.g., the conclusion you drew in your workshop presentation - since they haven't been peer-reviewed.
You could later publish your work-in-progress with citations to your prior conference paper. Alternatively, you could combine that work-in-progress with your conference paper to derive a journal article, the former aspect would be considered a new contribution (since it hasn't been published previously). In both cases, you could - if you wanted - cite your workshop presentation, since it presented some early results.

*I've summarised my understanding, since I'm not sure I've correctly understood the details presented by the OP.


text:
Would a professor be angry if I neglect to take classes within the research I'm working in as an undergraduate?
I am an undergrad currently working in the lab with a great professor and doing interesting work. I promised the professor that I would take more relevant courses related to the research I'm working on to help me with my research.
However, I found that there are some other courses that are more interesting to me and more marketable as a career skill. I want to take those instead but also continue working with him, but do you think he'd be angry if I went against his strong recommendation to take more relevant classes?

The professor can certainly be angry with your decision to go against his recommendation; however, this is far more likely to happen if you do it without explaining him several things:

your intention of not taking the courses he recommends
your motivation to take the other courses instead
and most importantly, your motivation and expectations from working in his lab

You certainly don't have to follow his advice and try to explore as many options as you want as an undergraduate, but I would give your professor an explanation BEFORE and a chance to make his points one more time. If the professor is actually "great" and professional, he would totally listen to you and understand your decision – nothing to be mad about.
Sometimes, professors treat some of their undergrad assistants similar to the grad ones. That is usually a good sign – you seem professional and valuable enough. However, this comes at a cost of them unintentionally assuming you want to continue working in their lab forever. With you clearly explaining your reasons, motivations, and aspirations, you have a chance to be as professional as you can be and maintaining the best possible relationships.

While your advisor may want you to take classes relevant to his interests, ultimately, it’s your degree and your career.
Where the two are in conflict, you need to focus on what will help you graduate and move on to the next stage of your career. If that means getting a job in industry, then you should focus on that. On the other hand, if this is someone you want to continue working with beyond undergraduate research, you may want to see about meeting him halfway—take some courses you want, and some courses he wants you to take.

The professor would not be called great if he would be angry with your choice towards a career which you think is best suited for you. There is no point in following all the professor's advice. You are not a PhD student, you are an undergrad - the time when you should explore as much as possible.
Of course, you could convince that you are doing those courses informally through video lectures or self studies and might want to discuss with him after finishing some of those courses.
I don't see any reason why I would be 'angry' if my undergrad research student does not follow all my advice, if it could give my research a different direction altogether.

Would your professor be angry?
(In the U.S. context) professors understand that undergraduates are still exploring their classes; you are not contractually obligated to take those further courses (unless you signed something to that effect). It would be (within the range of) normal for a professor in this situation to feel disappointed or upset when learning that you had changed your mind about this course of action he was expecting, but he should not take it out on you or be vindictive.
Why might he care?
In the near term, if you do not take the recommended classes, you may not be able to advance further on the work you're doing with the professor; this might mean the end of the job. Backing out on what you describe as a "promise" would be bad form in general. If the promise was also part of why the prof currently has you in his lab (investment in training you, with the hope that you will train yourself further), then the promise has even more importance.
What might be the effect on you?
So, this might end your job in the lab, if the coursework is a necessary co-requisite. You might find it hard to get the professor's recommendation for graduate school, if you choose to pursue it. (And/or the professor would have a harder time making a convincing case for your interest and skill in the field.)
Red flag check
Is the professor prone to expressing anger? Did the professor force you to make a promise about this? If either of these is true, you should find an ombudsman (university position of being a neutral 3rd party) or talk with the DUS (director of undergraduate studies in the professor's department) or another person you trust for advice.
If you are still interested in taking the other courses, I would recommend that you:

Study their syllabi and see if any skills meaningfully relate to the skills you would get in the recommended classes.
Look up on job sites what some of the marketable applications of the recommended classes are
Talk with other students in the lab or seniors in the major about the value of the skills from those classes.
Consider options you're willing to accept (e.g. not working in lab and taking desired classes; taking one recommended class and one new class; taking just the recommended classes and honing your lab skills).
Decide whether to bring the dilemma to the professor (if you trust him and your mind is truly not made up, and if his reaction to the different paths will impact your decision--e.g. whether or not you can keep your job in lab).
Otherwise, if you decide not to take the classes you promised to, tell the professor as soon as your decision is firm, so he has as many options as possible.

