What are the common productivity measures of a scientist, like h-index? I am aware of h-index. I was wondering what other types of scores are both widely and rarely used to measure the impact of a scientist?

The h-index is common (and the g-index, which corrects for self-citation), as is the Journal Impact Factor. Johan Bollen has a good review of the various metrics.

However, it's important to point out that all those measures are just different ways of counting citations. They don't account for things like code you've written or talks you've given and they can't address systematic bias in citation practices such as coercive citation or citation mutation. Also, any citation-counting metric will penalize younger researchers simply due to the time it takes to publish one paper and for other papers to get published citing yours. In order to keep academics from having to publish a paper just to describe some code they've written or a dataset they've accumulated, aggregators have been built to pull in these various metrics and consolidate them. Total Impact is a good example of such a system. The general field of study looking at incorporating these broader metrics is called #altmetrics, and you can find a collection of research on the topic here.


who should I contact for the Faculty interview follow up: Department head or Search committee? One month ago, I have done a campus interview for a possible academic job. Now I am thinking to send a followup e-mail. I would appreciate to let me know whom should I include in the follow up e-mail.

When they invite me for the interview, there was a search committee chair and 5 other search committee members. However, during my campus visit, I met more than 20 faculty members including the department head and school dean.

What I am thinking to do is to send an e-mail for the department head and cced to all the search committee members including the chair. Is this the correct approach?

Or should I send a follow up e-mail to the search committee chair and cced to the committee members.

Thanks

If your goal is simply to thank them for hosting you and meeting with you, I think it's really up to you to choose who to include.

However, I'm guessing that your main goal is to get a reply with some kind of update about your application status.  In that case, I would send a message with only one recipient.  The reason is simple: if there are multiple recipients, it's unclear who should respond and since they are busy people they may each hope that one of the other recipients will respond.

As for who that single recipient should be, I would write to the same person that invited you for the interview.  That message may have officially come from the department or committee, but there is a single person who sent it; that person is certain to know the status of the search and is the person most likely to reply promptly to you.

In case all the invitation correspondence was with an administrator and not a professor, then the search committee chair is a good choice.


How to supervise a bad PhD student I am a postdoc helping in the supervision of a PhD student who is finishing his 2nd year now. This is in Europe, meaning the student came in with a MSc degree and these 2 years have been of research. "Helping in the supervision" actually means here that my professor is nominally appointed as supervisor but I am doing all of the actual supervision (my professor is not familiar with the details of our project, just the "big picture").

The project is on computational physics/chemistry, and the PhD student has a background in chemistry with no prior computational knowledge. At the time of hiring we were under pressure to get the project going and complementing my physics background with someone who actually knows chemistry seemed like a good idea back then. Also the student was very motivated.

I have been spending a large amount of time teaching this student lots of physics and programming/scripting, which is needed to carry out the project. I assumed I would need to spend a lot of time at the beginning because of the background mismatch, so that was no problem. I thought things would improve with time. Unfortunately, they have not. The student is terrible at any kind of programming and has a lot of trouble learning new concepts, but what worries me the most is his attitude.

He basically is obsessed with getting results but is overlooking learning, in the form of reading books and papers and working hard on a problem for a period of time. If I tell him to "bang his head against the wall" for a couple of weeks trying to crack a problem before seeking advice from me (like we all have done during our PhDs), he gets frustrated after one or two days and starts sending me lots of desperate emails begging for me to intervene. This is a "gimme teh codez" kind of student, looking to avoid any problem which is of any real difficulty. I spend long meeting sessions explaining the theoretical and practical details of some approach, but he only seems interested when I write code that he can copy paste and use to get results (without even understanding the code, let alone the underlying physics).

Because of this I have to do lots of debugging and finding the same little (and large) mistakes that arise now and again because the student does not understand what he's doing. I have discussed many times with him that he needs to focus on understanding theory and code, instead of just getting results. But this is to no avail. I get the impression the student wants to do a technician's job rather than a scientist's job, but still get a PhD out of it.

As a result, I find myself working personally on any part of his project which has any hint of difficulty in it, spending way too many hours a week doing supervision, and getting increasingly frustrated at the lack of progress on the project. At this point, it would be fair to say that I could myself get everything he has to do (and more) done just in the time I spent meeting with him.

I have brought some of these concerns up, but the student won't accept they need to adjust how they work, instead claiming the tasks are too complicated (believe me, they're not), the professor does not help enough, the project is not well organized, etc. I don't know what to do - this student is getting easily 10 times more help than I did during my PhD (and I had a good experience).

To complicate things, I am just a postdoc so I have not a wide experience supervising different students that would tell me whether this case is common or isolated.

Am I expecting too much from my student? Is the problem I'm having a common one? How can I improve his attitude towards learning and working? How to deal with a bad research student?

Since I have been that student at the beginning of my PhD, I think I can give you some perspective. I was very motivated when I started, but I didn't know anything about research, so I lost my motivation when I had to be on my own.

I tried the same approach as your student with my PhD adviser, and he told me he's not going to do my work or homework because I have to be able to do everything myself. Obviously, everything I did as a PhD student, I can still do now, so it worked.

But, you have to establish your boundaries. You have to set some discipline, and the first thing is to reduce the interaction with your student. Set a meeting, once a week. One day before the meeting, your student should put in writing, briefly, what progress he made, and what problems he encountered -- that should be discussed in the first half of the meeting. The rest of the meeting will be you telling him what needs to be done next. You should not talk with or help your student outside these meetings, and you should ignore those abusive "help now!!!" emails he's writing you.

If your student just wants to do his job quick, as you describe, you have to realize his output won't be something you can rely on. You need to give him two types of assignments. Some imply things he already does well, so he doesn't lose completely his courage, and the others imply him learning new stuff. The latter have to be easier. You do not help him with them beyond suggesting papers or books to look things up. In case of programming, suggest SE for him to look for help, and give him some examples to get him started and nothing else. Under no conditions you should do his work.

There are things you should demand from your student. If he has to present data to you, the data should be in the format your group is already using, if there is code that he needs to write, it should be documented, and he has to present tests that it's working. If you assigned him to read a certain paper, you have to make sure he read it. If you told him to search for literature, he needs to be able to discuss what he found and how is that relevant for the project and so on.

Since you are a postdoc, you probably can't enforce things properly. If you were his adviser, you could tell him to follow your discipline, or find another adviser. As a postdoc, you could go to the boss, tell them about what's going on and that the student consumes too much of your time. Tell them you are thinking of setting a discipline and ask them to back you up, especially since you are doing their job. Anyway, whatever you do, once you set your new set of rules, don't let him cross them, or break them yourself.

Edit - in response to @CaffeineAddiction comment claiming that, as an adviser you need to introduce the student to the basics.

The job of the adviser is not to introduce you to the foundations of whatever field. Part of that job is to teach the student how to introduce themselves to the basics. In other words, you don't teach the man to fish, you teach the man to teach himself how to fish. The basics should have been covered in classes. If they were not, you do have to make a compromise, and intervene when the student seems to have a block and doesn't make progress. But, you do that simply because you don't want to lose the student.

That's what I do. If my student has no background, I give him an easy test case, I suggest them a class to take, I recommend a book, or two, and give them one of the not so complex code that works. The code is a model, and might contain a few layers of complexity. My job is to make the student aware of this, and guide them to search for the knowledge they need to improve the code, or write their own.

I took the code as an example, since that was the original question. But, when you start research in my field, you don't get a code. You get a paper with a bunch of formulas. To understand those formulas, you need a few years of reading textbooks and other research papers. It's very easy to get lost in the process, in other words, spending 6 months on trying to understand something completely irrelevant. The adviser's job is to offer limited guidance to understanding that paper, help you recognize your blocks and address them. The heavy lifting is still yours.

As far as I understand, there are only two valuable skills that an adviser is responsible to teach a PhD student. The first is to teach the student how to learn on their own a completely new subject. The second skill an adviser must teach is how to do research. Many advisers skip the first skill because of many reasons, but mostly because of the lack of time. Then they complain about students with technician mentality. But, learning that first skill, also teaches you the right attitude towards the unknown, which is essential in research.


