text:
What should a faculty member outside of the US do to move to a top-tiered American university?
I have three close friends who are ambitious and young junior lecturers at universities in Thailand, Indonesia and Singapore who are interested getting academic jobs in a top-tiered American university.
How might they go about achieving this? What can they do in the meantime to increase their chances, compared to academicians who are already based in the US?
Neither of them are American citizens, although one of them studied in the US and another in the UK. They all work in the humanities and social sciences. I know that entering the academic job market in the US can be expensive, with all the traveling. And my friends live more or less at the other end of the world.

Somewhat related, but not a duplicate: http://academia.stackexchange.com/questions/17694/is-it-more-difficult-to-score-a-tenure-track-position-in-the-us-when-applying-fr

As discussed here (Is it more difficult to score a Tenure Track position in the US when applying from outside?), getting a US tenure track position from e.g., Thailand might be tricky. JeffE pointed out that it is not necessarily impossible, however, your friends would likely need to be on the top of their fields in that case. Your friend from Singapore seems to be a different case, as the universities in Singapore (at least NTU and NUS) have an excellent reputation around here (something that can, unfortunately, not be said about universities in Thailand or Indonesia).
In any case, my tip is to try to get a postdoc position in the US first. Postdocs are often reasonably easy to get into (at least in CS, can't really say for social sciences), and can act as a step ladder of sorts to faculty positions. Anyway, your friends need to be aware that the academic job market is no piece of cake in the US. Hence, no matter what they do, they need to expect that getting a professorship at a top university may simply not work out, so they should have a fallback plan to account for this case.

If "junior lecturer" is a permanent faculty position, I'm not sure that going backward to be a postdoc makes sense.  Anyway, many postdocs are only available to candidates within the first N years after their PhD.

I interpreted Junior Lecturer more as something like a Research Assistant. Clearly, if the friends in question are already more senior, my answer is likely not feasible.

To give some thoughts on my own question:
Foreign lecturers in the US are common but from my anecdotal experience (I am not an academician) a lot of them began their academic careers in America, probably transferring from being a grad student there.
For academicians who used to be based at universities outside of the US and Europe, my impression is that they were mid-career and already well-known and respected in their fields before they made the move. They were usually specifically recruited by the American university.
Having some sort of visiting professorship stint in the US and presenting work at conferences in the US might help with the exposure, I guess, but I am not sure.

Publishing.  If your field has "A" journals then publishing in them will add to your credibility.
Co-authoring.  If you can manage to have co-authors in the U.S., you can come over during your sabbatical or visit their school for a few months. Make more connections, gain more visibility, present your work in informal or formal workshops at all the nearby research schools. Once people know who you are, they will think of you when a need arises or your application will carry more weight when there is a systematic search for a candidate.
References. Strong letters from reputed academics that are known to US schools.
Networking and presenting at conferences. Networking at top conferences. If you can manage to have your work be presented at top conferences, that would give you lots of visibility and also opportunities to network.

Staying and Traveling in the US is expensive but the harder part is reducing the information asymmetry (about your future publishing potential) between you and your potential employers and also convincing them that you would join, even if you did get an offer. For example, some school in rural Virgina may want to hire you but they probably won't try because they don't think you will come live in a rural culture which would be very alien to yours.


text:
How do I add my ORCID to papers authored by myself?
I have a few papers that have already been accepted and published.
I recently signed up for an ORCID.
Is is possible to add my ORCID to these already published papers,
and if so, how do I do this?
Response to comment
Ideally, I would like my ORCID to be listed on the paper itself or on the official website of the journal article.
Nevertheless, I would consider having the paper listed on my ORCID profile to be a good partial solution.

Do you want your ORCID to be listed on the paper itself/on the journal website, or do you just want your ORCID profile to link to the paper? The latter is definitely possible if you log on to your profile and select "add works", but I don't know about the former.

@user2390246 See my response to comment in the edited question. You could post the steps to "add works" as a partial answer to my question.

I've not (yet) seen any journals offering retroactive addition of ORCIDs. It's possible they might do so in future but I wouldn't bet on it.

I don't know if it is possible to add your ORCID directly to the paper in question (probably not), but it is possible to link to the paper from your ORCID profile.

Go to your ORCID account (signing in if necessary)
This should bring up a page with your "Biography", which consists of several collapsible tabs (Education, Employment, Funding and Works).
Next to the Works tab, click on the button for "+ Add works".
You then have several different options to proceed. The quickest is "search and link" which allows you to search a database such as PubMed or CrossRef, find your paper, and add it to your profile. I won't go through the full details of each step, but if you follow the instructions on screen, it should hopefully guide you through.

This would have to be done by the journal itself. The journal would need to embed your authenticated ORCID iD into the article's metadata, and amend the online version of the article in order to include your ORCID iD.
Retroactively adding an ORCID iD to a published work is no easy task. Like Andrew, one cannot recall any journals or publishers stating that they will retroactively add authenticated ORCID iDs to the metadata of existing published works.

Please do not add such remarks (for more information email ....) at the end of your answer.

@wythagoras - How is that spam? The question is about ORCID - the email address is support@orcid.org.

@WaiHaLee I'm stating that it is not really accepted at SE to add email address at the end,if the author of the question needs more information, he/she should comment, not have to email.

@wythagoras the email does not belong to the answerer.

@TobiasKildetoft Hence I removed it. Why do you address me?

@wythagoras Because I have no idea what you are objecting to. The answerer is providing the information needed for the OP to obtain further information.

source: Stack Exchange

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sort: votes


text:
How much information should I include in my lecture slides?
I will soon be teaching my first class as an assistant professor.
The class is made up of 130 undergraduate students,
most of whom are in their first year.
The class in a introductory course,
so I will be giving an overview of the field;
for each lecture I will going through one different topic,
with most of the material being qualitative rather than quantitative.
Last year the class was taught by Colleague A,
so I am adapting his material to prepare to teach the class.
Colleague A's lecture slides tend to be too sparse,
i.e. there are few words on each slide,
and it is not easy to follow the train of thought by reading the slides.
Another colleague, Colleague B told me that
students had mentioned to Colleague B that
students were unhappy with the lack of details on Colleague A's slides.
I feel a little stuck because
when I prepare slides for an academic presentation,
I try to keep my slides more sparse
so as to not overload my audience
who may be trying to read my slides and listen to me simultaneously.
As I prepare the slides now,
I feel that I may be erring on the side
of putting too many words in my slides,
e.g. the entire slide is covered with words.
How do I find the right balance of how much information
to put in my lecture slides to keep students happy?

As a university student, thank you for asking this, I can assure you that your students will be thankful

This might depend on what you're teaching, and whether it's an intro or more advanced course.

re: "few words on each slide, and it is not easy to follow the train of thought by reading the slides" - in an ideal world, the purpose of slides is not to be read, it is to serve as a visual aid during the lecture. People cannot read much or understand complicated diagrams in real time. So few words and simple illustrations are good. Now, your circumstances may require that your slides also need to be read by students later, in which case it makes more sense to include more text - but ideally, that should be the role of a textbook or separate lecture notes.

The best courses that I attended had sparse slides to help the professor present the topics (important formulas, diagrams that showed something, key words, ...) and additional lecture slides or a book. This is of course a lot more work for you and it really depends whether the subject you teach changes a lot over time, there are good online resources ...

@BenCrowell I agree. My philosophy is to do continuous improvement through incremental changes. As this is my first class, completely doing away with the lecture is extremely risky. I plan to incorporate more active learning elements as I teach the class repeatedly over the next few years, if the department is willing to trust me with this class.

Recommend you read Tufte's three books on the visual presentation of information - your university library should have them.

Here's a general guideline:
Figure out whether you want the audience to pay attention to you, or to the slide
They can't do both. A large part of the time, you want the audience to pay attention to you and the words you're saying. At those times, the slides should be as sparse as you can make them. Really, the only function they have is as a reminder to people whose attention has momentarily lapsed: this is what I'm talking about, this is where I am in the line of the story. Also make sure, during these moments that you're not looking at the slides. The audience looks where you look, unless you make eye contact with them.
But sometimes, you want the audience to focus on something in particular. Perhaps you're taking them through steps in a proof or derivation, perhaps you're explaining a complicated diagram, you may even be reading out a quote. These are the rare moments when you're asking the audience to really focus, and raise their energy levels for a moment. Here, you're allowed to have dense slides. These are also the slides that you're spending a lot of time on, so make sure to put the effort in. Use all the visual tools at your disposal to make the message as clear as possible. At this point, you're actually allowed to look at your own slide, because you want the audience to do the same thing.
Finally, do not mistake slides for learning aids. If you want to give students something to help when they're studying, create a version with added notes and put that online. Don't clutter up your slides to make them serve two purposes.

+1 for the this: Do not mistake slides for learning aids. If you want to give students something to help when they're learning, create a version with added notes and put that online.

If you are going to depend on added materials, make them available to the students before the lecture. I find writing an extreme distraction from listening, so I try to write as little as possible during lectures. The more material I know I have, the less I have to write.

@PatriciaShanahan The promise "this will be online shortly" is not enough?

