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Are TED presentations academically credible?
Many people, including myself, are fascinated by TED speakers. They provide us a new perspective. For example, see the TED talk The best stats you've ever seen by Hans Rosling.
However, when I talked about this to an anthropologist, he said that the statistics in this TED talk are unverifiable. He suggested that the speaker doesn't give us his sources, so therefore the talk is no longer a scientific talk. As a result, he suggested, real scientists are clever enough to stay away from these presentations.
Do TED talks have the necessary rigor and foundation to be citable in papers and other "scholarly" publications?

@ff524 I think that a question on scientific/academic credibility of particular sources should be on topic here.

@Ooker For general myth-debunking stuff you can try http://skeptics.stackexchange.com/ (i.e. if you are interested in -truth- verifiability of particular claims).

I think that this question should be belonged to this site, not Skeptics. It's something like "should we believe in science?", not "do scientists say so?".

Just because it has to do with science doesn't mean it is on topic. I thought TED was for entertainment, not serious science, so like anything else, take it with a grain of salt.

This question appears to be off-topic because it is not about academia. If there's a specific quoted statistic you want fact-checking, try [skeptics.se]

This isn't a question about specific statistic. The clip above is just an example. I think this question satisfies the fourth bullet: Requirements and expectations of academicians

@ff524 "Requirements and expectations of academicians", is the accuracy and scientific rigor of academy expected in TED talks?, are academics expected to produce and present results in such an exciting way as TED talks?, are they useful for people in academia?, how? etc. In short, if we were to make an informal Venn diagram with TED talks and academia, how would they overlap?

@EnergyNumbers I'd say that dissemination is part of academia and TED talks are part of dissemination. AFAIK, there is a good number of TED talks (maybe more than 50%?) in which the speaker is a reputed researcher.

For this particular example I assume Rosling uses the same data as Gapminder, and that data is showing full disclosure http://www.gapminder.org/data/ "The table below contains a summary of the indicator and, where applicable, links to the data provider and documentation."

@AustinHenley That argument for closure sounds more like an answer to me.

i would say that this TEDx talk was less than academically credible.

a TED talk is not the same as a scientific paper but most are backed by scientific papers which can be mined for refs/ data etc. most speakers are academically credible and many are top in their fields. however, topics can be inherently controversial and paradigm shifting in the Kuhnian sense.

How is "academically credible" different from "credible"?

@DavidKetcheson it was an emphasis to make sure the question was on-topic I guess

I think you are asking two slightly different questions at the same time:

“Are TED speakers and their ideas credible? (as in "likely to be correct")” I'd say yes, since TED's process for inviting speakers is at least as strict as that of many scientific publications. Most TED speakers are invited to speak at TED because they've become renowned scientists through their peer-reviewed publications.
“Are TED talks scientific (as in "usable to base your own science on")?” Here the answer is definitely "no", for the reasons you mentioned: they lack the information needed to be independently verifiable.

Note that this does not mean that their content is wrong or unscientific; it just means that the talks are incomplete from a scientific point of view, and thus not by themselves verifiable. But most TED presenters will previously have published the findings they present at TED in a regular peer-review scientific publication in a scientific format.
The bottom line is: you should treat TED talks like you should treat Wikipedia: use it to quickly understand new and interesting concepts. But before you actually apply one of these concepts, verify them using scientific literature.

Good summary. Note that TED speakers may present ideas that are controversial. For example, Elaine Morgan's TED talk about her theory that humans are evolved from aquatic apes. Also note that TEDx conferences are not necessarily at the same standard as TED. For example, TED have apparently distanced themselves from Graham Hancock's TEDx talk on "The War on Consciousness". (I'm not qualified to comment on either of these topics.)

As with the above commenter, I'd say TEDx talks can range quite to the low side in terms of credibility... At least in Japan, it's some sort of franchise that's desperate for warm bodies.

Additionally, I'd say that TED talks are usually quite entertaining and well presented. Presenting your ideas, research and results is an important part of the work for any academician and these talks could serve as examples for this, to some extent. Of course a stand-up comedy is more entertaining and some humor is always good, but specially for students, better too little humor than too much...

Alternatively you could treat TED talks like a chapter from a pop science book written by a famous or famous-ish scientist. Which may or may not be different from how you treat Wikipedia :-)

@mhwombat: Describing Elaine Morgan's Aquatic Ape theory as "controversial" is either charitable or euphemistic. It has no support among serious researchers in the field and directly contradicts known facts.

A similarly controversial ted talk is Savory, on combating desertification.  His "method" has no success stories, and contradicts what we actually know about the science.  His foundation is doing immeasurable harm.

TED talks are for popularizing ideas in science, technology and arts, as emphasized in their tagline:

Ideas worth spreading.

Very often they are a nice starting point to get interested into a certain idea and they serve as a general food for thought.
However, don't treat them as revelations, since:

they are not comprehensive (in 5-20 min you can't give a comprehensive introduction to anything (some things require hours to explain, others - years of studies); moreover, if a talk is for the popular audience (as in case for TED talks), many crucial details need to be simplified or dropped),
it is not rare that the presented idea is not considered mainstream (they do value originality; sometimes minority ideas can turn out to be a gold seam, which needs audience, in other cases it may turn out to be incorrect or inconclusive).

So, if you want to use the content of TED talks for anything beyond discussions over a beer, do consult other sources (e.g. scientific papers by the authors and check if the they are recognized in their field).
Also, very often checking out a relevant Wikipedia page gives insight into the status of a given view (is it present at all? is it disputed? is it this year's discovery or does it date back to ancient times?).
Or, as you did, asking experts (sure, they can be wrong too, but at least can be more objective than in a 15 min pitch).

People believe in scientists because they are paid to say the right things. Only other scientists in the same discipline can verify a talk from a scientist because we don't have time, energy and knowledge to do that. So I can't not have time to check every talk to see whether it is true. If other scientists decide to stay away from it (as my adviser advises), I think no way we can know. So I think the question turns out: is it true that true scientists want to stay away from these presentations?

People believe in scientists because they are paid to say the right things. — [citation needed]

People believe in scientists — [citation needed]

Well, maybe they don't, then at least scientists are paid for doing that. If we talk about that, this will be a loooooong debate.

"Is it true that true scientists want to stay away from these presentations?" That just depends on what your "true scientist" wants to get out of it. If you are looking for a potential source of inspiration, then TED is fine. If you are looking for examples of different styles of presenting your results for a general audience, then TED is great. If you are looking for an authorative review of the literature in a specific field, then a TED talk is probably not so fine.

Scientists often present TED talks. Scientists often view and enjoy TED talks. Scientists often share TED talks with colleagues. Scientists do not cite TED talks in publications. Scientists are most often (other income supplements exist) paid to publish reports of their research in peer-reviewed journals and teach. If you know a scientist who does not like TED talks, that's fine, but it's one person's value judgement and does not reflect the values or paycheck of anyone else. Scientists are a diverse group with agreements and disagreements and varied values.

Ooker, you have introduced a very important aspect of science and politics with the usage of one word: "true." Science does not deal in truth; science deals in fact. "Truth" is a political game that always uses an imperfect representation of facts, typically for the nefarious purpose of controlling other indidivuals' lives. To any given problem domain, there is an infinite number of truths, but only one set of facts. Science ends where the ego begins; when the scientist stands before a crowd of people and begins to speak, he is no longer acting in the capacity of a scientist.

+1. I have misunderstood between "fact" and "truth". But what about Hans Rosling? Was he still a scientist when he was standing on the stage? TED invited him because he's a scientist.

@Ooker Note that this is purely my opinion. I don't believe that Rosling was invited because of the veracity of his science.  He was invited because one of his primary foci of study is poverty in Africa and the "TED crowd" has fetishized "poverty in Africa" as the unsolvable problem du jure to fuel their next idealogical imperialism.  The veracity of his research and his conclusions are orthogonal to the aims of that group.

@JeffE in Spain, according to the last polls, scientists are the most valued and trusted. For example (sorry, in Spanish).

@JeffE - People believe in scientists {Austen, Kat, What gives scientists – and writers – credibility? New Scientist 16:39, 28 October 2011}. :^)

People believe in scientists because they see scientists talk on Fox News.

Not exactly an answer to the question, but I'd just like to correct a factual error in the question.

The speaker doesn't give us his sources, therefore the talk is no
  longer be a scientific talk.