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


text:
Is top 20% GRE scores enough be a strong applicant for an EECS/ECE PhD program?
I am going to take the GRE soon. My practice tests end up being at V: 158 (80%) and Q: 162 (80%). I didn't care too much about the quantitative section in the practice test so my real score should be higher. However, my Verbal seems accurate. I don't know about the writing, but I'd guess to around a 5 if things go well.
Question: Are these scores good enough for a PhD in electrical/computer engineering or computer science (not decided yet, something in EECS) at schools like MIT/Stanford/Berkeley? Should I be wasting my time preparing for the GRE? I had thought that GRE was completely useless, but after some searching online it seems it actually carries weight.

Why don't you care much about the quantitative section? I was always told the quantitative section is the most important for engineering and hard science graduate programs and you should aim for a perfect score there to get into top programs.

@Thomas Well, the main reason that I didn't do well on this practice exam is because they were so easy that I had become careless (thinking about the problem without actually writing anything down to tackle it and also ending sections early without checking work.) However, I did think that it was useless simply because of the fact that my entire college history is based on quantitative stuff (GPA, math/CS courses, research exp., work exp. etc.), so I figured that GRE was there just for the Verbal/Writing stuff.

The quantitative questions are easy, but the danger is running out of time in the exam. They get used as a filter -- if you can't ace these easy questions, your application is not worth reading.

@Thomas The only trouble I have is the brain energy to last 4 hours. If I am not tired, I can typically complete the quant section in half the time necessary. The problems though is that i tend to make dumb mistakes on every test I take.

@A_Happy_Student if the admissions committee learned that that was your attitude, they might fear that you'll make dumb mistakes throughout your research and prefer a different candidate. Some schools are dropping the GRE from admissions decisions, and I personally think it's a dubious criterion, but if the schools you are applying too require it, then you should take ALL the sections seriously, and not blow any of of them off. You can't know that the admissions committee will feel the same way about the relative values of the different sections as you do.

MIT EECS does not require GRE scores.

Aim for 90%+, especially on quant. Many (top) programs won't even look at your application if you are not at that range, unless something else on your file (really) stands out.
That being said, several EE/CS programs no longer require the GRE, MIT included.

What is your alternative? Why do you consider studying for the test a "waste of time"? If the exams are required for admission then, I'd suggest that you should do what you can to make the best effort possible. You are in a good program now, of course (UM), but the schools you suggest draw the most skilled applicants from the best programs in the world. The competition is fierce. Work hard. Do your best, knowing that nothing is assured at this level.
Even if the exam carries little weight in general, it might be used in marginal cases to indicate to someone in the process that you are (or aren't) simply superb.
But in general, do everything you can to maximize your "portfolio" in every category that might be a factor in acceptance.
There is no try.

Thanks for the motivation. I think that it's a waste of time because I have an ongoing research project that's pretty time consuming. Having to spend time preparing for the GRE takes time away from it, and also I really have no interest in memorizing a ton of random unused esoteric English words with popular usage dating back to the 1800s. (my greatest weakness)

Don't sacrifice long term goals for short term success, I'd suggest. It may be that the project will figure higher in the estimation of the proposed schools than the GRE, of course. That is especially true if judgements are heavily weighted toward interviews and such.

Indeed, so do you consider my GRE scores adequate enough for admissions or should I still devote some time?


text:
Very short phd interview presentation in just 2 slides
I have been invited for a phd interview and I was asked to prepare a 4 minute presentation with a max of 2 slides only on myself and my research interests. The fact that it's extremely restricted in time and number of slides makes me a bit too anxious. I'm not sure what info I'm expected to present in such a short time and in just 2 slides. Any tips?

This might depend on your field and the country in which it occurs. Say more? In particular, how focused are you expected to be on a particular research topic?

@Buffy it's a computer science phd in the NL and it's a pre-defined phd topic. In the email, all they said regarding the presentation is that they expect me to present myself and my research interests in no longer than 4 minutes and in not more than 2 slides.

@scaahu thank you, I saw the answers on that question, there are some good tips. However, what's mostly bugging me is the number of slides. I don't know what content I'm supposed to put in just 2 slides.

I'm still thinking about a proper answer, but don't make the mistake of using "dense" slides. You want to make an impression, not flood them with detail. Forcing you to create such a presentation is a great idea, I think, since it forces you to focus.