@PatriciaShanahan: I have the exact opposite impression. Writing down what is going on is the best way for me to memorise it. In fact, the lectures I understand the best (except the ones which were essentially revision for me) were the ones for which I could take notes without even looking at the blackboard (ie by ear). I say blackboard, since I find that it is generally much easier to follow a lecture which uses blackboard (or whiteboard, of course) rather than slides. I think they are ill-suited for an extended lecture (mostly because stuff disappears before I can properly internalise it).

The exception is, of course, when I can barely (or not even) keep up (due to an extremely poor lecture, lack of sleep, the material being way over my head, or a combination of those). In these cases, I can either take notes and not understand anything, or stop taking notes and focus on listening and/or filing the gaps in the lecture. I usually opt for the latter. If I still can't really keep up, I just doze off.

@tomasz Yes, of course there are people who benefit from writing notes. They can choose to write their own notes, regardless of whether good notes have been provided or not. I cannot choose to use notes that have not been provided. Good, detailed notes fully accommodate both of us. No notes may work for you, but not for me.

@Raphael Having the notes in front of me during the lecture works much better because that way I know what is in the notes, and whether I need to add something or not.

stuff disappears before I can properly internalise it -- very well put.

I agree with @PatriciaShanahan - it may just be because I'm dyslexic, but I always learned far more in lectures when I wasn't trying to write everything down as it was covered. I DO learn from writing, but I do that by writing my notes up after the lectures. For students like me, having separate course notes and being able to pay attention during the lecture itself is great.

Slides have a dual purpose: to help the lecturer through the lecture, and as a study aid for students. Because of this, I use two versions of slides: one for the students with a lot of details, and one for me with very few details. These are both produced from the same source (LaTeX), so there is minimal overhead on my part. I use my slides to guide me to tell a good story. Then the students have the whole story for studying later.

Good idea, but slides are not the best format for reviewing the material.

@Davidmh: What is?

@Davidmh If it is LaTeX, the students' version need not look like slides, even though it uses the same source. Beamer supports an article mode, for example.

I think the dual purpose nature of many lecture slides is what makes them bad for both purposes.

@Raphael But that's probably because not many lecturers realize that you should have two versions of the slides, which is why this answer exists.

@JiK I fail to see how you get good slides and good lecture notes out of the same sources, short of interleaving two otherwise (mostly) independent documents. Comparing my latest article and the corresponding talk, there is almost no overlap, and that's some of the images.

@Raphael: We are talking about lecture notes/slides for students, not research articles.

@DaveClarke In my mind, that means we have to take even more care with what we do.

I'll outline what the BEST professor I have ever had did (and this applied to everything from 1st to 4th year classes in the fields of business and engineering but could be adapted to other fields easily):
He had enough information on each slide that you knew what it was ABOUT, but nothing else. The remainder was left blank and they were posted online well in advance of the class they were used in. This meant that the students could print/download them and fill them in in class as he did.
During class he would pull up the slides on his tablet and then write and fill them in. This included everything from definitions to equations and the solution to examples. This meant that students ATTENDED class to get the notes (other class only 30%-40% of the students ever showed up), and in class they not only heard and saw the material, but wrote it down too which I found helped immensely not only with paying attention, but for recollection as well.
An average slide may look like this:
                                    TITLE
  ---------------
  |             |       Word to define:   (blank)
  |  Picture    |
  |             |
  |             |       Word to define:   (blank)
  |             |
  |             |
  |             |       Word to define:   (blank)
  ---------------

and in class he would go through, and explain the image/diagram, and then not just SAY the definitions, but write them in his own slides that were up on the projector. The other thing he was awesome at was actually pausing and waiting for students to catch up with what they were copying down.
Too much information and students in my program (engineering) would simply stop going to class because they could get all the relevant material directly off the slides. Too little information or slides not made available before the class made it REALLY hard to follow along - I find that I end up lagging behind the professor in these cases because taking sufficient notes at the same speed a professor is talking is difficult. Also, posting a complete set of notes online (even if it was after the class) for the students also resulted in class attendance dropping in my program.

This style is a disaster for me. I write slowly, and while I'm writing I cannot listen or think. Too much writing during the lecture, and all I get from the lecture is what I wrote - no understanding. I have to then treat the notes as a textbook and try to understand afterwards.

I usually adopt a method similar to Dave's. I have my course notes, which is a latex document (not a beamer presentation, to reduce overhead) and the presentation.
The presentation has very little text. You don't put text on presentations (there are arguments against even bullet points). I usually put images, diagrams, equations and etc, the things I want them to see so they can understand the underlying concepts. After, they can see all the little detail in the notes, which are on a "printer-friendly" format, since it is not formatted as a presentation...

Bullet points are fine, as long as they match the nature of the presented content. Generalizing, I would argue that any presentation approach is valid and useful, when it naturally matches the essence of the relevant content (and, perhaps, some other factors, such as context, style, audience, etc.).

I didn't place any judgment on bullet points. I merely cited that there are arguments against it, for instance: http://www.brightcarbon.com/blog/no-place-for-bullet-points-in-a-presentation/. Personally, I try to avoid them. Sometimes I fail :)

I see :). Well, I guess, it's all about the balance and to know what type of presentation to use when... BTW, the blog post you've referred to, seem more like a rant (which the authors actually warns readers) than a solid argument on the topic. The claim "there is never a good case for using bullet points in a presentation" is supported neither by solid arguments, nor research on the topic. Anyway, I don't try to avoid bullet points, but I try to prefer richer visual methods whenever and wherever is feasible and appropriate.

Here's how I would approach this problem. As you've mentioned, it is a known fact that overloading presentation slides with information is a pretty bad idea. At the same time, the students' feedback indicates that they seek more detailed information on the topic(s). Therefore, the optimal approach to solving this dilemma is IMHO to keep the slides' content sparse enough for best readability, while, at the same time, to have additional, more detailed, information materials hosted separately and linked from within the main presentation or, perhaps, better, from the class' website (or both).

The right balance: Keyword imprinting.  If you find your students rushing to write things down, you're doing something wrong.  This is an exceedingly common pedagogical failure.  You're purpose isn't to get them to pass tests.
What to do, if students have been habituated to write things down from high school is to not put much on the slides, but put the detail on-line.  With only a keyword, they'll HAVE TO listen to you to understand what you're talking about. Key words can be remembered easily and will make an impression when reading the textbook.

As I continued to ponder the question
of what is the right amount of information to put on my slides,
I came across writings by
Martin Fowler.
His philosophy to using slides is:

When I use slides, I design them to be a VisualChannel: an accompaniment to my words, not as a stand-alone "Slideument".
  (See link)
  The main principle I've tried to follow is to think of them as a visual channel that complements the audio channel which is my spoken words.
  (See link)

In my opinion, this is very wise advice.
In addition, as mentioned in this answer,
I can give a separate set of notes for students to read
in order to help them when they are studying.

When I see slides during a presentation I want to see more detail than less for the most part. Put what's important in there. I tend to like to read as well as listen.
In some cases I'll read the slide as I'm listening to the presenter and listen as they go through bullet points.
As a presenter you're told not to simply read what's on the slide but use the slide as a summary. So it's not uncommon that they will skip or sum up multiple points. If you skip a bullet point it's ok but if it's something I want to know more of then having it on the slide gives me the opportunity to ask more about it in class. If you leave it off altogether then I don't know what I'm missing.
The downside to putting more info than less is to not make the font too small that it can't be read. If you really care view one of your slides with different font sizes from the back of your class room. Or use more slides.
Also, to answer the others that say make two sets of slides, more often than not I would not read the slides later on. I take notes in class from the slides and presenter but that's just me.

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text:
Would students feel uncomfortable if I include in my lecture a quote which is somewhat sexually suggestive?
In my lecture, I am thinking of using a famous quote by Winston S. Churchill:

A good speech should be like a woman's skirt;
  long enough to cover the subject and short enough to create interest.

I like this quote because it clearly expresses the idea that
while you should go over the important details in your speech,
your speech should not be overly detailed.
However, I don't know if some of the students may feel uncomfortable
if I use this quote in class.
Question:
Should I play safe and avoid using this quote in class,
in case some students are offended?
What I decided to do
Although the Churchill quote is quite memorable,
I agree with the answer which says:

Whether you actually believe that or not, telling that joke gives students the impression that you do. That perception makes the classroom environment more unpleasant for a female student and less conducive to learning.

I will find another way to express my idea without the quote.
In response to comments
Several commenters have pointed out that:

My general advice is if you need to ask someone else if it is appropriate, you already know you will get into trouble.

That is good advice.
I had a "gut feeling" that it was not a good idea to use this quote;
partly I asked this question because I wanted to understand
why it was not a good idea.

There are better quotes that make the same point, e.g. 'I would have written a shorter letter, but I didn't have the time.'

@henning I don't think your quote expresses the same idea as Churchill's quote.

My general advice is if you need to ask someone else if it is appropriate,
you already know you will get into trouble.

It depends a lot on the country, the culture, and how you present that quote. I believe in France it could be acceptable, if given with enough historical context and oral precautions.