What order should I list author affiliations on a conference poster? First and foremost, as the title suggests, in what sort of order should I put author affiliations on the poster? Alphabetical? First author's affiliation, then alphabetical, or some other way (and do excuse me if a similar question has been asked and answered)?

Typically, affiliations are listed in the same order as order of authors.
Listing them on a poster should be no different than listing them on a paper or in any other form of scientific communication.

Thus, for example, if you have the following set of authors:

  Smith, affiliated with Ivy University

  Chou, affiliated with Arrwun Tech

  Patel, affiliated with Ivy University

  Garcia, affiliated with McName Institute

Then you would typically list them as something like the following (adjusted for your desired format):

  Smith, Chou, Patel, and Garcia

  Smith and Patel are at Ivy University, Chou is at Arrwun Tech, Garcia is at McName Institute.

As for when authors have multiple affiliations: for any given author, affiliations should be listed in descending order of importance (as judged by the author).  Typically there is a clear "primary" affiliation which comes first, and the order of any others after it matters much less.  The order of the overall set across all authors is determined just the same way as when there are single affiliations, by listing all in order and combining duplicates.


I got better and improved results later of one chapter of my published PhD thesis I defended my thesis in 2015. Later during the preparation of publications from one of my chapter, I got improved and better numerical simulation results than the one in my original thesis. Although almost all the conclusions remain unaltered. I published the modified result in a journal later. Sometimes I feel depressed thinking about that and I didn't make any corrections in my thesis because it was too late, but I have incorporated all the modifications in the journal paper later.

In another chapter 2-3 small mistakes are there during the writing of thesis, but they have zero influence on my results.

Will that create any problem in future? Please advice.

Improving on results is how science works. You should publish the results and be happy you did better!

As for minor mistakes, I would consider adding a short errata section as a supplementary file in your university database (if they allow it), or in your personal website if you have one. In either case this is perfectly normal and standard, don’t feel bad!


How to tell whether email seeking paid peer-reviewers for grant scheme is legitimate? How to respond? I am not sure if this question should be asked in the academia.SE. But, I don't have a clue either for other forums.

Today, I received an e-mail(in my academic id) from Kazakhstan saying that they would pay me USD250 per review of the research projects submitted to National Center of Science and Technology Evaluation (NCSTE) in Kazakhstan.

The e-mail reads as below:

  Dear Sir/Madam,

  The National Center of Science and Technology Evaluation (NCSTE) in Kazakhstan regularly organizes peer-review of research proposals from Kazakhstan’s scientific community. The center was founded in 2011 according to Decree of the Republic of Kazakhstan.

  NCSTE invites you to participate in peer-reviewing process of technical and scientific projects. The payment for assessing a research proposal is $250 (USD). One expert may assess up to 10 research proposals per call. The calls are expected to be announced throughout the year.

  If you are interested in cooperation and would like to be a member of our peer-review expertise, please let us know by filling in the “Form for international experts” (see in the attachment).Please, send to corporate@ncste.kz

  Please note, that NCSTE expects your H-index to be 5 or above according to Scopus or Web of Science databases for a particular period 2012-2017. Links are provided below:

  https://www.scopus.com/

  https://webofknowledge.com/

  In case your H-index is lower than 5, we still include you into our database, however won’t be able to use your service until it reaches 5.

  All expenses (postage and bank transfers) will be covered by NCSTE.

  Please do not hesitate to contact me if you have any questions.

  P.S.: For more information, please visit our official web site at http://www.ncste.kz/en

I am hesistant to click any link provided or to visit any link provided here because of the latest Ransomware attack (WannaCry).

For answer to my worries, I went through a forum like discussion in Cronicle page where few persons claim that it is legit.

I have the following questions:

Should it be legit?
Why will some agency pay this much money for a review of 10-15 page report?
For the first time I am experiencing this, how should I respond? Should I respond at all?
Can it be a spam or a scam? (There is a doc attachment, which I have not clicked till now.)

Disclaimer: Please avoid yourself from clicking any link here if you think it could be a s[c/p]am even from my side.

This is most likely genuine, in particular if the proposal to be reviewed fall broadly into your area.

Just check the actual web address of the links given (rather than what they say they are) and/or search the respective institutions online. I did once a similar job for the Polish science foundation.

Actually, if you click the link http://www.ncste.kz/en provided, you will learn that they are attempting to boost their science standing and one way to do that is to get international reviewers.

Don't be too paranoid about viruses, just don't do stupid things (like typing your password into some unknown/new website), or opening mail attachments of unknown origin, etc..


What is an "L.Mgt" qualification? I'm a software engineer in the process of building an information system for a UK university, and one of the staff members' (whose details I have to house in the system) highest qualification level is listed as "L.Mgt".

I've Googled the hell out of the internet and for the life of me I can't figure out what this qualification is. Can someone tell me what this is exactly?

My own work is on the STEM / hard science side of Academia, so I don't have first-hand knowledge about this qualification, but I would read it as a Licenciate degree in Management.

A cursory search turns up a few institutions that offer such a degree:

University of
Tampere
Lund University
Universidad de Navarra
Pontifical University of Comillas
Universidade Lusófona


Research Questions / Hypotheses for an Engineering (CS) Thesis I am writing a PhD proposal on a solution to an AI problem that hasn't been solved before (although there's related research). I am having trouble determining what kind of research questions / hypotheses are appropriate for this topic. I can't propose my solution is better, faster, more efficient than some previous technique (as is common in CS theses) as there is nothing to compare it to, it's a novel problem. I am not testing a hypothesis as to how something works (such as a theory of evolution, or quantum mechanics), nor developing some set of equations to describe some phenomenon. Rather I am using some standard machine learning algorithms to solve the problem. What form then should my hypotheses take? That I solve the problem to within some degree of accuracy?

Formal hypotheses are over-rated, but still often necessary for scientific communication, especially for a pedagogical exercise like a thesis proposal.  The key question here is this: how will you know if you have succeeded in your intended work?

If the problem hasn't been solved before, then your core hypothesis is that it can be solved effectively with your proposed approach.  From that spills out a whole bunch of secondary questions:

Is the problem well-defined enough that "solved" is meaningful? This is often especially problematic in AI (e.g., "human-like behavior in a chat-bot", "good book recommendations")
Relatedly, how can you measure whether you have actually solved the problem?
What is the difference between a trivial/toy solution and an effective solution?  Again, a big problem in AI, where it's often possible to make systems that technically solve the problem but practically do not (e.g., for real applications they require unavailable curated data, or a thousand years of training time).
What sort of "partial solution" milestones are there along the way that will help you tell whether you are on the right track?
What would an optimal solution be?  Can it even be identified?
What will you learn if your chosen approach doesn't seem to be working?  Will it be possible to definitively tell that it cannot be a solution?
How will you know when you have done enough?

If you can provide good answers to all of these questions (or even just most of them), then you will have a very solid thesis proposal, built around the hypothesis of "Approach X can solve Problem Y."


Do's and Don't's of Undergraduate Research I was fortunate enough to get a position as a researcher for the Mayo Clinic's SURF Program this year. My PI's lab focus is on the the immune system's role in CNS axonal and neuronal injury, specifically through the lens of how innate and adaptive immune effectors interact w/ infected neurons.

Although I do research under a professor at my college and I volunteered for a state university lab during the previous summer, this is my first REU/SURF opportunity, and I REALLY want to make a good impression. Here are my questions:

What are the do's and don't's in terms of being a skilled and efficient researcher?

Since I am still an undergrad, I know that I will be a less useful asset to the lab than a grad student or post-doc, but what can I do as an undergrad to not burden my colleagues and PI?

Thank you all for your help! Wishing you all the very best!

To me, the quality that makes a student not a burden is the following:

  A willingness to learn for themselves and good judgement about when to stop and ask for feedback.*

If a student isn't willing to try things out and learn independently, then it creates a burden on the supervisor. I really don't appreciate when a student asks me how to do something before they do a basic Google search.