The time limit on TED talk probably prevents the speakers from disclosing all sources. I cannot speak for all of them, but at least for Hans Rosling (the one featured in your question), all the data source he uses are listed here.

he said that these statistics are unverifiable

This, I agree. Even sources are disclosed, we may not know if the sampling is well designed and executed, or if the measurement techniques are the most accurate. Some more exploration on our own in the data providers' site is perhaps necessary.

And the real scientists are clever enough to stay away these bullshit
  presentations.

To be honest, I feel that your anthropologist seems no better. It takes only a few clicks to verify the data source, and yet instead of doing that, he/she decided to call the talk "bullshit." I'd recommend you to be more careful about what he/she has to say on all other "scientific matters." Better to verify them yourself.

I think the speaker only needs a slide without talking in a second to show his sources. But he doesn't. The bullshit word maybe a wrong using by me. We talk in our mother language and I need to translate it to English. The origin word isn't that so bad. I'll remove that then.

^ Then, "not showing the source of data" has now become "not showing the source of data in the way you like it." In that sense, I don't think any answer can satisfy your question.

Well, you can't publish an article without the references and saying "if you want references, please contact me".

^ Correct, but you can however say "details can be found elsewhere" with a citation without putting all the stuff onto a paper. Plus, TED is not scientific publication; both the general guide and detailed guide do not require citation. All I can say is Rosling is not at fault, he had done his due diligence; gave a website where sources can be found.

"TED is not scientific publication." So you mean that we shouldn't believe it until we have really checked it again?

Doing science is not about believing, it is about making verifiable statements. He made his sources available in a way that fitted that mode of communication. My impression is that he found an OK balance between popularizing his findings (the purpose of a TED talk) and comunicating how he got to them (doing science).

So you mean that we shouldn't believe it until we have really checked it again? — Yes!! This rule also applies to newspaper articles, refereed scientific papers, and claims by your advisor. (Accepting a result as a working hypothesis requires a slightly lower standard.)

@Ooker TED is not a scientific publication, but you can think of most of then as science popularisation.

If all the data sources for a TED talk are listed, I'd recommend obtaining those, and using those references as citations in a new paper.

I can only speak to my area of expertise (chemistry). That being said, some of the few TED talks on chemistry are "far-out," to put it politely.
For example, in this talk (from 2011), the speaker proposes creating artificial (by that I mean inorganic-based, not the Craig Venter sort of thing) life (an idea that has been pursued for decades) in two years (skip to 14:00 for the Q/A). Needless to say, we still don't have artificial life (which is probably a good thing).
Even optimistic experts agree we are many decades from approaching an understanding of how life emerges from a network of chemical reactions.
In this context, I feel that TED talks offer anything from fantasy to reproducible scientific "fact" (or the closest thing to it), depending largely on the speaker (what their goals are) and what's "marketable" to the TED audience.

Agreed. Besides TED not meeting the standards of a scientific publication, it is not even a source of reliable information in the first place. First, speakers generally fail to clearly distinguish fact from opinion and expectation. Secondly, scientific fringe theories and science fiction have been given a platform. This mostly happens at TEDx conferences, but your examples and the widely discredited and evidence-less aquatic ape theory were presented to TED audiences.

TED is Technology, Entertainment, and Design.  While speakers may use science to illustrate their topic, and may be presenting some or all of a scientific presentation, this is not a venue intended to disseminate scientific information.
Like Wikipedia, TED might be a place to provide pointers to the people, papers, and research that is ongoing in a specific area, but you should rarely find that the talk itself is a good source of scientific information.  Generally such talks are snippets from experts, and what you really want is the expert or paper being discussed, not the discussion itself.

So for a concrete case to consider, the first statistics Rosling presents are about relative child mortality rate in 5 selected pairs of countries. The second are the result of a small informal test of his own students' knowledge of the first.
I don't think it takes an anthropologist to analyse whether Rosling's numbers are verifiable or not. He certainly does not provide evidence in the TED talk that they are correct, in that sense they clearly are not verifiable from the talk. If that's what your friend means then fair enough. A TED talk is not an academic publication.
I'm not aware that the field of anthropology rejects in principle the notion of child mortality being a real thing. So Rosling's comparisons could be checked against other sources. It would not be appropriate to cite Rosling in a paper if you needed a source for the relative child mortality rates of those pairs of countries. You would go to WHO and/or national medical reporting, and pay close attention to their methodologies. In that sense they can be checked, and either verified or falsified. Will your friend give you long odds that Rosling has those pairs of countries in the right order according to WHO or his preferred source? Thought not ;-)
Rosling also hasn't really demonstrated anything about the state of knowledge of Swedish students, although the insinuation is that he has. He (serious-jokingly) says that there's a role for him to teach them something. His small trial is sufficient to support his small claim. His methodology is simple and obvious enough that the test is repeatable with other groups. There's no problem of fundamental science here. I don't know (and I don't think it matters) whether he's ever published on that particular result, but it's probably never appropriate to cite because it's such a limited and specific claim of no general interest. And might be cherry-picked.
Next he shows off his visualization software. The important thing to note here is that this is not an attempt to publish academic conclusions on fertility or life expectancy. He's using UN data (about which a great deal has been written elsewhere), to motivate the use of a particular tool, to combat what he believes are out-of-date general intuitions about that data. His hurried narration makes no scientific claims beyond the fact that a large group of what would be called "developing" countries used to have high fertility and low life expectancy, and now don't. And that AIDS reduced life expectancy in Africa. Neither of those is really controversial enough to really warrant further justification in this context: like the comparisons between pairs of countries it just provides something for you to go away and look up if you want serious corroboration.
There is nothing really to verify or falsify beyond his claim that anyone holds this intuition about developing countries in the first place. That is substantial, it's presented as novel and, even worse than his informal student study, he doesn't quantify it, let alone support it. He's not properly publishing a scientific conclusion, but then I'm not persuaded that he's pretending to.
And so on. In the next comparison US vs. Vietnam, I think he says "by the end of the year" when he means "by the end of the decade". Slip of the tongue, should never be allowed to stand in a carefully produced, copy-edited, reviewed scientific publication, but there it is. So in a sense, no, public speaking is not credible at all since such errors are far more common. In another sense, does this mean there's something wrong with public speaking?
One cannot cite (or even trust) the content of a TED talk as if it were the content of a peer-reviewed journal. TED doesn't do that. Neither is there AFAIK any fact-checking other than what the speaker does or arranges. You can treat the content of TED talks the same way as you'd treat the content of any public address by that speaker. So if you were writing a paper that for some reason needed to know what Rosling specifically says in public, then using his TED talk as a source might be reasonable. Otherwise, not so much, but then why would you want to?

the talk is no longer a scientific talk, and the real scientists are clever enough to stay away from these presentations

I think that's akin to saying that TV documentaries are not scientific talks and real scientists are clever enough to stay away from them. It's true that TV documentaries are not journal articles. It's true that there can be fakery and stupidity in their vicinity. However I don't think it's true that no real, clever scientist can get involved. They must distinguish the activities of "publishing research" and "popular education", and avoid claiming that one is the other, or applying the standards of one to the other.
TED talks are as credible as the individual speaker. The fact that TED has "chosen" them should lend no authority at all but probably, unfortunately, does. As for the credibility of TED as a forum, I don't recall what wit here in the UK observed that the country has very many people who would turn down an honour in principle, but tragically are never offered one. I suspect the same may be true of TED -- there are various reasons you might not want to do it, among them that the content of the talks tends to be over-trusted by people who enjoy TED and its speakers. These reasons are not universally applicable, and in any case apply most strongly to those who won't be invited.
Aside from giving talks, experts in the field might choose to watch or not watch the presentation on the same basis they choose any popular presentation of their field. On the one hand they might be interested to know what outsiders are hearing. They might enjoy the speaker. On the other hand, what are they going to learn? Everything shown will be either commonplace in their field or else the specific and perhaps controversial views of the speaker, that an expert could better assess by reading their publications than by seeing the simplified popular version.

Let us work out the following analogy: TED as a journal, Talk as a published article.
When one meets a questionable article with unverified claims, they may of course doubt the conclusions. A usual thing to do then is to write back to the Journal and raise your concerns to them. The Editor may possibly come back to author inviting them to write an erratum explaining / correcting / substantiating the conclusions of the Paper.  This process is known as "scientific discussion" and is a blood flood of academia.
As long as the Journal maintains and empowers such procedure, I would see it as a completely trustworthy source, despite occasional mistakes and errors in published articles, which are probably inevitable in real life.

Even in this analogy, TED is not an academic journal.