It depends on country culture and so on. Teaching about Churchill will make it almost natural.  In chemistry we and here we won't care.  At least 20 years ago and where I am it was so. Now we have to write she/he....

There is an easy advice for any of those types of questions: If something in the back of your mind is uncomfortable enough to ask it, the answer is: Don't.

Even if none of the students in your class are offended, you are teaching the unintended side lesson that it is ok to say offensive things.  Don't.

Avoid, but not for that reason.
Sometimes it is a teacher's duty to do things that may offend members of their class. A biology teacher who avoids the subject of evolution for fear of offending creationists is not doing their job, and there are plenty of other examples. The problem here is not that the joke could offend; it's that it gets in the way of learning.
It treats women as eye candy rather than as thinking beings, implying that a woman's clothing should be chosen for the benefit of male onlookers rather than according to her own priorities.
Whether you actually believe that or not, telling that joke gives students the impression that you do. That perception makes the classroom environment more unpleasant for a female student and less conducive to learning.
Humour has a place in teaching. Used judiciously, it can help hold the audience's interest and keep them engaged. But for your female students, at least, this particular joke is unlikely to serve that purpose. There are plenty of other ways to say it.

I like this answer even better than my own.

I'm familiar with the quote and I understand that it's well-intended.  But don't do it.  You're asking for trouble.  What passed as acceptable 70 years ago does not always fly today.

Perhaps the world was nicer back then ? You could walk down the street and people would smile and say "good morning etc" now all you see is people watching their smartphones...

@SolarMike: https://xkcd.com/1227/

@SolarMike  No, I don't think so.  I think it's just that objectification of women was considered more acceptable then than now.

@SolarMike  I don't think this is about smartphones and headphones, I think it's about whether a joke objectifying women that might have been acceptable 70 years would still be considered acceptable today.  An argument that courtesy is disappearing is not a good argument for repeating this quote in the context described by the OP.

@SolarMike If somebody has headphones on, it signals that they're not looking for conversation with random strangers. (Perhaps they are using the phone to say good morning to loved ones? Perhaps they are nervous of strangers?) In either case, the courteous reaction is to respect that preference. https://en.wikipedia.org/wiki/Berthold_Woltze#/media/File:Berthold_Woltze_-_Der_l%C3%A4stige_Kavalier.jpg

@SolarMike er... you're saying you see them coming and allow them to bump into you anyway, because you find their discomfiture amusing? I think we have somewhat different ideas about what constitutes "courtesy".

Hi, @SolarMike. I say "hello" to all my neighbors, the bus driver, and even random people I cross on the street, and yet I would not like to be in a class/presentation and receive such kind of objectification. You are mixing things here that have nothing to do. The world was not nicer 70 years ago. For women, the world is significantly nicer now.

Honestly, I don't think the woman's skirt part adds anything substantive. You can make your point perfectly well without it. "A good speech should be...long enough..." and so forth. Including the phrase makes you seem as if you do not understand the current bounds on professional discourse.
I don't feel offended, but it makes me question your judgement.

“Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.”
― Antoine de Saint-Exupéry, Airman's Odyssey
What purpose does the dress serve? Although, honestly, it's remembered 70 years later, would leaving out the dress have changed that? I don't know...

Don’t do it. You only risk alienating female students, who might already feel alienated from research staff – precisely for the same reason.
Would you do it if we did a little gender-swapping exercise?

A good speech is like male genitalia; too short, and it is just uninteresting; too long, and it will hurt people.

You did not only swap genders though.

@Azor-Ahai I don't understand your comment. I said that nabla did "not only sway genders" you say nabla swapped women's clothes to men's anatomy. Thus you confirm they did not only swap genders but also clothes for anatomy.

@quid Oh, I misread your comment, i didn't see the "only," although I don't think the clothes/anatomy swap is important.

@Azor-Ahai you are free to think so, but I highly doubt that this is objectively tenable. In any case I am pretty sure that many would agree that if we'd swap  genders back now in the metaphor in this answer then the result would be more inappropriate than what is in OP right now, by a considerable margin. So much so that anybody asking if it was appropriate would likely be assumed to be trolling.

To be honest, I (male) would find it in my culture to be completely ok (and even funny) to bring the new quote about male genetalia. It might be a little bit steange if presented by a man, however, if he attributed the quote so someone, it would be again ok. I'm not sure if Churchill's quote would be acceptable, though.

It's not merely a swap of gender. Your suggestion involves genitalia (original didn't), ridicule (original didn't), and hints at violence (original didn't).

Aside from just being sexually suggestive, this quote assumes a straight male audience.  That is it’s an analogy that only works if you’re “interested” in women’s legs.  In this joke the woman is an object whose purpose is to visually entertain men, not a subject who maybe chose her skirt length based on the weather not based on your opinions about her legs.  Find a metaphor that works for all of your students.

When I worked at my college radio station, I got some good advice.  I asked how do I know for sure whether a certain song I might want to play might be offensive to anyone.  The answer I got is that if you feel you have to ask whether it is appropriate, then you shouldn't play it.  I think that applies here.  If you feel that you need to ask whether people might be offended, then maybe you should use a different quote.

The quote would be reasonable in a few contexts - if you're teaching history, it may be used to describe the sort of person that Churchill was. In a broader context, it could be used when showing how womens role in society evolved in the 20th century. The quote itself is historical, and academic students should be mature enough not to be personally offended by history.
But that is not why you are using that quote. You're pulling the quote out of its historical context, and try to apply it today. The fact that it was said by Churchill isn't that important here, just trivia. The subject of your lecture is not history or Churchill, but (academic) writing style.

Exactly. The OP isn't proposing to examine this quote academically, they are suggesting endorsing it to their students "Follow Churchill's advice: ..."

The intent here is to be clear and concise.
Be clear and concise in your teaching.

I am a female student. I would not appreciate the use of this phrase in class, but if it was used in a smaller context with an established relaxed but respectful working relationship it would be fine for me. So, depends on the student!

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text:
Is providing an unpublished dataset worthy of coauthorship?
I’m working on a paper and I realized I do not have an adequate dataset (for reference, this is in a subfield of machine learning), nor do I have the time to personally go and create one. A colleague and friend of mine offered to collect the data and give it to me, as it would be useful as a benchmark for some of his own experiments later.
In this case, “collecting data” means finding and equipping participants with technology to monitor them perform a simple task for a brief amount of time (5 min).
Since this colleague is a personal friend whom I’ve worked with in the past, I have no qualms about listing him as a coauthor (and will most certainly do so, unless it is unethical for some reason). I am curious as to the general case of whether providing someone with an unpublished dataset is insufficient, sufficient or should guarantee coauthorship. I should emphasise that in my field, data is not something that begets the results but rather serves as a test to determine if a proposed technique or algorithm is well-suited to the task outlined by the data.
To put it simply: is providing data enough of a contribution to warrant coauthorship? Would it be unethical to list someone as a coauthor if they only created the dataset?

Just a note: You're not going to get a yes/no answer to this question (and if you do, you should discount it because this isn't a yes/no situation.) The best you can hope for is a guideline that you can apply to your own situation to judge for yourself.

I'm really hoping to foster interesting and relevant discussion more than get a hard answer. I fully expect that the only generalized answer is "Well, maybe." I just realized that this question could help/inform others in the future with similar situations.

Vote to close. This isn't really the place to "foster interesting discussion."

@Corvus: I fail to see how this is different from many other authorship questions we get. It’s a clear, yet not overly localised scenario. The only possible problem I see is that the answer may be field-dependent, but I have no background in such fields that would allow me to say.

When in doubt, offer co-authorship. It is then up to them to decline or accept.

Do you need to include these data (as part of the supplemental data) in your publication? (If you don't include it your results might not be repeatable for instance) The answer to this question will be closely linked to your initial question.

It is not usually a requirement to provide the dataset, however, there is a trend in the field to make datasets available on request so the experiment can be repeated if possible.

The Vancouver protocol gives authorship according to the following criteria:

Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND
Drafting the work or revising it critically for important intellectual content; AND
Final approval of the version to be published; AND
Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

So collecting data fulfills the first criteria. Therefore, the nice thing to do is to offer a co-authorship for your colleague. It is then up to him or her to decide whether he or she would like participate, which would entail fulfilling the other three criteria as well.

In this case, “collecting data” means finding and equipping participants with technology to monitor them perform a simple task for a brief amount of time (5 min).

Be careful not to underestimate the amount of time needed to recruit participants. The recruiter usually has to write several emails and advertisements, answer phone calls, brief and debrief the participants, prepare and take written informed consents, etc.
In answer to the comment, if your colleague accepts the co-authorship, ask him or her to write about the data collection, participants, motivation and possible limitations of the test, how the results can be interpreted and so on. Machine learning that matters should communicate something back to problem domain. This would be sufficient to fulfill the second Vancouver criteria.
Anyway, some fields have very different conventions, so your mileage may vary.

Obviously standards vary across fields. In some physical sciences, providing the data might not rise to authorship if the process of obtaining them was not considered significant creative work. Something similar would hold in many of the social sciences unless the data were really something special. In biology, my understanding is that providing new unpublished data would certainly warrant coauthorship and that providing old published data is often enough to clear the bar.