Similarly, if a student doesn't know how to judge when he/she is "stuck" and needs help, this also creates a burden on the supervisor (because the supervisor has to keep checking on the student to make sure they're progressing).

The dos and don'ts (to avoid being a "burden") that come to mind are:

Do ask your supervisor this question at the very beginning, to find out what he/she expects from you.
Do take detailed notes when you have a meeting with your supervisor or somebody teaches you how to do something, so you can refer to them later
Do keep a written record of your own attempts and progress (such as a lab notebook) to show your supervisor during meetings
Do ask a question if you don't understand an instruction or something that is said, because it will be much better for everyone involved if you clear things up sooner rather than later.
Do mention your own ideas to your supervisor, if you have some that you think will make your research better.
Don't think that just because you are an undergraduate, you can't make much of a contribution. Obviously experience helps, but it's really only a small piece of what makes someone a skilled researcher. Willingness to learn is a much bigger piece, IMO. I've had high-school summer interns who were better than any of the M.S. students in the lab, simply because they put in more effort to learn.

* Source of the quote: The Unwritten Rules of PhD Research, by Marian Petre & Gordon Rugg


Extent of "unscientific" or wrong papers in research mathematics Kevin Buzzard's slides (PDF version) at a recent conference have really unsettled me.

In it, he mentions several examples in what one would imagine as very rigorous areas (e.g., algebraic geometry) were the top journals like Annals and Inventiones have published and never retracted papers which are now known to be wrong. He also mentions papers relying on unpublished results taken on trust that those who announced them indeed have a proof.

He writes about his own work:

  [...] maybe some of my work in the p-adic Langlands philosophy relies on stuff that is wrong. Or maybe, perhaps less drastically, on stuff which is actually correct, but for which humanity does not actually have a complete proof. If our research is not reproducible, is it science? If my work in pure mathematics is neither useful nor 100 percent guaranteed to be correct, it is surely a waste of time.

He says that as a result, he switched to formalizing proofs completely, with e.g. Lean, which guarantees correctness, and thus reusability forever.

Just how widespread is the issue? Are most areas safe, or contaminated? For example, is there some way to track the not-retracted-but-wrong papers?

I would say this is a common, but not fatal, issue.  I think most mathematicians are aware of several papers in their field with serious errors/gaps without retractions/errata, and over time at least the wrong papers which are important get discovered.  (e.g., see this MO post for temporary counterexamples---there aren't too many that went unnoticed for too long).  There are also some grey areas where most people aren't sure if they can trust certain papers or not, and in certain areas/topics it's more of an issue than others.

The culture in mathematics is that retractions are typically for academic dishonesty, and incorrect papers either get corrected (or at least have their flaws exposed) in other papers or with errata.

What to do:

for an individual paper, check its review on MathSciNet, and check papers that reference that paper: if many people use it freely, it's probably okay, but if someone later found an issue they will often mention it in another paper.  if the paper has a corrigendum, it will be linked in MathSciNet.
if you start reading the paper and for this or other reasons become suspicious, talk to experts---usually if a paper is important and there is a serious issue, experts become aware of the situation relatively quickly
check if the author has errata/comments on their webpage
some authors are more reliable than others, and they get a reputation for it; this is something you typically learn over time from your own research and talking to experts.
don't panic: if you happen to use a result that was wrong and don't realize it (or publish a paper yourself with a major error), that's okay.  it happens from time to time and you can't check everything.  you might discover the error later or someone might point it out.  in any case, you are often able to then write another paper correcting the situation.
don't contribute to the problem: put errata for your own papers on your website and if there is a major error not corrected in a later paper, publish a corrigendum
(optional) keep track of known issues in a personal notebook along with their resolution.  i do this because there are quite a number of papers in my area with errors/gaps and i have a bad memory.  i contemplated making this public and letting other people contribute to this list, but i haven't so far mainly because i'm not sure i want to put in the effort to update it and make sure it is fair to all parties involved.  however i have shared this list with some people individually.


How to give a good lab tour? I am often called upon to give a "lab tour" to visitors, including but not limited to:

prospective graduate students
candidates for summer research positions (including undergraduate and high school students)
researchers or executives from our "industrial partners"
professors and graduate students from other universities, who have come to speak in my department seminar series
journalists or other media representatives

The goal of these lab tours is to leave the visitor(s) with the impression that we are doing interesting, important, and exciting research.

The research that goes on in my lab mainly looks like... students sitting at laptop computers. We are a telecommunications lab. A lot of the experimental equipment we use is not actually housed in the lab, and the pieces that are there in the lab are not that unique or interesting to most visitors. (Think a few Openflow switches and lots of wireless devices, none of which is particularly visually exciting.)

Given this, I am wondering how to use these "lab tours" to my best advantage. What can I do in a lab tour that I couldn't do with, say, a visitor sitting down in my office and talking to me over my desk?

Right now we mainly walk around the room and talk about the posters hanging on the wall, giving any students who are around a chance to give their elevator pitch. This doesn't seem very effective, and visitors often seem kind of bored.

Depending on your data and work, it maybe beneficial to make some sort of visual representation and/or simulations of your work. People are draw to visual representations that move and do something. Stationary images, while informative, are not always interesting to the layperson (or well even those interested in the field). You could create a presentation that shows the hardware that collects your data, the raw data and then create a road map back to your students at your lab. Show screen grabs of any software that your students might utilize from day to day. You don't need to get too elaborate and there are many resources (power point, desktop applications, web applications, etc) that you could utilize to create your presentation with whatever level of effort you wish to put into it.

I would also suggest looking for someone to consult with, not affiliated with your lab, to view your presentation.This way you can get a fresh outlook on how your presentation flows. If your school has a scientific and technical (STC) writing program, I would also suggest you talk with someone in the program about your presentation. They might be willing to help out with making things more interesting and clearer for prospective visitors. You could possibly even see if a student in the program would be willing to create a presentation for you as a senior project.


If I were to ask a professor on sabbatical to consult with him on a paper I'm writing, would I be imposing on him? I'm a fourth year undergraduate philosophy student.

Last academic-year, I took a seminar with a professor that I had known reasonably well before I took the course. During that seminar we had several lengthy after-class conversations about a topic related to the seminar. The professor seemed to enjoy the conversations, and I think we developed a good relationship (as far as undergraduate student-professor relationships go).

I plan to write an essay and submit it to an undergraduate journal in December. I know that the topic of the essay is interesting to the professor and covers some unconsidered possibilities that the professor expressed interest in during our conversations. That is to say, I think he'd enjoy thinking about what I plan to write about.

This professor is the only one in our department knowledgeable about the subject, so I can't ask anyone else for their thoughts on the essay. Unfortunately, he's on sabbatical this year.

Would it be rude to email the professor in order to ask him whether I might discuss my argument with him a few times during this term?

No, I don't think it's rude at all.

A sabbatical is not meant as a complete vacation from work. Rather, it's a time for the professor to focus on scholarly work without the distraction of teaching or (usually) administrative duties.

I'd say that asking the professor to comment on your essay is definitely a scholarly activity, and so it's a reasonable request.

Of course, it's up to the professor whether he actually wants to do it or not, or if he has time to do it given his other activities. Don't be offended if he declines. Also keep in mind that many professors travel extensively during sabbaticals, or spend the entire time at another institution, so even if he is interested, he may not be able to meet with you in person - you may have to discuss it over email, Skype, etc.


Is citing a blog post allowed in a research project? I'm currently writing an essay on the possible benefits of video games in education for my Extended Project Qualification, and for part of it I want to cite a blog post from Gamasutra written by a developer who makes educational games. My supervisor has previously said to me that I should try to stick to citing research papers or books, as these are generally reputable, and I agree with this. However I cannot find anything in a journal that fits the point I want to make, as I wanted to write about a developer perspective on these kinds of games. Would citing such a post have an impact on the reputability of what I am writing, and therefore impact my grade?