I'd agree. But the question seems to be about academic perspective and academic credibility (otherwise it should not be here).

so should we cite TED as a reference?

I have read @PiotrMigdal 's answer and he advised that we shouldn't. So basically, it is like Wiki?

My impression is that "Should we cite TED" and "How to refer to TED" should be asked as separate questions.

Ok, after I get the satisfied answer on this question, I'll ask this. Thanks

@DmitrySavostyanov Can somebody write to TED to do such scientific discussion like a journal? Or you are pointing to the comments under each TED video in its web site?

I think TED video and the comments only help us the direction. You can use it for discussion, not for citation.

If you're going to cite anything as a reference, it should be a primary source. TED talks are too short to be considered a viable primary source, even if the person giving the presentation is indeed an expert and the material is non-controversial. I wouldn't cite Scientific American either, though it used to actually be pretty darned reliable AND detailed. Use these as leads to find the real research; don't settle for the popularized version.

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How should I compare my algorithm to others when their code is not available?
In computer science, we usually implement our work into algorithms and codes. So in order to compare our work to others, we also need to implement their approaches as well.
But the problem is that usually there are recently published works in each area which have used complicated mathematical methods and claimed to beat other previous methods. But some of them are difficult to implement by just reading the papers; or they have not mentioned all the necessary details in the paper for a precise implementation of their work and neither have they make their code available.
How should I compare my work to these most recent algorithms for which the code is not available?

You can compare at the theoretical level, rather than at the practical (implementation) level.

No published working implementation = ignore it. It’s bad science anyway, since their claims from the paper aren’t verifiable.

Asking the authors for the code is of course always an option, but from my personal experience this almost never works (there is a reason why they did not put it online in first place).
I don't know which area in computer science you are from but normally there is some quantitative measure to determine which method is better and those measures are somehow in the paper. Those can be things like run time or precision-recall curves on certain data sets.
If you want to compare on the same dataset, you can ask the authors for the numbers / plots themselves and then plot your own curves together with them.
If you want to compare on a different data set, you can ask the authors to run the code for you. In my experience, this works more often because many code is not published because its messy and needs a lot of parameter tuning - so it is unlikely someone else will produce good results with it.
If you have Bachelor/Master students to supervise, you can give the implementation as a project to them (although you need to give them enough time to do it).
In my personal opinion, it is not worth the effort to implement a method which is not described in enough detail anywhere. It will probably cost you an unreasonable amount of time without even reproducing the quality shown in the paper (for various reasons).

"many code is not published because its messy and needs a lot of parameter tuning - so it is unlikely someone else will produce good results with it."   And there we have the difference between a CompSci person and a Software Developer.  Although admittedly there is often some overlap.... but at the same time, not nearly enough overlap.

I know it is possible to compare the results to the numbers given in their papers, but you cannot have a fair comparison unless you are sure using same experimental setup, for example, the type of cross-validation or the pre-processings they used regarding the data.

@ivanivan I've been an SE long enough to know that most programmers think too highly of very mediocre code. At least research CS code has the benefit of never really ever being intended to run in production.

To quantify "this almost never works": There is a study by Collberg et al., in which the authors of 263 papers wered asked to provide their source code. The authors responded by providing their source code in 87 cases (33% of all cases).

So how should i convince the reviewers that i could not reproduce the results of other works except the one from 2014 which has provided the code?

It seems like if the authors can't/won't provide source code and actively make it difficult or impossible to verify/reproduce their results, this should be cause for making a complaint to the journal that published the result.

"If you want to compare on a different data set, you can ask the authors to run the code for you." At which point your paper contains results based on experiments you didn't perform using code you don't have.  What happens when someone contacts you trying to reproduce your results?

What's wrong with being honest?
We compare our algorithm to A and to B.  We would have liked to compare also with X, Y and Z, but code is not available for them.

At least in our field it is frowned upon and gets rejected with "should have compared to methods X, Y, Z." or "lack of comparison". It's incredibly frustrating, but even stating that there is no code available does not seem to sway every reviewer.

I would also add that you have reached out to the authors but were not able to obtain the code to evaluate performance. This helps against the reviewer rebuttals. If you've reached out to the authors, and the code is not publicly available, most reviewers will not generally expect you to implement it by hand.

If you publish your code, and it produces better quantifiable results than any other published piece of code, then you can claim it is the best.  For anyone to dispute that, they would need to show better quantifiable results.  In science, we need to be able to test theories and in computer science, that means testing algorithms.  Peer review applies to computer science as well.

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How do I avoid or get past the post-orals slump?
I just passed my comprehensive oral exam. I took a week off and have spent the better part of another week trying to build motivation to get back to work.
Now I have about a dozen things I could do for my project: delve into the observational or modeling literature, hunt down a tricky bug in my prototype model (several approaches!), derive the more general governing equations for my dissertation model, learn somebody else's code which I plan on basing my model on, restructure my prototype code (needed, but it'll take hours), and the list goes on.
I acknowledge that this is a broad and opinion-based question, but here goes:
What are some good ways to beat the post-orals slump?

Beer and barbeque.

Done that, went hiking several times, and I've played way too many video games! :-)

I find "code gardening" can be a useful thing to do when you're in the mood for procrastinating. It's productive (research code can always be made nicer!), but isn't as brain-intensive as thinking of new stuff.

@Moriarty: I'm in this situation, and because I work on a large established codebase with numerous external users, there's enough code gardening work that I could keep busy for years (and kind of have). This can be good in moderation, but quite dangerous in excess.

Patricia's answer works for the short term, but in the longer term you'll want to set a list of priorities. You should definitely start with a conversation with your advisor to determine what he thinks your priorities are, as you're probably going to want to work on those. That should be the start of your list.
After that, work through other tasks/commitments. Any collaborations you're participating in, any papers you're waiting to complete, any bugs you have to work through. Much of grad school can be treated just like any large project, so long as you list and prioritize your tasks you won't get too bogged down and lost in details.

The most urgent thing to do is to take a short vacation and celebrate. Go do something fun, unrelated to your research. If you live near a beach and the weather is nice, sit on the beach with a non-technical book. Go to any local tourist attraction. Eat a nice dinner with friends. Watch a movie.
A few days delay will not cost much, but could bring enormous benefits in your readiness to get on with the next steps.

Totally! I've been doing lots of R&R. The trick is stopping that and getting back to work! ;-)

Getting back into work after a break can be difficult because tasks are stacking up and taken together seem overwhelming. As you said,

I have about a dozen things I could do.

What helps in this situation is just to get started with something. Begin with whatever seems least daunting / most easy. Once you are a back in the "flow", you can start thinking about priorities, milestones etc.

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Should I go for a post-doc after a PhD from an unknown university and several rejections?
I got my PhD in computer science (in the field of AI with a focus on GNNs) in 2021 from the university of my Iranian home town, which is good, but not widely known.
Afterwards, I worked for six months as a data scientist.
Now we have moved to Munich (Germany) and I've started applying for data-scientist positions and got multiple rejections without interviews. It makes me really disappointed and I don’t know the exact cause of it. I have only four papers in my PhD (almost all first author, one journal, two conferences, and one workshop). I don’t even know whether the reason for my rejections is that I am not a good match for the job, that my résumé and cover letter are not good enough, or that I don’t know the German language (I've asked some of them in LinkedIn and received no reply).
However, I have come up with the thought that I might have better chances when applying for a post-doc (because I have had a two-year sabbatical in Munich during my PhD.
On the other hand, I am afraid that I might leave my post-doc in two years in a worse situation (older without any job experience). I should also mention that I don't like academia that much anymore.
I would appreciate your comment or advice regarding this idea and also if you have any recommendations regarding the application for a job position or any other advice that makes this misery a little bit more tolerable for me.

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I would recommend you to give it a try to get a postdoc position in Germany or elsewhere in Europe.
You are saying:

I am so afraid that I might leave a post-doc in 2 years in a worse situation (older without any job experience).

First of all, a postdoctoral position at a good school is definitely a worthy job experience.
More importantly, after that your CV will carry a "European stamp", so to say. People will often judge you based on your last job. In their eyes, your CV will then look stronger.
Last, and by no means least, while postdocing you will be able to take a course of German, which will then become another good point in your CV.

Thanks Michael for your reply.
I have a two-year experiences of visiting research at TUM. Do you think it is not strong enough and having a post-doc experience might be better? As I said, I am afraid of getting older without job experience and getting stuck in the same situation maybe two years later (I don't want to stay in academia). But the thing you mentioned about the German course is totally right.