That's why I tried to explain a bit about my field. In some fields (such as biology), data is essentially unprocessed results. In mine, it is merely how we find out if a proposed algorithm or technique is suitable for a specific task. Thousands of people can all work on the same dataset and produce different and publishable results.


text:
Rude interviewer on an interview panel
I just had an interview for a role that was a perfect fit for me. This is a research role in a University. During the interview, the professor who was making the hire commented on how my skills in computational modelling was a close fit to his research project including the amount of upper division quantitative units I have taken; in my undergraduate program I took two math and two physics units every semester.

Of the remaining two other guys in their 50s, one was constantly berating my Alma Mater for being slightly lower ranked than this current University.
He also berated my average GPA without taking into account the level and load of the units I was enrolled in.
In addition, he was constantly berating my long term career goal while also putting down Elon Musk and the national research group of the country I did my undergraduate in.
He even went as far back to nit-pick my grades in middle school.
There are no standardised questions asked by the two other interviewers aside from the professor making the hiring

At some point the professor who was making the hire had to rebuke this old man who was on the panel.
Throughout the interview, I politely yet logically articulated my argument as to why his views were flawed.
To be honest, I was shocked at how the interview turned out given the culture in academia and research.
Is there anything I should do in the future if something similar comes up? How common is this?

This sounds like the Peter principle, with enough time, everyone rises to their level of competence +1 ... What can you do? difficult - they pick the interview panel - what you can do is what you did : respond calmly, logically and clearly...

This seems like more of a rant than a question.  If you'd like to make it a useful question that others could benefit from, I think it could be shortened to 2 or 3 sentences, to the effect of "how should one behave when a member of an interview panel seems to be acting rudely?"

I don't know what "berating" means as you've used the term.  What you consider berating might have been innocuous to others.  There's no way of knowing with actual quotes.  Also, a 50-yo male is not an "old man".  That also didn't help me sympathize.

Could you tells us what country this is?

@QuoraFeans how does this help with anything?

Maybe because culture in academia is not the same in every country?

I suggest you post this question at Interpersonal Skills.  I'm not sure it would fly there but I would hope so.

Outline of answer I would write if the question were open somewhere: let it wash over you like water off a duck's back and focus on doing what you need to do in an interview.  Ahead of time you would hopefully have figured out what the most important things you'd like them to know about you -- so in the interview, focus on making sure that you get that information about you across to the committee members.  Focus as much as possible on everybody else other than the heckler. In short, don't let a jerk derail your interview.

You have nice and professional and less nice and less professional people in every field, you unfortunately met one of the less nice people. The fact that other members publicly rebuked him shows that you are not alone in your interpretation that his behavior was not OK.
The important (and very hard) thing to do is not to stoop to their level, and you seem to have achieved that.

Usually, the hiring process is managed by not one person, but a committee. Therefore, those two other guys including that old man, given the fact that they have access to your enclosed information, are also in the hiring committee.
If someone criticizes your CV during an interview, usually not trying to find excuses is the best. Maybe you should point out some other feature of yours which makes criticized thing not so important.
Committee members are people. Maybe they had a bad day. Maybe one of their favorite candidates was eliminated 5 minutes ago. Maybe they have another thing in mind. Maybe one of them just plain did not like you. Maybe they're playing good cop bad cop routine. Those are all possible.
If you dwell on the tone of the comments rather than focusing on answering the questions, your concentration will drop and the remaining part of the interview will be worse.

Q: Is there anything I should do in the future if something similar comes up?
A: Concentrate on answering the questions in a plain and simple fashion.

Also, I would like to point out that your tone in the question when addressing them is not the politest. So, maybe we will see another question like below:

One of the candidates wrote very rude sentences about me in an online QA site. Should I
  consider him despite the good background?

+1 To me it also sounds from the question that OP got (and still is) quite emotional about the interviewers remark. Best way to handle this is stay calm and at the same time not getting rude yourself.

Generally speaking: staying professional, not stooping to their level, and being focused on upselling your existing skills and experience -- as others have noted -- is strategy #1.
But also: Be prepared to walk away. This is a last-ditch option that should be in your toolkit somewhere, someday. It doesn't sound like it was needed in this case, because 2 of the 3 committee members were giving you a fair hearing. But if you were being outright abused by everyone involved, and it was obvious you couldn't get the position (and it does happen), then walking out to save your dignity is something you have every right to do. Like many things, I expect that mentally preparing for this as a self-defense skill, which hopefully won't be used, will make you more comfortable, relaxed, and self-confident in future interviews.
As an anecdote: I have exactly two moments of professional regret, and they both involve not walking out when I was being unnecessarily berated by employers -- one during a hiring interview, with three people, when the dean who was the sole the decision maker belittled and cursed at me for no good reason. Beyond, that, I've probably wasted time on being "positive" in interviews that were clearly not going to be a good fit.

Thank you Dr Daniel. As a fresh graduate, I have very limited experiences with the hiring process and despite this I've always thought that professionalism in the hiring process was at least scared.
I will keep your valuable advice in mind.

What can you do? difficult - they pick the interview panel and that is something you cannot control.
What you can do is what you did : respond calmly, logically and clearly.
If the other two can over-ride him then you may be lucky - it does, of course, depend on what they were looking for.

Stay calm and professional - whether they are doing so intentionally or not, they are testing and observing how you function when faced with adversity. Escalating or counterattacking usually means you failed the test.
Figure out how closely you'd have to work with that person if you decide to take that job. Don't take jobs where you have to work closely with people you dislike.


text:
List of open problems: pros and cons of making it public
I am currently a 4th-year PhD student in Theoretical Computer Science, expected to graduate next year.
Since I end up finding more questions I'd be interested in solving that time or brainpower to actually solve them all, I am maintaining and keeping for myself a list of research problems I'd like to solve at some point, or see solved.
I have mentioned a few of these questions to friends or during open problem sessions in workshops, and currently this list is hidden somewhere on my academic website for ease of access.
Some of these problems, I really would like to see them solved, and I fear that I may not have the right set of tools or sufficient insight/intellect to achieve it by myself.
Ideally, I'd love to see someone get interested in them, and possibly start a collaboration leading to a solution. But I'd hate to see these questions get buried and forgotten, fading into oblivion without ever being addressed — just because I kept them to myself.
What are the pros and cons of making this list actually public? I am specifically thinking along the following axes:

Research: while I suppose advertising problems I deem interesting can only be good for the field I am in, is there any downside?

Short-term interests: I like these problems, and I do believe at least some of them are good ones. I'd be rather sad if some other people methodically solved all of them without me, although it's a bit selfish of me. Especially if I do spend some time on some of them before my graduation -- I only have that much time left to get new results and consolidate job applications for postdocs.

Long-term interests: Sooner or later I'd like to have a position in academia, and who knows even advise students. As far as I can tell, being able to suggest research ideas taylored to a student's interest is a big part of the job. Should I try and keep as many as these questions as possible in case I may need them sometime for this purpose?

@user37208 Perhaps it's just a personality difference, but I find your "worry about your own career first" statement rather distasteful. I know that's not how the real world operates, but I'd like to think that expanding the human knowledge is not (and should not be) a competition; it's a group effort, and participants should help each other as much as they can. That being said, I actually agree that the OP should keep a problem (or two) for himself, but not the "juiciest" problems, rather problems that he is (somewhat) confident he can and will work on. Or in other words, don't be greedy.

@101010111100: Universities are one of the very few places left to do theoretical research (and the only places left in some areas, such as math). There are far more people who want academic positions than places for them. If you don't worry about your own career, then you won't have a career. I'd like a friendly, collegial, collaborative environment too, but we don't have one, and we shouldn't pretend as though we do.

@anomaly: What were the othee places for theoretical research before?

@user37208 My gut reaction: worry about your own career first.  Publish the list as broadly as possible, and offer to collaborate with anyone who is interested.  Keeping problems secret is a surefire way to get scooped; on the other hand, a community of collaborators will boost your reputation and your career.

I was in a similar position at the end of my PhD. I didn't share my list but mentioned some of these problems to some people from time to time. What I found out over time is that my problems mostly were not stupid, but neither interesting enough that other people would put time into them; I just realised that I was too idiosyncratic. These problems had a meaning from my point of view but people with a different "history of thoughts" wouldn't see that they're worth the effort. (To be continued.)

(Earlier comment continued:) A few of them actually proved worthwhile later, within my own framework, but still I don't think people would've seen this at the time. I'm not saying I'm a genius and they were too stupid. Rather don't underestimate how everyone works in their own thought-bubble and getting into somebody else's original ideas is hard and if people have enough own ideas, they don't have the time. So in my case it wouldn't really have made much of a difference had i published my list. And even I myself don't think now that most of them were worth much time. Just my experience...

Point to keep in mind:

Asking questions is easy.  Asking questions other people think is interesting is less easy (see some questions on this site).  Asking questions that lead to important results is hard.

Fundamental ideas come up over and over again, so even if they don't take off at first, they'll spread eventually.