This is fine. Citing someone's opinion is different from reusing someone's results as long as the former is clearly separated from the latter. Find a way to distinguish both kinds of citations in your essay. The former is the data on which you operate, after all.

If your advisor insists of such a separation, consider using footnotes, endnotes, or an extra list (in addition to the bibliography).


Does cum laude mean the end of an academic career in Germany I have recieved the grades for my PhD, and the defense is yet to be done.
I have a magna cum laude for the course work, and a cum laude for my dissertation. Do I have an academic career in Germany if I end up with a cum laude for the PhD?
Is there any way I can salvage a magna cum laude? The defense remains.
Neither of my supervisors read any of my drafts. They said that I should submit, and then gave me cum laude, which is the second-to-lowest in Germany. (There is rite, cum laude, magna cum laude, summa cum laude.)

Well, yes, but also no.
Permanent academic positions that are not professorships are relatively rare in Germany. Since most researchers want to eventually have a permanent position, it is in the interest of all long-term researchers to eventually become "berufungsfähig" (suitable for becoming a tenured associate or full professor).
The vast majority of the universities are public in Germany, and hence the laws of the respective state regulate hiring in the universities. All(?) "Landeshochschulgesetze" (law on higher education) list mandatory requirements for candidates for professor positions.
For instance, the respective law of the state of North-Rhine Westfalia (that has the largest population) states as a requirement:

besondere Befähigung zu wissenschaftlicher Arbeit, die in der Regel durch die Qualität einer Promotion nachgewiesen wird;

In English, this means that the candidate must show a substantial/remarkable/special ability to research work, which is normally indicated by the quality of the PhD. Given that PhDs are thesis-only in Germany (while the defense may also include more general questions about the field of work), this means that the PhD thesis should be particularly good and have a corresponding grade. The state of Lower Saxony has in their law that the PhD should be above average, and given that there are four passing grades, "cum laude" is probably below average.
Now what does should mean concretely? It means that if a hiring committee wants to hire somebody with a bad PhD thesis, they risk the overall hiring process being delayed or even canceled. There may be objections, candidates not snatching the precious professorship may sue, or the respective ministry of education may intervene or simply refuse to send the offer letter to the successful candidate. There have surely been cases of pea counting as far as the formalities of candidates to be hired are concerned in the past, and this adds to the risk. Hiring committees and universities will probably take the risk if there is a very good and demonstratable reason for why the candidate is excellent despite a bad PhD thesis, depending on their legal interpretation of the should and how much they are willing to risk it. In any case, certainly, those candidates with a good PhD thesis have a substantial head-start, and it's quite hard to catch up for candidates with a grade lower than "Magna Cum Laude".
Having said this, there are also other permanent academic positions, such as in Fraunhofer or Max Planck institutes that may or may not have similar requirement. So a Cum Laude may not be a big deal if they want you for a different reason.


Can one's primary motivation be learning, instead of research, if he is applying for a masters program (instead of a PhD program)? I am applying for masters in computer science programs in North America. In my statement of purpose, I am planning to talk about broadening my knowledge about the field and applying this knowledge to other specific academic fields, as well as learning how to do research in computer science.

But I am not sure if this is a good idea for writing a statement of purpose. Had this been a PhD application, I am sure that this would be a bad idea, since PhD is all about research and in the statement of purpose for a PhD application, you should talk about your potential for valuable research by showing your previous research experiences, etc.

However, I am applying for masters and I don't have any proper previous research experience. Hence, I cannot talk about my potential to do research by showing my previous research experiences (since I don't have any). Hence, I am planning to talk about my ambition to broaden my knowledge about the field and apply this knowledge to other specific fields in academia.

Would this be a good idea to put in a statement of purpose that will stand out? Or should I better talk more about doing research?

Whatever excites you about the coursework you'll be taking, write about that.  There are many masters programs that don't involve doing original research.


Is it bad to submit applications for two different degree programs in the same department of a same university? I am referring to US graduate schools here. I am now having schools that I like very much, but I am not sure whether I can withstand the competition towards PhD admission so I am thinking about also submitting an application for the less competitive master degree program (if admitted, I could apply to PhD in the same department after graduation as an alternative route to research). Is it bad to do so?
The reason I am worrying is that I have seen people say that submitting 2 applications like this will convey a sign to the committee that you don't know what you want to do in the future. See the answer of this post

Based on the tag, I will give a US-specific answer.
Often, but not always, the difference between the masters and the first part of a PhD is that the PhD program comes with funding.
If your intent is to get the PhD eventually anyway, I would not recommend considering an unfunded masters.  This is essentially the same as starting a PhD without funding.  Reasons not to do that are discussed in Is it worth self-funding a PhD to attend a top 10 university?.


Where can I find scientific poster examples? I have in a few days a scientific conference and I will present my work in the form of a poster. Now I am in the process of looking for models of scientific posters, Please who can help me find some example.

See Colin Purrington's advice on designing conference posters.  You can find it here: http://colinpurrington.com/tips/poster-design

For more examples than you'll ever want, see the comment above by Danny Ruijters.

(I know we frown on link-only answers here, but Purrington's pages have been very stable for a very long time, and the advice is too lengthy even to try to summarize here.)


How is the Journal for an Annual Review Chosen The review in question that got me thinking about this is the The Review of Particle Physics by the Particle Data Group. It's a biannual review of all particle physics results and is meant to be the central reference for experimental particle physics results. It is highly regarded as the "bible" of particle physicists.

I'm mentioning this, because I think this working group is an institution in and of itself that could hardly depend on the prestige of a journal to make its claims credible. Obviosly it still has to go through a thorough peer review process, but still I think it kind of does have a standing of its own.

Since this review is quoted by virtually every paper that depends on experimental particle physics data, publishing it in a specific journal seems to me as to give this specific journal a citation/creditiblity boost (as opposed to it being the other way round as usual). Is this impression correct?

I recently noticed that they swiched from publishing in Chinese Physics C in 2014 and 2016 to Physical Review D in 2018 (which is a very prestigous journal in particle physics, I don't know the reputation of Chinese Physics). Looking through the history of the review,

I noticed that it has historically mostly been published in Physical Review or Review of Modern Physics with a couple of other journals intersparsed. How is the journal for publishing a review like this chosen? It seems to me that with a longstanding review like this, they gave some credibility to a journal like Chinese Physics which I had never heard of before.

Short version: it's a money issue, at least in the case of Review of Particle Physics.

Disclaimer: I'm not part of the particle physics community, so I might get some details wrong in the following, but I think the broad strokes will nevertheless be correct.

First of all, I think the scale of what the Particle Data Group is doing shouldn't be underestimated. They are a group of more than 200 contributors, who publish a humongous, ever growing biennial authoritative and extremely well-regarded review article. With over 2,000 citations per year, I think it's fair of you to say that the article would boost most journals, rather than the other way around. Obviously just the data collection, editing, and fact checking requires a fair amount of funding.

Now, the crux of the matter is that they (PDG) also distribute the article in the form of a book, and a shorter (200-300 pages) booklet for free. We're not talking small numbers either - more than 30,000 copies of the booklet, and over 10,000 copies of the book (see e.g. this APS announcement).

As I understand it, there is a process where different publishers bid on the right to publish the review by offering to shoulder (at least) part of the cost of printing the books. (CERN covers at least some of the cost for the booklet.) This is the main reason why the article has moved around between different high-energy journals. Then in 2014, apparently only Chinese Physics put in a bid, and consequently went on to publish the article.


What to name a section at the end of thesis containing original material for future development? I have written my master thesis. The last chapter is "Summary and Conclusions". After this chapter which ends the thesis, I want to add a specific note of my own. It is a new idea which needs lengthy explanation and it does not directly relate to the contents of the thesis. It is a new algorithm which is not used in the thesis but I want to introduce this algorithm for future development of the field.

I want to know under which section I have to write it. Should I write it as an appendix? Thanks in advance.

If it's related to the ideas in the theses, then it sounds like a "future directions" subjection in "Summary and Conclusions."