@user137927 Not knowing all your circumstances, it is hard for me to give advice.  In academia, a postdoc line in a CV looks much stronger than visiting researcher -- because a postdoc is a bona fide job. My guess, it will look similar to people in industry. So, from my viewpoint, it will be worth it. But I am not in industry -- so please give a limited weight to my advice. Compare it with other people's opinions. Your choice may also be simplified by the fact that at present you have no other offers. So you may consider starting a postdoc, while looking around for other jobs meanwhile.

Thanks Michael, very nice advice and elaboration.

@user137927 Good luck with your career!

If your goal is to pursue an academic job, a postdoc can certainly be beneficial. It provides valuable research experience and allows you to further develop your expertise.
Even if you are considering an industry position, a postdoc in your new country (Germany in this case) can offer relevant work experience and help expand your professional network.
Therefore, a productive postdoc can be advantageous in both academic and industry settings.

Thanks Bob. I am pursuing an industry position. Thanks for your comment.

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Co-author wants to remove herself in author list after revisions
I am a graduate student (biological sciences) and had a collaborator and a co-author who wanted her name removed from the list of authors after she is not satisfied with the revisions made.
Just to give a brief background, I am the project leader and lead author of this work, this co-author is a collaborator, who didn't do much work but helped me get access to the facility (which is also not hers). After a few months of working in the facility, I got unexpected results, which is worthy to be published as short communications.
To make the story short, we submitted the paper, then a revision request from reviewers came. It was major but doable, I addressed all the concerns and responded to the reviewers' comments and made some rebuttals. I send to her for her inputs and perspectives; and she decided to remove her name after feeling unsatisfied of the revisions and wanted more information, which is already out of my work. This is her prerogative to decide, but this decision seemed unhealthy for collaborative work. I'm wondering, should I consider her as a co-author in my future work? Or what should be the best response I should make?
I suspect she doesn't trust the work. She suggest she knows better but it's frustrating she doesn’t give any sensible edits.

You should consult a trusted mentor who is familiar with your manuscript.  Maybe your supervisor?

"which is already out of my work."  I don't understand this part.  Why can't you provide the information?

My supervisor agreed to publish it. I meant with the "which is not part of my work" is I didn't include it on my data gathering, I dont have available data to do what she wants

"I dont have available data to do what she wants"  The key issue here is why you are not getting that data.  Normally you should just do it.

didn't do much of work but helped me get access to the facility — Perhaps she wants to withdraw her name because she doesn’t think she contributed enough to deserve coauthorship? Or did she make some other contribution to the paper that you didn’t mention?

Have you tried contacting her directly and asking what her thinking is, and how she would like to proceed going forward? Deciding you want your name removed from a paper is not something a normal person would do as Step 1 in responding to a criticism, review, or rebuttal - unless it was really, really bad ("I don't want to be associated with this mess" level). There is so much unknown, from a "minor misunderstanding/mistake/panic" up to "never collaborate with this person again", and it seems like only a direct conversation with the person could help to figure out what is going on.

I did ask her for her reason. She said she is not happy how the paper was written, as a lead author I allow her all the freedom to include whatever perspectives she wanted and find relevant for the present work. Instead, she responded by asking unnecessary content and revisions, she dont agree with my rebuts to the reviewer despite I and my supervisor has carefully presented evidence. Also, she insisted she knows more about the study and could possibly has different findings  and questions the integrity of my work. What's frustrating (or annoying) is she have read the earliest data and finding

She even pointed out the minor format of the paper (for example using 12 points instead of 10, which is unnecessary).

It sounds like she withdrew from the paper, but not from the collaboration. In other words she's saying she doesn't trust the results of the paper enough to have her name attached to it, but not that she doesn't trust you. Therefore it doesn't mean the collaboration is over. Besides, if she contributed to your future work at the level of a co-author, she should at least be approached for co-authorship.
In response to her withdrawing from the paper, the best response is probably talking to the other co-authors, if there are any, about how to answer the reviewers' comments. If the consensus "best way" is unacceptable to her and she wants to withdraw anyway, then c'est la vie.

"she doesn't trust the results of the paper enough" You don't know that.

@AnonymousPhysicist I don't have the details. It's what it sounds like to me, but could easily be something else.

I agree with your perspective --that it shouldn't be the reason to end the entire collaboration. However, her attitude towards the concerns, although includes the quality, is she demands more, which I explained why we have limitations on present work. Another co-author agreed to send it to reviewer after weighing the points.

@Allure then do not include it in your answer.

@AnonymousPhysicist how else would I answer the question? There're a lot questions on this site where the details aren't available and one must draw inferences from what's in the question. That's what I did.

If the question (or your knowledge of the subject) are flawed, do not answer.  Gather information instead.


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Updated title of arxiv not recognised by Google Scholar?
I submitted a paper to a journal and one of the referees suggested to slightly change the title of the paper. The paper was already posted on arxiv. I have updated the paper on arxiv after the revision, but this update is not recognised by Google Scholar. The main problem with this is that Google Scholar is not detecting the new citations to the arxiv paper since the new citations use the new title.
Any suggestions on how to solve this issue?
Update: I updated the arxiv version 2 months ago but Google Scholar does not detect it. It detects new papers that cite my manuscript, but not the updated arxiv.
Disclaimer. I am aware of the following questions, but they are related to different issues.
Submitted to arXiv with a different title. How to make Google understand this is the same paper?
Do all versions of an arXiv paper appear in Google Scholar?

Google Scholar should (relatively soon) detect both versions, at which point it will likely list them separately.  Once both versions are showing up in your profile, you can merge them together.  Select the check-boxes next to both publications, and a "Merge" button should appear amongst the buttons up at the top of the list.  During the merge process, you can tell it which version is the "best" version, and it will use the information for that version as the source for its title, authorship, etc.

I am not sure if the detection is going to happen at all since I updated the arxiv paper 2 months ago, but it doesn't appear in Google Scholar. What you suggest is what I would also expect to happen.

Per one of your linked questions, check to see if Google Scholar's "old" version is pointing to the new one or not.  If it is, then you can edit the citation information in Google Scholar.  If not, then give it another month or so (Scholar can be pretty random in its update time), and then report it as an indexing bug if it still hasn't updated.  Don't panic, though, because citation tracking is a long game, not a short one.

Indeed, the "old" version redirects to the new arxiv version. Thanks for your comments. I'll be patient.

Any update on this? My arXiv title was updated to reflect the published title, but 6 months later Google Scholar has not updated the arXiv title (even though it links to the new version).

it's not a "relatively soon", since they only reindex their sources twice yearly.

You can change the citation info by clicking the Edit button in the top-right corner:

But then then the link between GS and arxiv paper gets broken

Google Scholar usually first indexes papers appearing within 7-14 days of their original announcement in arXiv, and then again within 2-3 days for minor tweaks that might have occurred after announcement. Any subsequent replacements or other metadata changes will appear in Google Scholar during their twice-yearly full system reindex, where they re-harvest all their data sources (details are at item number 1 in their documentation). Typically these indices occur in January and July. No prior notice is given to arXiv that they are occurring, so arXiv cannot provide you with specifics regarding dates for the next harvest.

I previously uploaded the v1 paper version on arXiv. However, when it was published, the paper's title did not match the title on arXiv. This resulted in my citations on arXiv v1 not being associated with published papers. I've uploaded the v2 version on arXiv with a title that matches the published paper. From your explanation, next January Google Scholar will replace the indexed arXiv v1 with v2 and associate citations with v2 and the published version, correct?

@XuesongYe as we have been informed by the Google Scholar team, yes.

@XuesongYe Did it finally work out in January?


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What to write in email to potential PhD advisor?
I would like to apply for following PhD studies in the Nordic countries, particularly in the field of Computer Science. The problem that I found is that it says in the admission procedure that "before applying one should get a Professor or Researcher that agrees to supervise the applicant".
I have checked up the personal webpages of the Professors and I have found their topics of interests, publications and so on. I like a lot of the topics in which they make research, but I do not really know how to address an email to them asking if they would agree to supervise me. Particularly I have the following doubts:

Should I make a small research article putting my ideas about one research interest of them? The problem here is that I believe I would not have the enough time to go through a lot of papers made on their reseach groups. What can I do if do not have the enough background? Time is running fast for submitting the application and I do not believe I would have enough time to study in deep their research.
Should I send my CV and ask to a specific Professor that I have interest in following PhD studies under their supervision, and if it would be possible if he or she to send me some open question or open research task so that they could see that I will manage to do it well on his or her research group?