Pros:

If some of the questions are indeed interesting, you could help people find good problems.  If you're lucky, you may get asked to collaborate, but I wouldn't count on it.

Such a list, may help get your name out there.  Maybe the questions are great and people think you're brilliant.

Cons:

The most obvious and serious con for you is that someone else solves what you're working on before you do, and a lot of your work becomes unpublishable, and you don't get a job you want.

Some of your questions are trivial/well known and people think you're stupid/ignorant.

Worst case scenario (exaggerated): everybody in the field finds your questions super-interesting and all work on the same question but nobody solves it for the rest of their life and the field dies.

Suggestions
Think very carefully about which of your ideas you want to share, with whom, and with what purpose.  I'm not going to advertise to the world what new idea I'm working on, or even a good one I have on the back burner, until I make serious progress or have compelling evidence.  Because (1) I don't like to compete with people, and (2) if nothing works out (most common) then it's likely either not a good idea or not the right time for this idea.  This doesn't mean I won't tell people, or ask other people related questions, I just don't post a pdf on the internet.  I tell some people I trust, and sometimes this leads to collaborations.  Occasional "further problems" to projects I've done, I mention in papers, but this is when either I don't want to do it myself or I deem it unlikely anyone else would solve it before me.
Also, at least for me, often it's years between first asking a question and answering it, but if I had advertised it, maybe someone else would've done it in the meantime robbing me of the satisfaction of answering it myself.
If you decide you are willing to share some of your ideas on the internet, and you think they may be of wide interest, rather than just posting a list, consider making a blog of some of your thoughts.  If you get readers, this could generate interest in things you like, which might make your work more popular.  At the same time, you can pose your questions in a very informal way, so they're not presented as if they're supposed to be a grand list of the most fundamental problems in the field.
Not everyone has the same philosophy as me, but I would consider being too open about your ideas somewhat risky at your stage.
Oh, and maybe ask your advisor first.

Thank you (and especially regarding the very last point). I'll try and think on what is best, based on your answer and the comments above.

+1. I did not expect such an honest answer on this site. Well done!

"Oh, and maybe ask your advisor first." I asked my advisor first. He said "it is not interesting", so I believed him, and abandoned the idea. Some time later, another unrelated group published a similar idea.

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


text:
Does having an MSc in a UK university increase chances of being accepted for PhD programme at the same university?
I had a conversation with a professor who told me that getting into a PhD programme at some university (in the UK) is very difficult without also having an MSc from that same university. Is this true?
If it's relevant, we were specifically taking about Economics PHDs.

That is probably a decision that is pertinent to each university and branch economics, engineering etc...

I've never heard of this requirement and it seems very unlikely to me (unless the specific university you're talking about is Oxford or Cambridge. Then I would believe it). Anyway, I would contact admissions staff (or even a current PhD student) at your chosen university to clarify.

@astronat Why would you think it would be the case for Oxford or Cambridge and not others? Is it purely because these two are very competitive? Because others are also really competitive (like LSE, UCL).

NO, it is not true.

@pafnuti less the competitive aspect, more that I have the impression that they have a lot of arcane rules and biases (many not explicit). I could well be wrong of course-- this is just a bias of my own!

In general, NO, it is not true, but if the professor you talked to works at said university, it is probably true.

I wonder if you (or the professor) have slightly misunderstood the situation. In some UK universities, people intending to do a PhD are initially admitted to a research-masters programme (e.g. MPhil), and then permitted to transfer into the PhD programme given satisfactory progress after a year or so. I think this is especially common in arts/humanities subjects, where research projects tend to be proposed by students rather than supervisors — the student has to demonstrate that they have a well-developed and feasible research question before they can transfer into the PhD.
This approach is largely an administrative convenience, as it makes it much easier to shed under-performing students: they are refused permission to transfer, but may graduate with the relevant masters degree.

It depends?
I don't think there really is a straightforward answer to this - as there can be some institutional difference.
Though I would in general be a little bit surprised if it were required.
For people who have obtained a UK BSc (it may need to be an honours degree), it is possible to directly progress to a PhD, provided you get a First (maybe also a 2.1) in the BSc. (No idea about a BA - and all related types of Bachelor's degrees.)
This definitely applies to at least 3 universities in the engineering field.
Now: If I am not mistaken, I believe that the majority of people who were "doing a PhD" with a non-UK-education background had a Masters Degree before starting a PhD. (During my time at a UK university.)
However, this wasn't neccessary a Master's Degree from the institution at which these people were working towards a PhD. (Though one person was on some integrated course which was a 1 years Masters followed by a PhD.)
In this context, it may be interesting to note, that the "Student Loans Company" (i.e. the state) will loan the funds for a Bachelor's degree, but not a Masters. A PhD is typically funded (unless one goes for the self funded option).
This means, that unless you have wealthy parents or an employer paying for it, a Masters Degree in the UK makes little sense if you plan to follow up with a PhD and going Bachelors -> PhD makes more sense.
If we now look at the rest of Europe, it is pretty commonplace to obtain a Masters Degree before commencing a PhD. (Though some countries may have some different routes, such as the old German "Diplom" and the French Engineers that may lead to a PhD/Doctorate.)
And if you want a definite answer, the only method is to check the requirements on the university's website, as only they will be able to give you a definite answer.

Regarding student loans, they are now offered for masters courses, but on significantly worse terms (£10,000 maximum, to be paid back concurrently with one's undergraduate loan). And In the sciences, integrated masters degrees are common; as "first degrees", those are funded for the full four years.

@georgewatson Well, that's an improvement compared to 2011 with respect to being offered.


text:
What to do if a postdoc I just started has practically no opportunities for self-directed research?
During the interview for a postdoc position, I was given the impression that there will be various opportunities to get involved in research other than the main job description of the postdoc, and also before I started I mentioned that I would like to also work on my own related research project, and the supervisor said that would be fine.
At the time I started the position, two of the collaborators on the project said they will be decreasing their involvement in it. The supervisor has a hard deadline for completion of his research, and he is a bit nervous. It became somewhat obvious that I would be working for the next several years as a calculator for the supervisor and not really practicing my own research skills.
I am worried that my research experience and output from this would be low, and that the postdoc position will not prepare me for a staff scientist or professor position. Is this something that I should seriously discuss with my supervisor, or should I just start searching for another postdoc position?
Edit: I asked this question back in 2020. This is a comment from my 2023's perspective. I was right about the postdoc position not being a great opportunity to do research per se. It was more like a technical position, where most of the work could have been done by a software engineer. I don't regret continuing with this position because I have been doing real science in my spare time, including time that was available to me because the required work wasn't really time-consuming. I'm not so sure if I would have done it again with the full knowledge I have right now about this experience.

Why would you just search for something new without even discussing this with your supervisor?


text:
Are data that can be obtained from the text of a report considered to be in the public domain?
I have been working with some data from a technical report that is freely available online as a PDF document from the website of the institution that published the report.  I've cut and pasted the data from tables in the report for my research (and written a program to process it as the data are stored in an odd order in the PDF tables).  I'd quite like to use this data as a part of a machine learning benchmark (with proper attribution, of course).  Would the data be considered as being in the public domain and available for use for academic purposes, and made available in a more machine readable format?
I should add, I will of course be asking permission to distribute the data, I was just interested in the expectations surrounding this; is it a courtesy (as it is in the public domain) or is it a substantial favour that is being asked (or somewhere in the middle)?

Did you try to find a license under which the data/technical report is published? If there is any, it should be possible to find it somewhere on the website.

Can you copy and paste the Coca-Cola logo just because it is easy to find?

It it is question of law vs of academic etiquette and norms I would ask on Law SE. Copyright law is not straightforward. For example, plain facts are not subject to copyright but arrangements of facts might be.

@EarlGrey I don't think that is quite analogous, the purpose of scientific/technical reports is to let other researchers know what you have done so that they can build on it.   The report could just describe what was done and leave it at that, but all of the data is given in tables, in full.  Quite a lot of statistics benchmark problems are taken from data given in old papers.

@GeorgeWhite I am mostly interested in what the expectations would be, for the author of the report as well as the researchers.

@Snijderfrey There doesn't seem to be any licence or statement of copyright (it is written in German).

@EarlGrey A trademarked logo is subject to trademark and copyright law; data is not subject to either (at least in the USA).

Copyright notice is no longer required.  Ask on Law SE for legal issues. Here for plagiarism, professional etiquette etc and academic norms.

@DikranMarsupial "There doesn't seem to be any licence or statement of copyright (it is written in German)." Huge assumption from your side, then. You did not find one, it does not mean that there isn't one. Since you downloaded it from the institution page, either there was a notice there or you ask directly the institution.
Assumptions are like plutonium: they decay with time, use cautiosly and in small doses, if you don't know them you are bound to get burned.

@AnonymousPhysicist really? for example here:
https://play-lh.googleusercontent.com/XRCu-SyFrrG2mKj1zF8ohJ_pniwGJcDOsrMWgHpppWvyxGIk98SGz3KGgVFcdQ4WrQ=w240-h480-rw
"there doesn't seem to be any licence or statement of copyright"

@EarlGray "Huge assumption from your side, then." I wish people wouldn't put words into my mouth that I have not said.  I have made no assumption of anything - I am asking questions.