If it's really not related at all, then it should go in a different paper.


Is it unethical of me and can I get in trouble if a professor passes me based on an oral exam without attending class? I have been experiencing anxiety based on some recent events. During my last semester of college I enrolled in a language course in a language in which I was already fluent. I did this to enable quicker graduation.

After the first two weeks of the class, it became apparent I wasn't going to benefit at all from this course. Additionally, as I was soon graduating, I had other work to perform. I asked the professor if I could stop attending classes and simply turn in the homework by the end of the semester. I did this while speaking the language that she taught. She said "yes".

I didn't attend class for a month and a half, and didn't hear from the professor again. Towards the end of the semester, I emailed the professor to inquire what she wanted me to do to pass the course. She scolded me because she wanted me to attend at least some of the classes (I had misunderstood her in our first conversation). She then told me that despite that, it was OK, she would give me a passing grade (via oral exam), as "you are fluent in the language and shouldn't come to class as it will seem unfair to the other kids."

This appeared to me as if she would pass me based on merit alone. I was VERY shook up, and called her again the same week telling her that I feel like withdrawing and holding off graduation and just taking a different course next semester before starting grad school. She reassured me I'm all set and I need not worry.

Graduation happens, however I was still uneasy as I was preparing to start grad school. I felt like I cheated the system. I contacted her again, and again she told me not to worry. After the first week of grad shool, I called her again and demanded I take the midterm and final for the course in an attempt to ease my mind and worry. Scored 99 and 96 on them without studying.

I still feel really guilty for some reason, and I'm still trying to cope with this. Its honestly affecting my performance in school. MY worse nightmare is that my undergrad will find out and take away my degree and that this will affect my grad school as I needed a bachelors to enter. The professor made it seem as if she was taking a risk by letting me do what I did. She made it seem I was doing something illegal. She told me not to tell my classmates..

As such, my question is: If what happened was found out, would my grad school have grounds to kick me out? If my undergrad found out, can they pull me degree?

Edit: Thanks for the answers, I guess why I'm soo stressed about this is because, to my understanding, she made it obvious that I and the prof. were doing something against school policies, I knew about it and didn't think much about it.

I feel like you're overthinking this. What you did seems an improvement to me over taking, say, bowling to fill a last credit, which isn't uncommon in undergrad. The professor gave you your grade and you're off to grad school. There's no reason to revisit it, with yourself or anyone else.

Also, it isn't your responsibility, as a student, to audit how a professor grades a class.  They may have even consulted with others before letting you do this; you don't know.  Don't make assumptions - you did what you did, and the professor decided it was enough to pass the class.

Put this behind you and focus on grad school.


Are faculty salaries negotiable? Are faculty salaries negotiable in general? Wherever they are negotiable, how could applicants gain insights about the statistics of offers or the extent of safe negotiation?

This entire answer is US-centric, since I have no clue how other countries work. This is not to say that I know the US system that well - but rather that it's the only system I know at all.

Public universities work differently from private universities. Public universities usually have pay scales and these are often public since professors are considered state employees (yes, my salary is public knowledge). So you can start digging around there. Usually there's a range within which you can hope to negotiate: moving out of that range is beyond even the power of the university to authorize.

Private universities usually have more flexibility and it might be harder to get the range of salaries. But if you get an offer you can ask around to get a sense of the ballpark.

As for what a reasonable range is, getting data is very discipline-specific. For CS, the CRA puts out stats fairly regularly and there's the Taulbee survey. For other disciplines, there might be something similar.

Salaries in academia at least at tenure-track level are less flexible in general. Probably the best way to get to the top of the permissible range is to have another offer. Other than that it's hard. Often, the things that are most easily negotiated are other parts of the startup package. Which is not to say that you shouldn't negotiate salary - but unlike in industry, it's less likely to be as beneficial.


Choosing between Bachelors's in a higher uni vs masters in less reputable uni? I graduated with an EE degree last year and interned in two Physics labs, From September until March for experimental physics in Lab until COVID struck and lab closed and another one from Mid Summer (June) until September in computational physics (still continuing part-time I will come to that later).
Been applying for the Fall 2021 cycle to Physics Grad programs however I was told that I lacked a Physics Background [ Had only taken EM classes and maybe 1st-year basic waves and mechanics].
Recently I got in BSC honors in Physics in a reputable university [will take roughly 2 to 2.5 years] along with another offer in Masters in a less reputable university with a requirement to complete a qualifying year (consists of higher Physics undergraduate courses). I talked with the department and supervisor who has told me that funding is available for research as well as some money from being a TA. I was only able to get in due to a connection from another prof in another University who very much vouched but failed to convince the admission committee in his University (due to lack of physics background). So I would also assume that the supervisor has done the same.
Being torn I don't know what I should choose, I feel l should choose Bachelors and then apply directly for Ph.D. while masters and then Ph.D. would take the same amount of time. In  addition, my current research professor is very enthusiastic about what I have done with the detector simulation software development (he is the leader of the research group I am in which I can't specify for personal identification reasons) and he has suggested a collaboration with the university which I want to do bachelors in and wants me in future after I complete bachelors.
Financially speaking I would assume that Masters would be slightly less expensive than doing Bachelors (from approximate calculations I have done).
I am just very much torn between these options, the professors on both sides have gone out of their way to help me pursue my passion.
Additional follow up: Does it matter where you do your masters for Ph.D. (plan on pursuing an academic career)  in terms of university ranking and reputation?
Sorry for long text, and thanks for any advice, suggestions!

Paying for a masters degree in physics is a poor idea, even a poorer idea is a second BS in physics.
Get an engineering degree if you're going to spend your own money.


Applying to a lab as a post-doc; I am peer-reviewing their work I'm applying to a lab whose work I happen to be pretty familiar with, due to peer reviewing one of their articles.

Is it ethical to mention this information to them?  I feel that if I don't mention it, and they find out later, they may feel that I mistrusted or misrepresented during the application process.

Does the answer depend on whether the article has already been published, or whether it's still in the review process?

If you have previously peer-reviewed their work, you are obligated keep that information confidential unless the journal policy says otherwise.  If your potential employer somehow finds out you reviewed their work, they will know you did the right thing.

If you are currently reviewing their work and applying for a job with them, you should stop reviewing and contact the editor.  Tell the editor you now have a conflict of interest and cannot continue reviewing.


Statement of Interest for Ph.D. admissions I am trying for a Ph.D. (computational biology) at IMSc, India (link). They are asking a covering letter, a statement of interest, a curriculum vitae including university grades/marks. When I searched about statement of interest, some webpages were dealing this same as thesis proposal. So I am confused.

Is statement of interest, statement of purpose and thesis proposal same?

The primary difference between a statement of interest (or purpose) and a thesis proposal is the specificity. A thesis proposal outlines a specific project to be pursued during the thesis research, and will usually be written at some point during the process. However, in many cases, this is done after the graduate student has been accepted and joined a particular research group, rather than before admission has been granted. When asked for at the admission stage, it's usually in cases where the assignment to a particular research advisor is done at the outset of the doctoral program.

A statement of interest, on the other hand, simply details the kinds of problems or research areas a given student would like to pursue as a graduate student. This is usually asked for in admission cases where the decision is being made at the departmental level, rather than the individual faculty member level. A student is not specifically committing to a particular project at this stage—nor does the department necessarily want such a commitment.


How to make my work publishable if my supervisor isn’t any help? I just finished a bachelor’s degree in applied maths. The thesis was designed to be a fairly formulaic implementation affair of an (obscure) NP-problem, but I happened to develop a novel heuristic algorithm for it, which had some very interesting properties, both theoretical and computational.

The problem is not a canonical NP-problem, but a rather obscure one. It could be that no one would care at all, but

it does seem to outperform all previously published heuristics;
it is based on a novel way of utilizing the problem structure that conceivably could be applied to other NP-problems.

“Talk to your supervisor” is good advice, but he didn’t show any interest in the project throughout the semester (despite it being his area of research) and he hasn’t even commented on the report, despite being asked repeatedly. At this point, I am close to certain he will be of no aid if I would want to pursue this further.