I will transcribe what the ad specifically says:

You must do your best to find a suitable supervisor at the department who agrees to supervise you. Please see the research pages
  of the department, and especially the descriptions of the research
  groups.
You must agree on a study plan, a research plan and a financing plan together with your (found) supervisor,  and submit an application
  to the steering committee of the department's doctoral programme.

also about the supervisor it says:

A student who wants to become a PhD student should start the
  application process by finding a supervisor at the department, who
  works in the field of interest of the student and who is willing to
  supervise the student. If the student is unsure of which supervisor to
  contact, he or she may first contact the research coordinator of the
  department who will steer the student in the right direction.
  Generally, a supervisor is a professor and/or principal investigator
  employed by the department.

For what I read it seems, at least to me, that one should really have in mind a good research proposal before applying, am I wrong? or only with an email will suffice to contact the potential supervisor?
What should I do in this situation?
Thanks

Have you seen e.g., Details an applicant should include/exclude in an introductory letter to a prospective grad school adviser?, Sending a research proposal to find potential PhD supervisor, etc?

indeed @ff524, I have followed those advices, but with no luck at all

Also, I really like the people who answer your question to talk about the length of an email to a professor. Too long emails may be rejected and not be read and too short ones may be assumed careless.

If you have a specific potential advisor at a university, start by sending a brief (and polite, of course) email. Ask whether she would be willing to take a new student and say a few words about your background (what you did in your bachelor/master, where and with whom). Thus you can show that your background is compatible with the advisor's research. If you manage to add a few words about how you liked something specific about the advisor's recent work, that will certainly be a big plus. End by thanking the supervisor for her time and say that you are ready to provide more info if necessary. The advisor can then help you get through the formalities if she sees a potential in you.

You might read these:

If the student is unsure of which supervisor to contact, he or she may first contact the research coordinator of the department who will steer the student in the right direction. Generally, a supervisor is a professor and/or principal investigator employed by the department.

Contact the research coordinator at first and kindly follow these steps.

Prepare your research proposal and CV that state your research interest.
Write an email that explains these points:

State your intention to apply to his/her University.
Explain why you apply to his/her University?
Inform them that his/her
publications caught your attention.
Explain your research plan, inform them that you attached your research proposals.
State your appreciation if they give their guidance.

Wait for response from them. If their response is positive, they will be questioning you more detail about your research as part of the pre-selection process.

I have upvoted this answer because it is precisely what I did myself, and it worked. The department head (research leader) knew of a potential advisor who was looking for a good candidate in a specific field. Deal done. Good luck!

Well done. It was based my own experience.

From my experience in Sweden, what most professors weight the most to evaluate a candidate is the research experience. Make sure you include a list of all your projects, with a brief explanation of what you did; and a copy of the reports of the finished ones, if they are not very big. Glancing at your profile, I see you have been published, that is very good, make it visible!
Grades are (usually) not very important, but be prepared to promptly produce a transcript if requested.
Of course, common sense applies, a large dump of stuff is more likely to get ignored or deleted than a well distilled selection.
Best of luck!

I would suggest you have a very good research proposal. Go through your proposal and then contact the professor(s) who also have interest in what you are interested in.
Ensure that the email is well thought out and avoid all unnecessary spelling errors.
The email should also include your academic achievement as it relates to that of the professor(s).


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how to make the structure of an opinion article?
I have seen a lot of information about the structure of an academic paper; and in summary the structure is as follows:

Title
Abstract
Introduction
State of the Art or Background
Methodology
Results
Conclusions
Future work or Recommendations
References

Nevertheless, I found (in rare ocassions) some articles that look more like opinions; and, I am not confused with the Letters to the Editor or other sections that would correspond to a magazine. So my question is how to structure an article, to being submitted to a peer-review conference, that is aimed to express an opinion like in an essay?
or said in other words, which are the parts of an opinion article?
I ask this because the Professors that initiate me in research activities had always stated that the opinion is pointless in a research article. Therefore, only facts that could be proven should be put in an article for a peer-review process.

which question are you asking ?

the question I put in the last part: "how to structure an article, to being submitted to a peer-review conference, that is aimed to express an opinion like in an essay?"

So, not "how true is that?" then...

This kind of article is known under the name position paper.
First, the structure that you mention for research papers is indeed traditional, but it's not a rigid standard. It is important to emphasize that the structure of a paper is not predefined, it should be determined by the purpose of the authors. Typically if the contribution is a new method for solving problem X, then it makes sense to explain why problem X is important (motivation), what has been done to solve it (or similar problems) so far (state of the art), then explain the new method and propose some experiment or evidence to assess its validity.
The same logic applies for a position paper: it is not simply an opinion in the sense of a taste or a personal preference (probably what your professors were thinking about btw), it must be a motivated opinion (preferably a strongly motivated one, otherwise it might get rejected). The structure should therefore reflect the reasoning behind the opinion and present the arguments that support it in a logical manner.

When writing a paper there are two things that you might want to achieve but, regrettably, in practice, they might be incompatible.
One thing you might reasonably want to achieve is to make your paper easy for your intended audience to read. A good way of doing that is to stick to a structure that your audience all know (even if they might not love it). The structure you describe certainly achieves that for an academic audience.
The other thing you might, with equal reasonableness, want to achieve is that the main messages of your paper should be rapidly understood. That wish would lead you to an entirely different structure:  a title that foreshadows the conclusions, an abstract that summarises them, then the conclusions followed by detailed argument and finally methods, detail, and literature review (probably in an appendix).
During my career I have written many papers with one or the other of these purposes. What is the key to deciding which approach to take? If you want to show an academic audience how clever you are, then you probably have to go with the standard approach you have outlined. If, on the other hand you are writing for busy people who primarily want to know what you propose and secondarily, if interested enough, why, then you need to go for the sort of structure I have outlined.
I think there is a kind of middle way. Even with the traditional, and to my mind laborious, structure of an academic paper, you can still tell a story. Nothing engages a reader better than a story. So what you have to do is to see that your intended story is there all the way through. The danger comes if you see the headings in your list as separate sections that could be written in isolation from each other. That is a particular risk if you pay too much attention to the often repeated advice to doctoral researchers that you should start writing as early as possible in your research. Write when you are clear in your own mind what story you wish to tell.
Unless your paper comprises only the facts about your topic, but includes every single one of them (which I believe to be an impossibility) you cannot write a paper without selecting what you wish to include and therefore what you have to exclude. Your opinion inevitably enters into your choice. What you must avoid is expressing your opinion as if it were a fact, or claiming that your supposed facts comprise everything that is to be known about the subject.

Write when you are clear in your own mind what story you wish to tell. But how do you clear your mind without writing?

@Henning There are lots of ways. Various forms of mind mapping work well. But if you really cannot think unless you write whole sentences then, having thought, throw away what you have written and start again with your ideas in some kind of logical sequence. It is simply unfair on your readers to expose your half-thought out scribblings on them.

absolutely. I think the advice to start writing from day one refers to "thinking-writing". A lot of rewriting, editing, and polishing go into the production of the final work.

That is one way. In my experience, with a well thought-through and detailed structure  the amount of rewriting and editing can be minimised.


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What exactly would count as copyright infringement in a replication paper?
I have been following the review process of a replication journal
In particular, it has an open review which can be seen.
On a particular submission they are having a debate about whether copying equations and their explanation in a paper counts as copyright infringement.
I would like to ask this question here, since the answer seems non-obvious.
Equations, by themselves, since they are ideas, should be free from copyright infringement. But to have equations, explanations, replica of figures, and discussion, would basically be a copy of the paper, and I imagine that would be copyright infringement. Where exactly can a line be drawn?
Note: There are questions on stack exchange which ask similar questions, but often in context of building up on previous research. Since the point of such a journal is just to replicate, it would seems that the aim is to build a freely available copy of the existing (perhaps paywalled, copyrighted) material, that can be freely accessed, and this is different intent than regular articles.
Also, answers regarding plagiarism aren't much help in this case as the point is to do "explicit plagiarism" with proper attribution.
Crossposted to law.SE

It seems that you are asking about specifics of copyright law. These will depend on the country concerned. It is mot clear to me that questions about copyright at this level are on topic for this site (maybe law is more applicable.).

It is true that this question is about copyright laws. But the reason for asking the question is to have a better idea of what is expected of a replication study, and what is permissible. Since replication studies, and more precisely having a journal for the intent of replication is a new idea, I doubt there is precedence for it.
Regardless, I am looking more along the lines for general guidelines to such work, rather than copyright as specified by a particular journal or country.
I would nevertheless appreciate help in cross posting this on law.stackexchange appropriately.