@EarlGray if there is some subtext in your response to AnonymousPhysicist underlying the quote from my comment, I don't know what it is.  I looks like a snark, but I will assume it is not.

@downvoter, would be interested to know the reason why.  In statistics a lot of benchmark datasets are taken from tables in papers.  The expectations on usage are not all that clear, hence the question.

@DikranMarsupial - I'm not the downvoter, but I'd guess that it's for the implied assumption that if you weren't allowed to use the data then you wouldn't be able to do so.  Whether the data can be copy/pasted or would have to be transcribed by hand has no effect on whether you're allowed to do it or not.  I think the question itself is fine, but you may want to revise the title to remove the copy/paste reference.

@Bobson thanks for the useful feedback, I've made the suggested edit.  I suspect the version of the dataset I first used several decades ago may well have been typed in manually from a printed version of an earlier report.

Your question asks about "public domain" but these are really the wrong words to use, as a) it's complicated but unlikely that these data are public domain, and b) it might not matter much for what you are asking to do.
If you just want to use the data, I don't know of any law that would make this illegal, even if the data could be considered a copyrightable database (that is, data are not copyrightable, but collections of data can be). Academic convention is of course to cite, and if the primary data in your paper are from some other source you'll end up going quite a bit beyond just a simple citation and likely have to describe specifically where and why you got the data from that source.
If you want to also distribute the data, rather than just your analysis of the data, that's where you could possibly get into trouble if they were indeed deemed a copyrightable collection (which, of course, they might not), were not associated with a license that allowed you to distribute in the manner you would like to distribute, and it would be safest to just get permission. However, you probably do not need to post the data at all if they are freely available, just point others to where they can be found.
This is a good reminder that if you do produce and distribute data you would like others to be able to use to remember that you should include a license with those data to avoid any ambiguity as to whether people can use the data; if there is no license given, it must be assumed that the authors reserve all rights allowed to them. If your preference is that others use your work, let them know by using a license! Note also that even for data that are released as public domain or with a similarly permissive license, academic standards of citation still apply; licenses give you legal rights only, not ethical ones.

Taking your question literally:  In the United States, data is not subject to copyright.  Some sources state that only creative works can be in the "public domain."  If you use that interpretation, then data is not in the public domain.
Example references:
https://sco.library.emory.edu/research-data-management/publishing/copyright-data.html
https://guides.uflib.ufl.edu/copyright/datamanagement

I think this answer could use a little bit more nuance for a couple reasons. While it's true that "facts" (i.e., data) can't be copyrighted, data "compilations" or data "curations" can be: https://blogs.libraries.indiana.edu/scholcomm/2017/12/12/copyright-and-data-curation/ Personally, the point where something becomes a data compilation is clear as mud to me. Tables of raw data should be fine, but redistributing a database might not be

The other thing is that while tables of raw data should not be restricted by copyright law, tables with "data" that is derived from some other source might actually be covered by copyright; depends on if the authors of said derived data can reasonably make an argument that their process has creative originality. But if was a clearly banal process, then it should be fine. Again, I'm not going to claim the boundary between the two is always clear

@anjama: Collections of data are only protectable to the extent that they fall within the requirements set by the Supreme Court (under US law, other countries differ). In short: It has to have some degree of originality (creativity) in the "selection or arrangement" of the data, or in the accompanying text and presentational elements (if any). But the underlying facts themselves cannot be subject to protection in the US.

@anjama What you say is true, but it's not what the question asks about.

Without a license or a clear statement that it is in the public domain you must assume that the creators hold all rights. In most jurisdictions these days copyright is automatic. It need not be asserted, though it is helpful to do so.
You should ask the creators for permission (a license) for any use beyond fair use. Using "all" of it is likely not fair use.
But no, you can't assume that the things you find online are public domain.
You may be able to "use" the data for another analysis, but probably not able, ethically, to republish it in any form without permission.

Note that I've assumed that some level of "creativity" was involved in producing the data.

Comments are not for extended discussion; this conversation has been moved to chat.


text:
Putting verbal offer of PHD position on resume
While I was studying abroad, I was offered a PHD position for having a very impressive project. I was actually only in 3rd year engineering at the time and I din't want to go into the professor's specific area of research, so I declined the offer. The only written confirmation I have of this is an e-mail exchange.
That course is important in the field that I'm going into, so I really want to mention that I did really well on it, but I'm afraid that a verbal conversation and an e-mail exchange isn't official enough. After all, if someone asks the professor, it's highly probable that he will have forgotten and he might claim I mis-understood the e-mail exchange. Should I:

Include the fact that I got an offer on the resume anyways.
E-mail the prof to get a written confirmation and only include his distinction in my resume if he replies. What type of written confirmation would this even involve?
Tone down the claim to say that I had the best project and leave out the offer.

Since it was verbal, you could also mention it only verbally, once you get to talk to them?

I would not include such an offer on a CV. Saying you were offered a position is fine to include in a cover letter or statement of purpose or other such document, but a CV should be a listing of demonstrable accomplishments. Including something like this is potentially awkward—and declining a job offer is not normally what you want to "show off" on a CV anyways.

That's the conclusion I came to as well.

I would recommend against including a verbal offer on your resume.  Even aside from whether the professor remembers, an offer of a PhD position might not be very meaningful.  Professors vary in how careful and responsible they are about making such offers, and I've known of cases in which faculty expressed interest to potential students in ways those students thought of as near-binding offers but which were not intended that way.  (If someone says "Would you like to come do a PhD with me?", they may view the question as having implicit conditions such as "provided you meet the admissions requirements and I can come up with funding for you," while the student may not realize that.  This question means the professor will try to make things work out, but it doesn't guarantee that they will try hard or succeed.)
Of course your offer may well have been far more serious, but it's hard to convey this on your resume without going into too much detail about it.

Tone down the claim to say that I had the best project and leave out the offer.

I would take this approach, assuming you have some official recognition such as an award for the best project in the class.  (If it was at a prestigious university, then having such an award might mean more than the PhD offer.)  If you don't, then there's insufficient basis for calling it the best project.
If you're applying to graduate school, why not ask the professor in question for a letter of recommendation?  That would give him an opportunity to write about how impressive the project was, how it was the best in the class, and how he wishes you wanted to specialize in his area since you would make a wonderful PhD student.  Hearing these sentiments from him would mean more than anything you could list in your resume.
Similarly, if you're applying for jobs, you could ask the professor whether you could list him as a reference.
If it wouldn't make sense to ask him for a letter or to serve as a reference, then it's probably not important enough to be worth worrying about indicating on your resume.


text:
Ratio of applicants to jobs for engineering professor or assistant professor
Where can I find statistics for jobs to applicant ratios for engineering professorships or assistant professorships?
The reason I'm asking this is I'm thinking this might be the best metric to determine whether become a professor in an engineering field is "easier" (greater probability of being hired) than a humanities related field.
If the ratio I requested isn't a useful statistic, I am also open to other metrics.

Note that if 100 people apply for each and every one of  100 jobs, and all get hired, the success rate per application is one percent.  If 100 people each apply for two jobs among 100 on offer, and just 50 of them get hired, the success rate per application was 25 per cent.  This is not a good metric for ease of getting hired unless people in all fields have the same practice of how widely to apply, which they probably do not.

@BenCrowell what would you consider to be a better set of statistics to summarize the difficulty of acquiring the position I mentioned in the question?

I would suggest comparing the number of PhDs per year to the number of new faculty hired per year.  Obviously this is measuring something different than what you're asking for — it doesn't distinguish PhDs who unsuccessfully applied to faculty positions from PhDs who had no interest in staying in academia — but it does avoid the statistical pitfalls of job-to-applicant ratios.

At my institution I would say the ration is about 1:6. But this is a really bad metric for 'hardness of getting hired'. For example in the humanities typically applicants' hair is already greying, while engineering applicants almost still have their milk teeth. That is a much stronger indication that humanities jobs are much harder to get than engineering academic jobs.

What are you measuring by the 1:6 ratio?  That your institution graduates six students who are looking for academic jobs for each person you hire?

I was talking about the approximate fraction between the number of candidates that apply for a tenure track job at our institution and the number of offers we give. Of course there are many other legitimate measures - my point was that none of them are very good at estimating 'hardness off being hired'. Of the PhD graduates in our institution who try to follow an academic career, I would guesstimate that about 1/2 eventually get a tenure-track position, but this is a very crude estimate, and again is a bad measure for difficulty of the field, whatever that means...

At my institution I would say the ration is about 1:6 — This figure sounds extremely low. (On a recent faculty search, we had about 50 applications for one TT opportunity, and I would imagine similar, if not higher, numbers of applicants per opening at other places.)

@user1258240: Either you are working in a hiring system like the German one, where the calls for faculty jobs demand very specific research profiles, thereby limiting the pool, or you're thinking of the ratio of invited candidates to hires.

The number of offers you give or the number of offers that are accepted?  (My department historically makes 2 or 3 faculty offers for every offer accepted.)