I asked the head professor at the department as well – he said he’d read it but hasn’t. I reminded him about it but that looks like a dead end as well.

So what are my options? It’s far from publishable in its current state and I obviously can’t pursue it further on my own.

The foremost thing you need is a mentor familiar with the subject to guide you through the process of paper writing and in particular provide feedback to you. Unless you are very good at it, writing a mathematical paper without any feedback is a bad idea, as it’s very difficult to estimate yourself whether your writing is understandable to others. Also, scientific writing is an art of its own that you probably have not mastered yet.

As you already guessed, the canonical choice for such a mentor is your supervisor, but as he is not an option, I would consider the following (in roughly this order):

other members (PhD students, postdocs, etc.) of your supervisor’s group who have experience in paper writing;
visiting scientists or collaborators of your supervisor;
other scientists from your department, with whom you are on friendly terms;
scientists from other universities doing related work;
look for a mentor on your department’s bulletin board or similar.

To avoid quarrels with potential mentors and because it’s ethical, you should clarify the following:

You are not good at estimating the publishability of your work. It may very well be that it turns out to be unpublishable.
The essentials of the situation between you and your supervisor.
How you will handle authorship: Just mentoring your paper writing does not qualify for authorship by common authorship standards, but it’s not unlikely that your mentor will, e.g., find some extension or improvement of your work that is worthy of authorship. Authorship may be a relevant incentive for mentors. For more information, see authorship.

Together with a mentor it should be much easier to decide on the publishability of your work and what journal is suitable for it.

Finally, some further caveats:

Depending on how much your supervisor laid the intellectual foundations for your reasearch, e.g., by giving you detailed ideas on what you should research and how to do it, he may have reasonable authorship claims. Unless he verifiably abandons these claims, this would lead to all sorts of trouble.
If you are worried about your work being stolen, you can publish the current state as a preprint, e.g., on the ArXiv. Be aware that there are journals that do not allow for such prior publication, but as far as I know, this is not a problem in mathematics.


How to formulate my resume, if a PhD defense exam fails with mark “Dissertation passed, Oral failed” My PhD examination consists of two parts namely the dissertation note and the oral note. Unfortunately, it was fails with “Dissertation passed, Oral failed”.
What could be the best way to form it in my resume?
Could I write: finished PhD study only with Dissertation, in short “PhD Dissertation”?

So, have you officially been granted a degree of Ph.D. or have you not?
I cannot tell from the way that your question is currently phrased.

If you have a Ph.D., you can simply honestly write down that you have a Ph.D. degree, and not attempt to explain whatever it means at your institution to be given a Ph.D. while failing your defense.  Don't hide it if you are asked, but if this is the case then apparently your institution thinks that you are worthy of a Ph.D., and it's up to others to judge whether they respect your institution.

If you do not actually have a Ph.D. yet, then you can't write that you have a Ph.D., and it probably doesn't matter all that much to the reader that you have an accepted dissertation.


What is the norm in PhD internships in terms of their duration, tasks, and location. Context:

I am on my third year doing a PhD in Engineering in a North American University. The norm in my institution is that a PhD is 5-6 years long. I was funded through the past period of time through a scholarship. The "understanding" is that the advisor funds students after the initial three years but nothing is formal.

Situation:

My advisor found an internship opportunity for me and "strongly" suggested that I take it. In this case, the company pays me while I am there.  During that time, he gets matching funding from the government. The idea is that he would use the matching funding to pay me after the internship ends. He basically takes the money and gives to me back later. I trust that he will do that. I am not sure if this is considered normal or not in acadima but that is not my question.

The problem:

The problem is that some aspects of this specific internship seem abnormal to me and I want to get feedback from the community about these aspects.

Questions:

1- The internship is for 9 Months. It is full-time internship and I will not have time to work on my PhD. This means that my PhD is extended by 9 Months (5-6 Years + 9 Months). Is this a normal period of time for a PhD internship? I have seem people go on a 3-4 Months internships and even 6 in one case but never 9.

2- The tasks of this internship seems to be a long the lines of a Full-time engineering job. There does not seem to be any research involved. My thinking was that a PhD internship would help me develop my research skills and this seems to be an internship for a masters student or an undergrad. Is it normal for an PhD internship to be a full-time job in disguise?

3- The internship is located in another city. I have to move there for 9 months. This would require me to completely change my living situation twice in 9 months. Is this considered normal?

I am considering passing on this opportunity and finding a more suitable one myself. I just wanted to get feedback from experienced people before doing so. I would appreciate any input.

For research internships I think doing a bit longer will result in better outcomes. In my experience it takes 1-2 month to get into a new work environment/topic and doing serious research in 2 month is unlikely.
The best way to find out is to talk to your supervisor (at the internship) about this. The internship should not be a pure engineering task (it is still a full-time position though). It is probably to be expected that you do some hands-on work but you can ask about the topic and the probability that this will result in a publication. Depending on what your PhD topic is, you could also see this as an opportunity to get some real-world experience.
This is quite normal (I moved to the US for 6 months, I know a lot of people who did this). Of course if you do not want to do this, your supervisor should not be pushing you.

It would be best to consult with your advisor before searching for something else yourself. Maybe he just wants the additional funding for you but maybe there is something else about this internship that makes him think it is suitable for you.


Can I change the referee once the letter of reference has been submitted? I am applying for a PhD position in US universities. I started an application for a specific university and suggested my referee names. My referees have already submitted their LORs. But I did not submit the application later. But they are in the application portal.
Now I want to submit an application for the next semester and I have a hunch that one of the letters was not that strong or impact my application in a negative way. So I want to change my referee. My question is- is it possible to change because she already submitted the letter.
Also, how important a referee is? I have a referee with whom I worked on one project and have good relations. On the other hand, there is someone with whom I have 3/4 publications but I have a doubt he will write something good (because he wants me to finish the remained projects first and does not want me to leave the lab right now).

The importance of letters of reference is covered in many other questions on this forum, and I won't discuss it here.
As for changing letters of reference: Most systems are set up to just take as many letters as are submitted. They will then all become visible to the selection committee. In other words, there is probably little you can do about the already submitted letter short of writing to the selection committee to disregard that one letter -- but that raises so many other questions that I don't see that as a winning strategy either.


Is it advisable to hand in a thesis by visiting my supervisor's house? I have to hand in the thesis to my supervisor, but I could neither find him in the faculty nor contact him, but I know his house.

Is it advisable to hand in a thesis by visiting my supervisor's house?

I wouldn't find it okay if someone would come to my house because of that. Work and personal life should be separate and it would be inappropriate to visit the supervisor there.

Does he not have an office? If nobody can tell you where to find him, then you should call him or write an email and ask for an appointment.


Possibility of doing PhD in astronomy with only masters in CS I have a masters degree in Computer Science & Engineering (and currently employed in s/w industry in India), but have no degree in physics. For long, I've been interested in doing research in physics, especially in astronomy, astrophysics or in particle physics.

Are there good institutes or universities in EU, US or India which accept students without any degree in physics to PhD program in astronomy or astrophysics? If so, do they also offer financial assistance or some form of scholarship to such students to meet at least one's tuition fee expenses?
I checked with an institute in Germany that offers PhD in physics but I was told that a masters degree in physics is a mandatory prerequisite. Does this apply to all leading German institutes? What about other leading institutes in EU or in the US?
What are the pros and cons, if any, between doing PhD in US versus in EU, especially in the field of physics (in the subdomains I mentioned, if that too matters)?

In Sweden there is no hard requirement. (In Spain, for that matter, there isn't either, but I don't recommend going for a PhD there). You just need to convince a professor that you are a good asset for the team. The way it works here (and in some other countries in Europe) is that the PI gets funding and hires whomever he wants, based on whatever criteria. Other countries make the decision at a department level, usually putting stress on the marks. Anyway, the difference is convincing one party or a few.