Redoing the experiment should not require copying anything from the original paper. Period. This really is not that hard to figure out.

@JonCuster I'm not sure it's that straightforward. If you exactly reproduce the method (which is the whole point) then your M&M should be basically the same. Although you shouldn't claim the method as your own, you'd still say "We followed the protocol of Custer et al. (2009) [details]".

@arboviral - precisely - reference it, and phrase it in one's own words.

Don't worry about copyright. Just don't plagiarize.

Relevant: What is the difference between plagiarism and copyright infringement?

I think some of these comments are missing the point of the question slightly. If the point of your paper is to check the reproducibility of an existing result, you follow the published protocol as exactly as possible. If you are able to follow it in its entirety, and it was written well, it is clearest to use the same text. This is not the normal situation of "we did the same as X et al. but with species Y", this is "we deliberately and intentionally followed the exact same protocol as X et al.". And I doubt any journal would let you just say that without then explaining what you did.

To take an example from a paper we're preparing right now, there are only a limited number of ways to say "we vacuum-hatched egg papers from colony-reared Liverpool-strain Aedes aegypti in dechlorinated water for two hours and then pipetted 500 larvae per tray into trays containing 1.5L of water and Xmg of liver powder". If someone wanted to reproduce our findings and insisted on rewording that just to avoid copyright concerns, it would make comparing the actual protocols unnecessarily difficult.

After asking permission to Elsevier (I'm editor in chief for ReScience), they confirmed (in this specific case) that equations can be re-used without asking permission to Elsevier:

Our Global Rights group has confirmed that these equations are not
  copyrighted;  therefore, you can merely acknowledge the 2012 Journal
  of Theoretical Biology as the source of the equations but do not
  require written permission from Elsevier.

From what I have learned about copyright law (IANAL), the answer is non-obvious to the point that even a lawyer could only guess. Leaving aside the issue of how jurisdiction would be determined for the moment, and assuming that the US copyright law (and in particular Fair Use) applies: The problem is that the way copyright law is structured, copying the explanation of the equations would constitute copyright infringement on its face. Fair Use is merely a defense that may be applicable, and it depends on the balancing of multiple factors (the four factor test) which is by necessity somewhat subjective. The only way to truly definitively determine whether a specific act of copying is exempt by fair use or not is to have a court render judgement on this specific use.
It may be that in practice, this specific case is clear-cut enough that a lawyer could with confidence predict based on precedent if this case would be covered by fair use or not, but for that you would have to ask law.SE (in fact, you should probably ask there to make sure there aren't any errors in the above as well).

Great question. Firstly, I am not a lawyer and for anything approaching a formal legal answer you'd need this to be migrated to Law.SE. With that caveat, I'll have a go.
Original content is covered automatically by copyright. Under the 1886 Berne Convention which first established the recognition of copyrights among sovereign nations, copyrights do not have to be asserted or declared, as they are automatically in force at creation: an author need not "register" or "apply for" a copyright in countries adhering to the Berne Convention.
Certain categories of work cannot be copyrighted. For example, a list of the materials required for a protocol cannot be copyrighted, at least under US copyright law (reference). However, the protocol itself can be.
Usage of copyrighted material is permitted under certain conditions, such as fair use. I'll probably expand on this later, but basically while fair use is not clearly defined it could fall within the usage described here.
If you did that, you should make it clear what part of the M&M in your paper is quoted from the source (and clearly attribute it).
For categories of work that are covered by copyright, unless covered by e.g. fair use reroduction of a substantial portion of the work is prohibited by the laws of copyright without a special license.
A free license or open license is a license agreement which contains conditions permitted to the user from the holder on a specific list of uses for his work. As originally defined (and thus with respect to software, which was the original target of these licenses) a license is free if it gives users the following freedoms:

Freedom 0: The freedom to run the program for any purpose.
Freedom 1: The freedom to study how the program works, and change it to make it do what you wish.
Freedom 2: The freedom to redistribute and make copies so you can help your neighbor.
Freedom 3: The freedom to improve the program, and release your improvements (and modified versions in general) to the public, so that the whole community benefits.

(Freedom 2 is the most relevant for our purposes.)
Licenses meeting these criteria and commonly in use by academic publishers include Creative Commons licenses such as CC-BY-4.0 (which is used by all PLOS journals).
TL;DR: the only way to guarantee you won't get sued for copyright infringement is to target studies published under open licenses, or get explicit permission from the copyright holder.


text:
Best workflow for publication-quality figures with multiple subplots?
What’s the best way to create full publication-quality (i.e. vector) figures from multiple subplots, from various sources? For example, I want to include a TIFF microscopy image and an EPS plot exported from Matlab in the same figure. A friend suggested PowerPoint, but it no longer supports EPS plots. Loading and exporting the full figures from Matlab is an option. I haven't used LaTeX – if this is suggested, what packages would be required?
My journal requires figures to be in EPS or TIFF format.

What software do you have available? Adobe Illustrator?

I don't have Illustrator, but I'll take a look at Inkscape!

Please strongly reconsider whether this really is a good approach for your situation. Unless your plot is using the same axes as your microscopy image, they probably should be separate plots and what you intend to do sounds like one of those difficult-to-read mash-up plots.

I would use Matlab, check for subimages, and https://www.mathworks.com/help/images/display-multiple-images-in-the-same-figure.html, and (https://stackoverflow.com/questions/13884832/how-to-import-an-eps-file-and-insert-the-image-to-some-position-of-a-figure

Creating figures with multiple subplots requires a lot of fine tuning that make programmatic approaches (like LaTeX, or R) tricky. It usually makes more sense to do this by hand, since the layout of subplots can change depending on personal preferences and revisions.
A few options:

Inkscape is a good open source tool for making vector graphics, as mentioned
Adobe Illustrator is a common, professional tool for vector graphics
Affinity Designer is a cheaper professional alternative to Illustrator, and works very well with many different file formats, and I've found more intuitive than Illustrator


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Choosing between PhD students or postdocs as a lecturer
I have been appointed as a lecturer in a UK university. For establishing my lab, the department head offered two fully-funded PhD students (research programme) or two postdocs. I am struggling with what to choose. I consulted with some colleagues but received contradictory advice.
Postdocs are more experienced for a starting lab but successful PhD students are better points for my promotion. On the other hand, PhD students have lots of official responsibility and paperwork while postdocs have no direct interaction with the university/department.

What about 1 PhD and 1 postdoc, would that be possible?

What do PhD students cost at your university?  It varies widely.

What exactly are you doing in the lab, resp. want your co-workers to do? Experiments, theoretical research, teaching,...?

Would the postdocs be for the same length of time as a PhD (~3.5yrs each)? Finding other funding/studentships for great PhD candidates is usually much easier than the salary and overheads for a postdoc.

@AnonymousPhysicist There won't be much variation in cost within the UK, for a fixed subject. PhD student pay is usually pretty close to the RCUK rates.

It obviously depends dramatically on your discipline and what you want to do with those positions.
That being said, in most cases I would assume that the decision should either be to hire 2 students, or 1 student and 1 postdoc. Here are some advantages of hiring students in your case:

As a new faculty member, you need to develop a profile for your team. PhD students are often largely a blank slate with not many preconceived ideas for what they will be working on in the next years - it's much easier to steer a team of 2 students into a coherent direction than 2 postdocs, who pretty much by definition already have a research agenda.
Similarly, postdocs should and will develop their research direction independently of you, which should also include letting them work on their own projects and publishing their outcomes without you. Mentoring postdocs to be fully independent is great and very fulfilling once you yourself are fully established, but in the beginning you may want to use your scarce startup funds in a way that better maximises them for your own career progression.
PhD students will stay on longer. You have a better chance to develop them and publish extensively with them before they graduate. With a postdoc, it's easily possible that they are gone on to their own faculty position before you have really started to hit it off.
In many fields where some amount of manual labor is required, a team of 3 PhD holders but no students will be highly dysfunctional, with lots of talking heads and nobody doing the grunt work.
As you say, successfully mentoring PhD students will reflect positively on you in, or will even be required for, your promotion case. I don't think that having had postdocs usually really counts for anything in this regard.
You may simply not need a postdoc at this point. In my experience, postdocs are most productive in a large lab where the PI is stretched too thin to supervise all students effectively. This will not (yet) be the case for you.