I guess I shorld have made it clear that -my institution is not in the U.S.. It's not german either, but anyway this just shows that measuring application to job ratio is a bad measure. A better one would be average number of years from starting graduate studies until entering tenure track (or getting tenure). And in There measures, getting engineering jobs is way easier.

I don't think that applicants per job is a statistic that is reported by departments. I've been on all sides of job searches (applicant, reviewer, bystander, administrative assistance), and that's always been a number that's stayed internal to the department.
However, for jobs in the US, a good rule of thumb is that the number of applicants will be on the order of about 100. A short application window or a very specific research profile will diminish the pool, but the number of applicants will still be substantial.

I think this varies significantly by field and by location.  My computer science department got 300 faculty applicants for each of the last three years (for varying numbers of positions).  Comparable departments in larger cities regularly get 500 applications per year.


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Benchmarking my research results with related work's results
I have an accepted paper in CS, in which I proposed a new method in data-science related topics (data-intensive analysis, a lot of hyperparameter tuning and design decisions).
The reviewers opinions are positive, the method is clearly described and the results are validated properly. Thus, the conclusions of the work are valid.
However, one of the reviewers wrote that the paper lacks an empirical comparison with other similar works.
From my point of view, comparing the result of my method to the results of the related work is not viable for many reasons, such as the problem I am tackling is slightly different, the type of the dataset I am using is also different.
So, I see a fundamental difference between my work the related work that makes any comparison really not valid, though both my work and the related work are in the same area.
Any suggestions to improve my paper?

If the paper was accepted, it means that the reviewers and the editor / chair considered it to have sufficient merit for publication. Comments in the reviews are suggestions to improve the paper, but being the author, it is finally up to your discretion as to what is appropriate.
In your case, assuming that you now need to send the final camera ready version for publication, you could update the paper with the reasons you think such a comparison would be invalid. This would also help future readers of your paper who may have the same question.

Arrange a comparison
The implied argument there is that if you want to make a solid argument about the superiority of method X for task A, then it's best practice to compare it empirically with related work. Your argument that it's not possible to directly compare numbers of your method for your task with a different method for a different task is technically correct, but not really sufficient.
So in the scenario of you proposing method X for task A and related work using method Y for task B, it would be methodologically proper to arrange a comparison by using method X also for problem B, or method Y also for problem A, depending on what's the main novelty in your paper.
If it's the task (because it's an important task for some reason) then you would need to provide some evidence why a new method is needed at all. You'd be expected to first apply the known methods from related work to your task/dataset in practice, reproducing their approach even if you believe it can't possibly be good enough - so that you'd have evidence that they are not good enough and your method is necessary.
Alternatively, if you believe that your method is superior, then it would be considered appropriate to try it out also on the dataset(s) that related work was using, compare and contrast. If you pick a substantially different dataset, then if you run all your experiments only on that, then these experiments can not say much about how your method compares with others.


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Masters by Distance Learning accepted for PhD?
I have done by B.Tech in Biotechnology couple of years ago. Since then I am working with a company on bioinformatics research. I also did 1 year PG Diploma in Bioinformatics from classroom program.
Most of the Indian and UK universities have this prerequisite that I need to have a masters degree for PhD. As I am currently working in a company, will correspondence or distance learning masters will be valid?
I already saw these:
Distance learning: taken seriously?
Are Master's becoming required for USA PhD programs?

Skipping the reputation aspects discussion, programs and degrees from any nationally accredited higher education institutions are all valid. In US, such institutional accreditation comes in a form of an accreditation from one of several regional commissions, such as Southern Association of Colleges and Schools Commission on Colleges (SACS-COC). I imagine that similar accreditation mechanisms exist in UK, India and most other countries. Keep in mind that there is a significant difference in the educational process and its outcomes, as well as, consequently, your future career prospects, between nationally accredited programs and degrees and the unaccredited ones. For more information, see this Wikipedia article as well as articles linked in the its "See Also" section.


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Counting a translation as a separate publication
I have read this question. My interest is not in the h-index, but in a colleague listing a paper in two different versions and expecting credit (and teaching release) for both. (They got both versions published in peer-reviewed journals, but one is a straight translation of the other --- I checked.) True, it takes time to do a translation, but the intellectual effort that goes into translating one's own paper is rather less than producing the original research. I think the colleague is behaving selfishly and in an intellectually dishonest way. Before I make a big deal out of it, however, I want to make sure I talk to the right person(s). Is this behavior as big a deal as I think it is?

Unless your colleague is concealing the fact that one paper was a translation of the other, it seems to me that it is up to your department and its standards to decide how they "count" and how much "credit", teaching release, etc, should be awarded.  I don't see any dishonesty if the colleague is just asking for release based on both papers; if the department doesn't think they merit it, the department can just say no.

@NateEldredge. The colleague is trying to conceal the fact that one is a translation of the other.

Then clearly that is dishonest.

How is your colleague trying to conceal this?  The normal thing to do is just list both on your CV without further comment.  When I see a paper written in an uncommon language in my field (which includes popular languages like Chinese or Spanish), I assume it is not a serious research paper--maybe an exposition or just minor results.

Some journals publish articles in both local language and English. Such bilingual articles can certainly not be considered self-plagiarism.

@Kimball. In our activity sheets we are supposed to list our publications and also provide a count. The reported count makes it clear that both publications are counted, even though the listing contains no hint that one is a translation of the other.

It is one thing if the translated version was an 'official' translation - certain Russian language journals were translated wholesale into English back in the day (may still be?). Those you would reference by the English version than indicate it was translated from the Russian version. Somebody translating their own work and submitting it elsewhere as a different paper is dishonest.

In that case, it doesn't sound dishonest to me---for expository articles should one list that they are expository and not original research?  What would be dishonest is demarcating something as a refereed publication when it is not.

Regardless of what one might call this behavior -- self-plagiarism, double-dipping, etc. -- your colleague's behavior is an example of gaming the system. It is a common behavior observed by dishonest and insecure academics in response to various metrics that are introduced to measure their productivity and performance. Some examples related to the one under discussion are:

Listing a paper legitimately published in two versions (one as a conference proceedings and one in a journal) as two separate listings in one's publication list and without pointing out the connection. See this recent question.
Splitting a paper into several smaller papers to artifically inflate one's number of publications while possibly decreasing the work's overall scientific usefulness and impact.
Strategically "saving up" work done in one merit review cycle to write it up in the next cycle due to a feeling that one has done "enough" work for the current cycle and feeling insecure about one's ability to continue to generate meaningful output in the future.
Choosing the journal one is submitting to based on Impact Factor, h-index or other arbitrary and mostly meaningless indices.

Not all of these practices are equally unethical or dishonest, but they share the common feature that the practitioner is letting their actions be influenced by factors that are tangential to, and in some cases opposed to, the academic's main goal of advancing scientific knowledge. They can also have the effect of distorting institutional decisions about who is performing good work, who deserves to be promoted or offered jobs, etc., and to the extent that that is the case, in my opinion they cross a clear boundary between ethical and unethical behavior.
In the case under discussion, based on your description there is no doubt in my mind that your colleague is behaving dishonestly. It is fine for him to publish his paper in two languages if he feels that that adds some value, but he must clearly indicate that the two publications are duplicate versions of the same work and not try to claim credit for both.

Would you mind elaborating on "choosing the journal one is submitting to based on..."? I'm curious as to how this violates "the academic's main goal of advancing scientific knowledge".  In the lab I'm in, we target certain conferences that are known to be on the more prestigious end of the spectrum - I thought that this was something most academics did (as in, targeted specific conferences/journals)?

@tonysdg, sorry if I wasn't clear enough. The practice you describe is different from what I was referring to, and doesn't "violate" the goal of advancing knowledge. It is perfectly okay to pursue publication in the journals and conferences that are the most prestigious and have the most relevant audience so as to maximize the impact of your work. However in places where one gets rewarded for maximizing an arbitrary numerical index, that could distort one's incentives to the point of causing some people to select a suboptimal (from a scientific impact point of view) publication venue. ...

... At best, pursuing such numerical indices is "tangential to ... the goal of advancing scientific knowledge", that is, not especially harmful or unethical but in my opinion still a minor form of gaming the system, and a practice that helps perpetuate a counterproductive rewards system.

Let's split this into two different aspects: honest representation and bean-counting.
Your colleague has control of whether the publication is represented honestly.  Any listing of the two works should clearly declare their relationship to one another, e.g.:

"A translation of this work into LANGUAGE is available as TITLE "
"This work is a translation of the original document TITLE"

Not making such a declaration is dishonest, essentially a more difficult to detect form of self-plagiarism, and should be called out as such.
Bean-counting to determine whether a translation counts as a separate publication, on the other hand, is the problem of the various organizations that want to compute metrics.  As noted in various other questions on this site, these metrics are highly variable in how different organizations compute them, quite noisy, and should be regarded are a rough estimate at best.  Thus, I would not recommend worrying about that aspect of it.