It is true that all the people I know in the closest related department, are physicist, but they do a lot of programming and data analysis. Your strong points are:

You can improve code quality. (I have seen code that gives me nightmares.)
You can implement new algorithms.
You can learn the physics along the way.

CS backgrounds are, by the way, quite common in Bioinformatics and, to a lesser degree, Biophysics.

References:

I am in Sweden working in Biophysics, and my girlfriend is doing a PhD in Astrophysics.


What metrics are used to judge a mathematical journal's quality? The metric I see most on the internet and on journals' home pages is the 'Impact Factor'. Are there any other metrics that are considered as important as (or more important than) the Impact Factor?

To expand on JeffE's comment, impact factor gets zero respect among mathematicians.  It gets very little respect in any field, as far as I know, but it's a particularly bad measure for mathematics journals.  For example, it only counts citation received within two years of publication, which is just about the quickest turnaround time you could get in mathematics (given math's publishing practices and timing).  So numerically, the impact factor amounts to saying that if your paper doesn't inspire people to drop everything else and rush to get followup work into print quickly enough, then it has had zero impact.

Impact factors are also manipulated by journal editors, often enough to require serious work detecting and punishing this behavior.

The only reason impact factors exist at all is that administrators want simple ways to rate research productivity, especially in dysfunctional settings where there's no infrastructure of trusted experts.  Counting citations is easier to defend as "unbiased" than most other approaches.

There are many other numerical measures of journal quality, such as eigenfactors, but they are not popular or widely used.

In 2010, the Australian Research Council rated 20,000 journals by quality based on expert opinion (for example, see here for the math journals).  This is still not great, since the ratings miss subtleties (such as journals with greater strength in some subfields than others) and it's not clear how reliable they are for lesser-known journals anyway.  However, this is the closest anyone has come to giving a replacement for impact factors based on expert opinion.  Unfortunately, it was so much work that they decided not to do it again.


Journal ranking statistics on scimagojr vs. the "prestige" of its editorial board My advisor and I are considering where to submit a paper based on my thesis. Originally we planned to submit it to Journal X, but an opportunity arose to submit it to Journal Y following a conference invitation (where "X" and "Y" are so named to preserve the generality of the question and my privacy).

Journal X is a popular journal with a distinguished editorial board. On ranking sites such as scimagojr it appears to be ranked Q1 or Q2 depending on the subject field with the rest of the statistics similar.

In recent years, 2010 and onwards, Journal Y seems to significantly outrank Journal X in virtually all the statistics offered by scimagojr (e.g. its H-index and "impact factor" are several times higher), though their subjects of interest only partially overlap. It ranks among the top 5% journals in its listed subjects (it seems to have exploded in 2010 or so). So, to me it naturally seems a better target for publication.

The issue is this: my advisor (a well-known researcher in his field who knows a lot of people) is unfamiliar with this journal, and is generally unfamiliar with its editorial  board, which seems to him of not very high quality. As such, though he seems impressed by the rankings, he is unsure if I should submit it to this journal and left the decision to me.

The question is this: how should I weigh the "prestige" of the editorial board of a Journal as compared to the more numerical statistics offered by scimagojr? Should I be concerned that my advisor doesn't know anyone on the board?

Sumbit where you think it will have a better visibility. Rule of thumb: do not submit to a journal that you barely know any member of the editorial board. You want to maximize the impact of your paper and, as such, submit somehwere where it would be most appreciated both by the editorial and by the readership of the journal.

I do not think it will do your paper a big favour to submit to a journal with high (possibly artificially infated) statistics than to one well known and well respected, with distinguished editorial board most likely to take good notice of your work and, consequently, you.


Justification statement for exceeding the maximum length of manuscript I am submitting a manuscript to a journal that specifies "papers must not exceed 30 double-spaced manuscript pages, including all figures and tables." My manuscript has 37 pages. The journal asks to provide a justification statement if the manuscript exceeds the length limitations. Based on previous experience with the journal, one of my colleagues told that the journal is not too strict and generally considers papers that exceed the maximum specified length. Since I am submitting a manuscript to this journal for the first time, I am quite anxious. Please advise how I may justify the length of the manuscript.

Assuming it is true, I'd say that I'd made a good faith effort to keep it to the limits, considering whether any of the material was extraneous, but it is still at 37 pages.
But also add that you would welcome advice from reviewers including advice on reducing the length.
I doubt that a detailed technical statement will get the result you want, since the editor may not be able to evaluate what you say since that is more the job of reviewers.
Some papers can also be split into two, of course. Perhaps you have considered that already. Not all, of course, but it is worth a look.


Publications and International Standard for bibliographic references I'm applying for a job which requires the list of all publications.
Quoting the call:

  Publications over the last 10 years in chronological order within each category following the International Standard for bibliographic references with DOI whenever possible.

I'm a bit confused because I have no clue how to write my publications in this format.
Since I'm a computer scientist I usually take the bibtex from databases like DBLP or Scholar, but I'm not sure if it's equivalent for this International Standard.
Do you have any suggestions?

Have you searched for this citation style? There is even a wikipedia article on this: https://en.wikipedia.org/wiki/International_Standard_Bibliographic_Description. There is an example which gives you an hint how you should structure your bibliographic reference. If a certain element of the list can't be applied to one of your publications , you could leave it out/not mention it.  My guess would be that official university catalogs use this or a similar style and you could consult these to make sure you do it right.


What things can I do as a job market candidate to gauge the internal political culture of a department that is hiring? I am about to finish my phd and have been frustrated with the toxic politics and culture of my department.

During the job search, what are some specific things I can do to learn about the internal political environment of the hiring department?

I am not talking about their personal political beliefs, but instead the politics of how things are decided in the department, whether people respect each other, whether there are camps fighting for power, etc.

I want to avoid ending up in a department with similar political problems as the one I'm in now.

One measure of the politics within a department is the faculty member's attitude towards collaborations. When I was touring grad schools as a prospective PhD student I remember interviewing with a faculty member. I asked her if she collaborated with other faculty within the department or other departments. She answered dismissively and instead asked me why I was interested in asking such questions and why it mattered whether she was involved in collaborations. If you get such a response, or sense such attitudes, this might imply there is an unhealthy dose of hostility or competition between faculty within the department.


Cover letter for journal submission (math) I'm preparing to submit a math paper to a good general-interest journal.  The page asks for a cover letter.  What should this include, beyond "here's a paper for consideration"?  Should there be, for example, a brief summary? Claims about why I think it's interesting?  Suggested reviewers? The first two of these of course appear in the article. The journal submission page gives no guidance.

This is a near-dupe of Are cover letters sent to referees and should you highlight the contribution of your paper in the cover letter?.  However, Googling around suggests that the answer is rather field-dependent, and this is not reflected in the answers there.  I am looking for information relevant to pure math, for which a search hasn't turned up anything.

In my previous submissions I've basically blown this off, per my adviser's advice.  It doesn't seem to have caused any problems, but I'm wondering if there's anything I can do to make the editor's life easier.

Unless the journal asks for any specific pieces of information, then a "Here it is for your consideration" is all that's required. In the (math) journals I'm an editor of, that is essentially what the letters look like, and they almost never contain anything that is of importance to the editor or to reviewers.

I believe that this is very different in other areas, but then the submission guidelines will say so.


Examples of teams of teachers? There was another question In universities, how to team up with your colleagues? which talked about building relationships but what I am really curious about is:

Are there any universities which actually have teams of teachers?

I am not referring to simply two teachers sharing the same module. I am also not referring to teachers being friendly with each other. I'm referring to teachers actually being developed into a formal team. In a team not everyone has the same skills and those differences make the team stronger, not weaker. In teams there is a genuine interdependence. In a team, there are common objectives which you know have been met or not.

There are many examples of increased effectiveness of teams (and certainly plenty of books and articles written about them) but since teaching is such a solitary activity (meaning you do not interact with your colleagues while teaching) perhaps it is natural to ignore the idea of actually building teams of teachers.