Not all of those factors are true everywhere, but you should be able to decide for yourself what of the above is accurate for you. However, what I suggest avoiding is hiring postdocs in the hope that they will be some sort of pre-trained super-student, who will do as told with no real benefit to his own career. The few times I have seen young faculty take such a stance, it always ended with very little outcomes and a postdoc who quit after a short time.

If you are setting up a lab, a postdoc may help kick-start that process since they will have relevant domain knowledge of what to do, and an interest in doing it quickly to get results to get a job (some of this may be manual work, but a slightly different twist on it). But, 1 new prof and 2 postdocs seems out of balance compared with 1 new prof, 1 postdoc, and 1 new grad student.

+1 I would also add another point that there is a certain dropout risk with PhD students. I have seen too many students who realize after starting a PhD that they are not cut out for grad school. Sometimes they were never adequately prepared to begin with. Sometimes they are okay in the beginning but can't live the grad student life. Sometimes they want to stay and finish but they fail their exams and the department forces them out. And sometimes their own circumstances change. Of course, the OP should look at his department's dropout rate before making this judgment but it is a real downside.

@DSVA As I said, I am sure you will find exceptions for pretty much all of these points - but if one or more of them are not valid, the OP probably is aware of it and can take her/his situation into account.

Unless some regulations keep you from doing this or you expect to be overrun by excellent candidates, I would advertise the positions for both levels.
I have seen many such offers for positions where you can either apply for a PhD or postdoc position.
This way, in addition to what xLeitix wrote, you can take into account the quality of the candidates – which arguably has a much higher impact than their rank.
Also, you stay flexible if you should not find any candidates at all.

I know from myself and from my friends as an engineering PhD student in the US, PhD students are vastly divided into two:

The ones who expect every step, every single instruction and idea from the advisor. They are not much of a help if you're looking for self starters who fly their own tangents. These are mostly clueless students who do not know why they do PhD. They are good at programming, modeling etc. as long as they are given whatever the job is or idea is.
The ones who push for new ideas, new methods, and does not only work on what you suggest for project progress but also conducts what s/he thinks would work better. They have tons of ideas to conduct, they enjoy what they do. And mostly, they like to learn as much as possible, so they are more flexible rather than focusing on one single thing, which is whatever the dissertation is about.

From 2 PostDocs I have worked with, in my lab, I have observed:

They are more focused in one area, and mostly wanna publish/research in that area since they like to pursue academic career afterwards. The research area is mostly related to their dissertation or kind of continuation of their dissertations "future steps", so they are not always as flexible as a PhD student.
However, they have better discipline,and better time management and organization skills. They can easily kick in a project.
Mostly, because of their experience, they are more able to or better at looking at big picture rather than getting lost in details, compared to new PhD students; which is pretty necessary to be on time with projects timelines because postdocs are generally much faster and more efficient.

Of course, my observations as just a PhD student may not necessarily be useful for you. But if I were in your shoes or when I hopefully one day get to a similar position, I guess I would devote 1 quota for each if it is possible. 1 for a postdoc who has proven to be"all-over-the-place" but also expertise in one topic, so depth-and-breadth together; and also for management and organization skills. And the other quota to a PhD student to be flexible in research to do. But while choosing PhD student, it is necessary to be able to differentiate whether the student is a self-starter and self-willed or "requires-to-be-managed-at-all-times."


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Is it ok for one of your letters of recommendation to come from someone in the department/program to which you are applying?
[See title.] It seems ok, but one might consider it unfair in some sense? I just wanted to make sure this is acceptable. (I am specifically talking about graduate school applications.)

Edit: I apologize for previously withholding some information. Here are some more details.

I am majoring in math and will have two letters from math professors at my undergrad institution.
I also have a letter from a professor in a different department ("probability/statistics") in the same institution and am applying to this department's graduate program.

It is more than okay; it makes it very likely that you will be admitted.

@DavidKetcheson Doesn't that depend a lot on what the letter says?  I agree it's not bad as a strategy, but one letter can only do so much.

@BenWebster It certainly does, but why would a professor write a letter of recommendation to be sent to his/her own program unless the letter is very strong?  I certainly wouldn't recommend a mediocre student to my own program.

@DavidKetcheson I wouldn't count on everybody having that attitude.  Some professors aren't willing to tell a student that they can't write them a strong enough letter (and sometimes students are in a borderline situation); you can't, as someone getting a letter, just assume it's strong because the person agreed to write it.

Yes, this is fine.  On the whole, a letter from someone in the department is better than a random one, in that the writer is well-known to the people on the committee.  So, certainly this isn't something you should go to trouble to avoid.
EDIT: It seems from comments that the OP is applying to their own undergraduate institution.  That's it's own can of worms (many schools heavily discourage this, for good reasons, I think), but I think there's no question that you must get at least one letter from the institution you attended as an undergraduate.  It would look really problematic if you didn't (committees would assume no one there would write you a good recommendation, and thus wonder what you did to ruin your reputation).
EDIT 2: Just to comment further, given that the OP also left out that they are changing to a different department from their undergraduate degree.  In that case, having a letter from someone in the department is a big help.  I don't think the jump from math to statistics is so big, but generally it's very good to have letters from someone who knows the program and what it takes to succeed in it well, which is always tricky when shifting between fields.

Have to agree, it's generally a good thing when the 1) the people you're going to be working with want you to be there, and 2) someone is willing to stake his reputation on you.

Thank you for your input and for your edit! I have added a few more details in my original post; apologies for not being clearer.

Yes, although there are some caveats.
The best letters come from people who know you for an extended period of time under a variety of circumstances that would reflect the entirety of the qualifications you'd need in graduate school.
Presuming that you weren't an undergraduate at that university, then how well would the letter writer know you? One scenario would be that the letter writer  had been a faculty member at your previous college and who had transferred to the new one. In this case, they could make a strong argument for why you would be a good candidate.
But if the letter writer simply knew you from a summer program or other short relationship, then their letter would not be as strong as someone who knew you for four years.
Addendum: The OP clarified that he is applying to the same institution that he graduated from as an undergraduate. In this instance, I agree with Ben Webster that it is critical that at least one of his letters should be from a faculty member at that institution.

I think that would make more sense for someone with a bit more experience for sure. If someone just finished their 4 year undergraduate program, you would not expect them to have developed more than a few months contact with anyone outside their institution unless they were a very well traveled individual. Someone in industry and academia for 20 years should have a reference from someone they worked with more than a few months. But a summer program can literally be 10% of a recent bachelor's entire 'career', which is significant.

Thank you for your input! I worked with him for one semester at my undergrad institution and am applying to the graduate program at the same institution.

If you're applying to the same institution you graduate from, you should probably ask another question about that feasibility (also noting which country you're in). Some universities are very adamant about not bringing in their own undergraduates into the graduate program. Some don't care.

@RoboKaren: is that worth a question on this site? It would either be very narrow ("does my institution allow this") or very vague (answers of the form, "some do and some don't"). Would it make more sense to ask the admissions dept, or is there a really useful generalization that an answer can make? "West of the Mississippi they allow it, east almost all don't" ;-)

The question would be something along the lines of: "What are the pros and cons of applying to a graduate program at the same university where I did my BA?"

@SteveJessop I don't know about asking it as a separate question, but it certainly seems like relevant information for this particular OP.  Not having a recommender from your undergraduate institution would be a huge red flag.

@BenWebster With regard to the "attending grad school at the same place" question, here is a post on this website. As for my situation, I have added more details to my original post; apologies for not being clearer!


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Tenured position to be started very soon...what to do with the old affiliation
Nowadays I am a second year assistant professor (without tenure) in physics at a German university (rank W1, Juniorprofessor), advising 2 PhD students.
Today, it came to me the information about a permanent position abroad (in Europe) and I am strongly considering applying for it.
My problem is the following: the selection process had just started now, and I will not know the decision until middle july. The preference in the new institution is to start the new position is September 2015 (which means that between the decision and the start is less than 1,5 months).
My questions are the following:

At which point should I say something about this to my present institution: of course I do not know if I will be selected for the position, but I also understand that it is very bad for my present institution now to say them: "Well, I will leave the institution in one month."
At which point should I explain my Phd students about this change: this is definitely my most important headache. How should I present this point to them, and more important - when? Do you think it is good that I tell them that I want to apply for this position?