This type of conduct is NOT self-plagiarism. You cannot plagiarize yourself. This is duplicate publication, or "double-dipping." I'm getting really tired of this new self-plagiarism mantra, especially since actual plagiarism is more serious than duplicate publication/double dipping. They are not in the same category, yet attempts are being made to conflate the two as one and the same. Otherwise, good answer.

@daaxix Like it or not, our culture appears to have settled on this definition.  Your disagreement with the way people use words does not make them wrong.

I would not expect something like this on a CV, which typically just lists papers with citation info and no further description.

I assume that in the later translation paper, the article states something like "this is a translation of X", since that is standard practice enforced by editors. For the purpose of institutional evaluation (tenure, promotion, raises), the question is what rules have been established regarding summary documents like the CV. Standards for what goes on a CV and how it is presented are constantly in flux, generally driven by institutional requirements. 30 years ago (at least in my field), research output was reported in two groups, "publications" and "presentations", but since then, universities are increasingly requiring more nuanced subdivisions into book chapters, working papers, conference proceedings, peer-reviewed journal articles, translations, and so on, at least for promotion-type purposes. While my university required faculty to submit a current CV annually, it only required the minutely-subdivided CV for promotion purposes. Department chairs vary substantially in their documentation requirements for the annual raise-review, sometimes not even asking for the titles of papers published, just the number, or sometimes including a paragraph of general discussion regarding research activities.
I disagree with Jakebeal's assessment that it is dishonest to not label a translation in listings like the CV. Dishonesty means that there is an unquestionable and known rule that something must be done, yet it wasn't done without openly declaring resistance to the rule. There is no such rule. It would not be irrational to create such a rule, as universities have done regarding the division of the CV into more labeled categories, but it would also not be irrational to create a rule that requires each article to contain contextual information such as "This study repeats the procedures of papers A, B, C using a new dataset" or "This study repackages the ideas of paper Z more efficiently". When a scholar keeps saying the same thing over and over, we don't claim that he is dishonest, we claim that he is boring or something along those lines. Accusations of "dishonesty" should be held in check, until it is clear that there is an attempt at deception, rather than a disagreement about what standard one should follow.


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What are books and websites I should look at before trying to write a grant?
I am an undergraduate currently involved with a local arts nonprofit, and the folks in charge would like to write grants and proposals to the colleges in town for cooperating on an after-school program. What should I read to find:

Organizations I should be in touch with which offer grants
General guidelines/requirements for a successful proposal?

Also: How do I find somebody in my school or elsewhere whom I could ask to review my grants before I submit them?

The form of a successful proposal varies wildly from organization to organization and often also within different programs in an organization. Many grant organizations thus provide "model grants" or "writing guides" somewhere on their website that you can look at to see what they are looking for (they aren't interested in wasting their time either).  See, for example the NSF's grant-writing guide.
Government organizations also generally allow you to search a database of previous grant recipients: you can look for some who are close to your area (thematically and/or geographically) and ask them for advice or to share their examples of winning proposals.  People are often willing to help out like-minded colleagues in this way.

OK, but where would I look for a list of arts or government organizations?

http://www.grants.gov/ is the generic starting point for federal grants.  You need to be more specific about what you're looking for if you want more specific advice.

I'm looking into a program to use theater arts & music to teach STEM (web design, electronics) and business (marketing, management, etc) to high school kids with the involvement of some local colleges.


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Why do so many researchers in CS fail to clarify their symbols and notations in research papers?
I am exploring some new research fields in CS from my unrelated field in math.
Many papers I have stumped upon during research seem to completely ignore the fact that notation and symbols have meanings. Coming from math, this is a bit unsettling to me.
I hate to provide example, but here is one. In equation 1, some magical capital letters are used as functions, but never defined. No references are provided either. Here is another one. Virtually all the symbols which are supposed to mean something in math are not provided with any definition.
I've encountered a whole string (dozens) of these papers in a row.
Is this a common practice in CS? Or perhaps due to page limit? Can anyone explain what I am seeing?

In the first example, the functions are defined.  T^\pi is the Bellman operator; read further.  This is consistent with other papers on this topic area.  In my experience, I have not encountered what you are seeing.  Maybe I'm from the area, so I don't need the definition of standard notations.  I'm sure when someone without a math background venture into your area, they will query the meaning of standard notations; e.g., integral, sum, etc :)

@Prof.SantaClaus I have to some what agree, for example, https://arxiv.org/pdf/1801.05914.pdf, the symbol \Gamma is not defined. However, I find that unlike CS, in math, the notations are followed consistently not just between researchers, but across the field, or even across different levels of education from university to k12. In this case, even though \Gamma is not defined, I intuitively knew that it denoted the \Gamma function. So I guess the issue may be that CS is younger. But then there is more of a risk of serious misinterpretation. And what benefits do undefined symbols bring?

If the definitions really are well known, then omitting them saves space (in case of page limits, which are more common in CS than in math).  It also means that a reader doesn't have to wade through pages of definitions she already knows in order to find the new material, which can be very tedious and annoying, and possibly damage her opinion of the paper.

Sloppiness of course. If you were a reviewer for such an article, you could point it out and they would apologize and add the definition. I do it all the time. Reviewers get sloppy too, skimming past the early formulation if it is familiar, and only analyzing the novel steps (and many clearly never check the math at all).

The opening to section 1.1 reads "The most popular and widely used... comprised of a set of states S, a set of (possibly state-dependent) actions A (A_s), a dynamical system model comprised of the transition probabilities P^a_{ss'} specifying the probability of transition to state s' from state s under action a, and a reward model R. A policy π : S → A is a deterministic mapping from states to actions. Associated with each policy π is a value function V^π, which is a fixed point of the Bellman equation."

T is defined in that paragraph, at least implicitly. The immediate line before equation 1 says that V is a fixed point of the Bellman equation and then immediately writes V = T(V). Given that context, even if you didn't know that T was the bellman operator (a widely used notation), I would have assumed that that was clear. I've seen many math papers say "consider x, a fixed point of the such-and-such map, x = f(x). Can you explain how you feel that the paragraph proceeding equation 1 fails to define the terms of the equations? Do you feel that the description in that paragraph is insufficient?

In the case of the first paper, the meaning of these equations are well-known within the subfield of reinforcement learning. (See Barto and Sutton's book for background.)
For instance, V is usually a value function which is the expected reward from following a policy π to termination. (The Q function - the value of taking an action from a state is also often used without full definition as well.)
I can't speak about CS as a whole, but in subfields like reinforcement learning, this is somewhat common. Personally, I find myself getting more and more formal the older I get. But, CS doesn't demand the same rigor as might be found in mathematics, so people get used to not providing it - and don't demand it of their graduate students.

Even if T is well known, what is the definition of P, or R, their domain, range, etc? It seems to me that we are excusing poorly written or loose math here by simply deeming them to be "well known". This raises a further question, do all these reinforcement/machine learning researchers use the same notation? I fear not.

Barto and Sutton's book has been a seminal book in the field, and that's the terminology that has been followed for the most part. Although there are variances, they are usually close enough that one can jump to the new notation without much difficulty. (Note: It seems the new version will be Sutton and Barto.)

Funny you mentioned that book, I am going through it right now just to understand some of the notations, and I have to say that even in that textbook, the notations are awfully unclear, for example, on page 38 of http://incompleteideas.net/book/bookdraft2017nov5.pdf, the authors defined R_{t+1} as a real number, then immediately followed up by calling R_{t+1} a random variable. Anyways, the focus is not on that particular paper or even this subject, but rather my confusion on why this kind of practice is followed or allowed. If you say that this field is more creative, then so be it.

I have to echo the comment above to your original question. The more time you spend in a field the more comfortable you get with the notation. I would surely be confused by notation in your field if I began to study that field. It's hard to learn new things - and easy to forget how hard it was the first time.

P and R are sort-of-defined in the paragraph preceding equation (1): P represents transition probabilities and R represents rewards. The problem is that neither of these is defined with a superscript \pi that denotes a policy. As a result, I can get a general idea of the meaning of equation (1): The value of a policy (in a state) is the immediate reward plus the expected value, discounted by \gamma, of the value of the next state. (The second = in (1) just serves to define T.) But I can't give more precise information without learning about the model.

This paper is an interesting study on the related question of reproducibility: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17248/15864

Mathematical notation tends to be more context-dependent in computer science than in mathematics. I guess the reason is cultural: computer scientists are often also programmers, and programmers routinely deal with much larger abstract systems than mathematicians.
Even a small program can have hundreds of named functions and variables. Large software systems are orders of magnitude larger. The code also evolves over time, as new concepts, functions, and variables replace old ones. There is no way one can define everything with the level of rigor a mathematician would expect.
Instead, the code is expected to be self-documenting. Function/variable names are often already sufficiently informative that further definitions are unnecessary, especially if you already understand the context. The structure of the code and the patterns in it give further hints that can help to understand it. Difficult/confusing places may have comments that clarify them, and high-level concepts are usually documented.
If a computer scientist can't read code, their career options are severely limited. Reading code is a basic skill every CS graduate should have, just like every mathematics graduate should be able to read mathematical proofs. And because the target audience is familiar with context-dependent notation, computer scientists often use it in their research papers. They may even find it easier to understand than mathematical rigor.