They want you to be very specific and very quick, that's fine. That's good.
Slide 1: Who are you? Your academic past, or some other relevant information (e.g. industry experience, if relevant to your future research). That should take about 1 minute.
Slide 2: What are your research interests? Did you do a masters, and if so what is it about, what was the main result? Other things that you'd be interested in doing during your years as a student. Here it's important not to veer too far off course. Especially if you're joining a "pre-defined" program, but showing additional interests is a good thing.
Both of these slides can be set up as bullet points that cover the main sentence from each point, with or without "reveals", up to your preference. And practice with a friend, and with yourself (record and time yourself).
Good luck!

+1, I'd even suggest to replace the second slide with a figure that shows the result. A picture is worth a thousand words (and I'm sure OP can talk about their thesis without further prompts).

I'm worried about slide 1. The overall focus of everything should be forward looking, not the past. While the past can't be ignored, half the talk shouldn't be backward looking. Introduce the past only to show how it invigorates the future.

@Buffy: Yes, but if you want to talk about who you are, you need to say who you are. Where did you come from? What did you do? That's an indelible part of the question who you are. It's an introduction. The future? I know the future. You want to be a PhD student in this program.

2 slides in 4 minutes is not an excessively low number; I'd be worried more about four minutes than two slides. The restriction is probably to make people speak from their knowledge and use the slides as a visual aid, rather than reading from Powerpoint. You want people to be listening to you except when you point to a graphic - not ignoring you while they read a slide.
My advice would be to put no text on your slides, except perhaps your name. Choose 2-4 important images, figures, or other visuals that illustrate your work, and use the slides for those. Have confidence in what you know, and you'll find that you don't need to take prompts from your own slides any more. Practice what you want to say out loud plenty of times, to make sure you don't forget something important and to make sure you're within the time (in an interview they almost certainly will penalise you if you go over time). If it helps you, maybe put a few subject headings on an index card as reminders.

You should be able to summarize your thesis in 5 minutes or to talk for 2 hours about a subset of one paper.  -said a teacher I admire
In addition to (perhaps meld into) the great answer by inkblot, consider the possibility of a table on either interests or accomplishments.
Something with headings like Topic/Finding (not the full title)/Publication (add a fn for ref at bottom of slide, but the just the journal and perhaps year is enough for large text in a viewgraph.
Allows for quick scanning of the content, forces you to organize topic...and sorta emphasizes that you get things published (which is bringing the bacon home, getting the ball over the goal line).
Examples might be something like (within a topic of Taniana-steel examination)
Electrical properties/ Superconductivity at 1K, under presssure/ Science
Electrical properties/ Frustrated heating/ J. More MechE Papers (in press)
Application testing/ Underformance in pick axes/ J. Mining Tools
Application testing/ Failure in fracking pump/ J. Petr. Engin. (submitted)
Etc./Etc./Etc.
(You may have some papers off the beaten track of the thesis but just put them at the bottom of the table and make clear with a cell highlight or a line across the table that these are outside the main topic.)
Of course, you can do the same thing with the hierarchical structure of PPT bullets.  But a table looks cleaner and easier to read than the indented bullets.  Also, lots of busy people are used to seeing dashboards.
If there is some iconic image to dress up the slide, consider to add it, so that there is a little visual impact and something showing actual content. For the example above, I would do the graph of transition point of the superconducting Taniana-steel...as it is your most noteworthy event.  Obviously in a longer talk you'd have graphs from most of the papers and one per slide.  But you don't have the time.  And so, it will be more in the mannner of an illustration that is good salesmanship.

The OP seems to be in the position of giving a presentation at a PhD interview, not a presentation based on work previously done during a PhD. So I am not sure how relevant the details in your answer would be for the OP

Don't use slides at all. They know your name. They have your resumé. Just talk. Say why you are passionate about the subject you wish to research. Say why your academic achievements qualify you to research it. Make eye contact as you do so.
If you use slides they will distract you from making those key points, and they risk distracting the interview board too. You want them to focus on you not on your slides.
By all means prepare slides that you never show if that helps you plan your talk. But don't show them!

I don't foresee this going down well with a job interview committee

Maybe it depends on local practice and maybe on the subject matter. I do not claim that my experience is universal. Nevertheless, if I were on the committee I would be looking for just what I have prescribed. And I have sat on more than enough such committees (UK and Central Europe) to know what is wanted.

This is in the context of someone being interviewed for a PhD place/studentship. Is that the context of your extensive hiring committee experience?