This question seems related: http://academia.stackexchange.com/questions/38179/how-to-keep-plans-for-a-job-change-quiet

I would not tell anyone anything until you have accepted the position (ideally with a signed contract). Leaving a position on short notice leaves your colleagues in a bind to cover your teaching and leaves your graduate students (and possibly lab personnel) at risk. If you are given an offer, you may be able to negotiate solutions to these problems (or the offer may be made so late, that it is not an issue). It is not unheard of for graduate students to be allowed to transfer. Delaying the start date by a semester, even a year, is not uncommon. If the start date is not flexible, you may also be able to negotiate some sort of teaching buyout which will allow you to teach a reduced load at both universities for a semester/year with each university covering a portion of your salary.
The reason not to tell people is two fold. If the position falls through, you do not want to upset your colleagues. Telling your students also seems premature. They really little to no control over the situation and it is likely going to make them anxious.
In terms of control, the student can drop out immediately. By telling them early, you save them 2 months of "wasted effort". They can also work harder with the goal of graduating early. The 2 months additional warning time is not going to result in a significantly quicker graduation. Arranging alternative supervision is really out of the hands of the student and requires the current supervisor, the new supervisor, the department, and the funder all agreeing. They are not going to move quickly on the issue until the PI confirms he/she is leaving.
Not telling the student is not the same thing as not preparing the student. Hopefully, when you took the student on, you created a safety net for them (e.g., a second supervisor and alternative research paths). You should reconsider this safety net, alternative supervision, the key resources they need, and the time lines of their current and future projects. It is probably worth discussing aspects of the safety net and steering them into now (e.g., increased collaborations with a potential second supervisor and reducing the resources needed).

Thank you for the answer. In particular the advice concerning students is very important for me.

"teach a reduced load at both universities" seems infeasible, as the other institution is described as "abroad".

@BenVoigt According to the question the OP is currently in Germany and is looking at a position in "Europe". I know lots of people who have split time between the UK and Western European universities.

How common is it for graduate students to follow their advisor when they move in Europe? We had a whole lab move into our department from another university a couple years ago, and another whole lab move out about 5 years before that. Of course, moving from state to state in the US may be entirely different from moving country to country in EU.

@user137 that seems like a reasonable question. Why don't you ask it on the main site..

I've been in more or less the same situation, though with a slightly less strict time constraint. Here is what I've learnt/done:

The timing of the move is negotiable. If they really want you, they'll wait 6 months or even a year. 1 1/2 months is completely unrealistic, and they know this.
You may be able to have a part time appointment at your original institution.  This will enable you to manage your students and projects there and facilitate a smoother transition. Avoid committing to doing any teaching. (This commitment may eventually become a real hassle, especially if you have small children you can't be away from for too long).
Don't tell your students or colleagues until you know something for sure.  And do what you can to take care of the students, such as finding alternative supervisors, funding at your new location, or money for them to travel to visit you (or vice versa).
Check your university's regulations. I had to give 6 months notice before I could leave, though this was negotiable.

UK universities move fast in the hiring process. It is not uncommon to have job adverts that come out about now, with interview dates in mid July (which is when a decision is made) with the hope that they will start in September. More often than not they get people to start on short notice.

@StrongBad: That's amazing. The hiring process in Belgium and Sweden took many months.


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Is publishing a journal article covering failed attempts a good idea?
I am currently doing some research on an algorithm that may (or may not) end up being slower than other similar algorithms. The idea behind it seems solid although it will probably not be as fast as other, already known and used solutions. Finishing and testing is of course part of the science, so the research will get carried out nevertheless.
So here is my question: is writing an article about conducted, but failed work a good thing?
My thoughts are that publishing such an article would help people conducting similar research, who would otherwise waste their own time, trying to do the same thing. Saving their time is crucial for the scientific community in my personal opinion, but I am unsure how others perceive the same problem and I do not want others to have negative opinion about my work.
There are many similar questions on this site, but none seem to duplicate this exact one. This question, for instance, covers confirming or denying others research carried out and described elsewhere, while I am talking strictly about inventing and disproving the idea myself. Many other talk about the rationale behind not posting negative results, but that's also a slightly different subject (although undoubtedly related).

possible duplicate of Have researchers any incentive to publish negative or confirmatory results?

@Corvus I think the linked topic is similar, but not a duplicate. That topic covers confirming or denying others research carried out and described elsewhere, while I am talking strictly about inventing and disproving the idea myself. Thus - it only partly answers my question, unless I were to separate my own work into two articles (one describing the idea, and the other showing negative results).

That question is just one of many. Try searching the site for "negative results".

@Corvus I just did, and I cannot see any strict duplicates. On StackOverflow asking similar questions is acceptable, so I thought the same applies here. If I am wrong and this question is too similar to others, I guess I will have to get along with it.

Searching "failures" also produced some interesting hits, for example: Why don't people publish failures?

I think it's close, but not a duplicate. Other questions are on incentives or the rationale for behavior, this one is asking for a good practice (and these are not the same things).

These kinds of things happen in more numerical sciences. For instance, finite difference schemes are pretty useful and are very fast but there are different ways to compute derivatives numerically which can also be useful and these have garnered attention as well. Different techniques can be enlightening and lead to new research for sure. I clearly can't comment on your situation but I would see what people in your field think.

Try to find something positive to say about it: identify some circumstances (however obscure) in which the algorithm performs better, or some obstacles which if removed would make it perform better, or some variants that merit further research which could improve the performance. At the very least be very clear about the insights gained: why is it that an idea that on the surface looks so promising turned out not to work in practice?

In order to give your work sufficient rigour and novelty for publication, you might need to set out the theoretical basis for why you thought your new algorithm would be quicker; and an analysis of why, despite that theoretical underpinning, it was not quicker: i.e. how did reality interfere with the theory?
In theory, the test for whether or not it's a good idea to publish failed attempts, is: would it help other researchers advance? In practice, even if it did, you might struggle to find a journal that considered it of sufficient interest to be worth publishing.
Some fields do now have a journal of negative results, which could be a suitable venue. That seems, for now, to be mostly restricted to fields within the life sciences, which might not be your field.
So you might want to consider going to one of the new mega-journals, which select only on the basis of whether your work is methodologically sound and on-topic, and whether you've paid their publishing fee.
And now you can see one risk there: you've got to be careful to avoid predatory publishers.
Another, less obvious risk, is that given some megajournals have incredibly wide scope (e.g. "science"), they are not always able to get suitable peer-reviewers: so your work could appear alongside some really shoddy work, leaving readers doubting the quality of your work, even if the journal is widely held to be non-predatory.

For what it is worth, the blog post to which you link might not be considered unbiased. I find the Scholarly Kitchen blog to have a strong anti-open access bent and author Kent Anderson (now the publisher of Science) has a long history of criticizing open access in general and the PLoS family of journals in particular. This is not to say that bad articles don't get through the editorial process at PLoS One; if you publish 30,000+ articles a year it will happen. But I think there is less reason to fear the open access mega-journals than Anderson would have you believe.

@Corvus I find Scholarly Kitchen and Beall's list of predatory publishers to be invaluable perspectives to give some relief from the flood of uncritical open-access promotion.

The key question to analyze for this decision is whether you just have a "failure" or a "negative result."  In this case, I am characterizing the distinction as follows:

A "failure" is any case where you didn't get what you wanted in the study.  This might be a negative result, but it might also be due to error, mistakes, design problems, management problems, etc.
A "negative result" is a special type of failure, which clearly establishes that the system that you are dealing with could not produce the result you wanted or expected.

Negative results are often harder to establish than positive results, because there are generally more alternatives to rule out.  They are, however, legitimate contributions to knowledge and should be published.  Thus, if you have a project that is a failure, you should analyze it and ask: how hard would it be to turn this failure into a publishable negative result?  If it is not too difficult, you should definitely publish your negative result.
For some cases, such as medical studies, the answer is obvious and publication may even be required.  For others, such as certain complex software systems projects, it may be effectively impossible to actually establish a negative result.  For your own case, of investigating an algorithm, it could go either way, depending on the nature of the algorithm and your investigation thereof.

Its a very interesting idea. showing what you call failed attempts. however we need to realize that many problems, and the more complicated they are , may need many attempts or different approaches. its more steps toward a goal , than failed attempts. I think the word fail , actually implies giving up, maybe give yourself a D grade , or a C, but yes this would show the process , which is very important. so like Ford Model T was most successful, and there were many before that, in development, ford model A, model B, model C , etc, so these were predecessors, and they were in development , toward, maybe the goal of the Model T, which proved most profitable

Can you please try to clarify what you are saying a bit?  I can't understand how this answers the question as currently written...