Edit: When studying team dynamics, we can see that "real" teams do include some risks but my point is not about the weaknesses (which are typically overcome by the strengths). Teams normally operate an a higher level of efficiency than non-team-groups-of-people working together. A key element of real teams is that objectives are team objectives and individual accomplishments are not highlighted. For example, if 3 teams are all competing to get to the top of the mountain and we give a reward to the first person to summit the mountain, then we are really focusing on individual efforts (so each member would naturally think of themselves before the group as a whole). However, if you simply reward the team which first plants its flag at the top, then individual accomplishments are minimized and one member of the team is more likely to sacrifice for the greater good of the team.

Indicators of real teams (as opposed to groups of people who work together but are not a team) include: Interdependence, shared accountability (each answers to the boss but also to every other member), common goals, and members having skills which compliment each other in order to affect the common goals.

Do we ever see these qualities in groups of teachers?

In the more advanced levels, I have had subjects taught by several lecturers. Each one was teaching the part of the subject closer to their area of research and expertise.

On a more general level, there was a department of Astronomy and Atmospheric physics (climate and weather). Astrophysics subjects were taught by astrophysicists, and climate subjects by atmospheric scientists (do they have a cool specific name?). Inside Astrophysics, stellar evolution was taught by a different subset of professors than extragalatic astronomy.

It is also common for the senior professors to lecture, and the grad students to do problem solving. This is usually explained because a clear explanation of the theory requires experience and care; whereas solving exercises is a less critical task, ideal to build teaching experience. (Bad people that hate professors may say that teaching theory requires less work, and once it is done they can repeat the same for years, but solving exercises requires more work)

Edit:

Another example is the curriculum. Each subject is built upon the subjects taught before, with more or less coordination among the lecturers. Differential equations requires the knowledge obtained in Calculus, and it will in turn be used for Quantum Mechanics. If the Calculus lecturer fails miserably (for example, not covering the necessary material), the students will struggle through the following ones.


Which license should I aim to publish articles & software under? Suppose I have the choice of license under which to publish my research work in Computer Science (constituting scientific papers and software) online; and that I need to make this decision before any journal or conference has accepted any of it. Specifically, suppose for the sake of discussion my academic employer would accept whatever it is I choose.

So, what to do, what to do... Is "better" or worse to put things in the public domain (e.g. via a CC0 dedication or otherwise), or to have a more rigid license? The FSF seems to be pretty critical of Creative Commons licenses, yet these can be seen at, say, arXiv... plus, I'm not sure I want to be all that legalistic with a 1000 pages of license text.

What should guide me when choosing the license, then? And what does your "licensing experience" teach you?

CC licenses are good for the written word, but you need a software license for software. You're going to have to have two licenses at the very least. On top of that, depending on your publication venue, you may not have a choice of license. Many venues require the transfer of copyright in order to publish, so your license for your articles may not matter once you give up your copyright.

To answer your question directly, for publicly funded work, I prefer the 3-clause BSD over public domain for software, but this is partially due to my institution's requirement to either use GPLv2 or BSD for software. For documentation CC-BY is my preference, and I have no institutional requirements there. I have these preferences because I believe that publicly funded work should be as open and free as possible to the people (i.e. the public) that funded it, but I adhere to an academic perspective that credit should be given where credit is due.


Why does arxiv.org not assign DOIs? I know that arXiv have their own identifier system, but considering how widely adopted DOI is, why do they not use DOI perhaps as a supplement to their own identifier?

At least in mathematics, the arXiv is a pre-print server --- papers are mostly eventually published, and receive DOIs then. In fact, the arXiv encourages authors to add these DOIs to the arXiv metadata when they become available.

I think it could be quite confusing for papers to end up with two DOIs. Given that the arXiv numbering scheme works quite well, and in practice everyone knows how to resolve handles of the form arXiv:NNNN.MMMMM, why add the complication?


Moving from Switzerland to Germany during my PhD, how do they count working experience I already have? I am currently doing my PhD in Switzerland. Since my professor recently get a job in Germany and will move the whole lab there, I need to go with her. That brings up to the question of working experience on the table. Both in Switzerland and Germany, the salary increase with the year of PhD. However, I am not sure if I move to Germany I would be counted as the level starting from the first year or they will consider the time I already had in Switzerland. Anyone has related experience?

You will have to ask the administration, or ask your advisor to ask the administration. Unless you transfer within Germany, this is decided on a per-case basis. But in principle, if you have equivalent experience to the current position (which you do), this should be feasible. However, as also pointed out in the comments, you will only get the corresponding level, but with all likelihood you won't get the runtime within the level counted. It might help if you add how much time you spent on your PhD in Switzerland at the point at which you will move.


In Sweden, can a supervisor ask his PhD student to provide a private future work list of his thesis? Recently, I faced a new academic phenomenon that a high level researcher informed me about. I am writing a potential reasoning of the phenomenon:

From a legal point of view, PhD is similar to a transaction in which a PhD student produces an innovative content for the University and, in return, the University will give the student a PhD degree. Thus, it may be concluded that whatever the student produces in these years in direction of his thesis is for University.
Moreover, one of the important aspects of a successful research is the potential growth that a research can have (future work). A part of the future work is written inside the thesis; however, many times this part is not such detailed.

Now, suppose that a supervisor wants to take advantage of the future potency of work of the PhD student for the future PhD students of the same University (assuming that the University has the intellectual property of whatever he has produced in direction of his thesis).
In this regard, the supervisor may decide to ask him provide a detailed future work list with explanations as a private/inter-lab document so that the next students follow this direction.
Is this request legal (based on the Swedish regulations) from a supervisor to his student?

A supervisor who asks you to write a detailed "future work" document might be trying to cheat you as you appear to worry about, but it's unlikely.

What's much more likely is that they're interested in the scope for future projects both for students, and for postdocs.  If your supervisor can get a grant based on work you've done during your PhD, and there's funding for a postdoc on that, it could well be to your benefit - you should interview well on the topic at least.

Without the backing of your supervisor (either in their lab, or moving on with a reference from them) you're unlikely to have the chance to work on this material anyway, and your dead ends may prove to be good projects for new students with a different skill set.

Finally viewing anything in academia as a simple transaction is rarely helpful model.


Why do some tests have a (nonzero) minimum score? Some tests have minimums in their possible score range. Cisco's 300-1000 point range, and the SAT's 200-800 point per section range come to mind.

What purpose does this serve? I assume there is some statistical logic behind it. Maybe it would make more sense to me if I understood how they go about calculating the score from a given number of (in)correct questions.

According to the Encyclopedia of Research Design (page 629), it signals that these are interval variables, not ratio variables:

  Standardized tests, including Intelligence Quotient (IQ), Scholastic Achievement Test (SAT), Graduate Record Examination (GRE), Graduate Management Admission Test (GMAT), and Miller Analogies Test (MAT) are also examples of an interval scale. For example, in the IQ scale, the difference between 150 and 160 is the same as that between 80 and 90. Similarly, the distance in the GRE scores between 350 and 400 is the same as the distance between 500 and 550.

  Standardized tests are not based on a "true zero" point that represents the lack of intelligence. These standardized tests do not even have a zero point. The lowest possible score for these standardized tests is not zero. Because of the lack of a "true zero" point, standardized tests cannot make statements about the ratio of their scores. Those who have an IQ score of 150 are not twice as intelligent as those who have an IQ score of 75. Similarly, such a ratio cannot apply to other standardized tests including SAT, GRE, GMAT, or MAT.

Salkind, Neil J., ed. Encyclopedia of research design. Vol. 1. Sage, 2010.


Focusing on one specific academic field? This question has already been asked, albeit not so much, in this thread. This, however, still gets me thinking. I am an early career research (not even done with my PhD yet). A PhD candidate told me that despite all my papers being focused in one country, I am "all over the place." Meaning, my published works are in different fields (i.e. sociolinguistics, politics, anthropology, international relations) - all of which I have a good grasp with. What is common among all my publications are my ideological standpoints. I remained consistent.

My degrees are in area studies, and I did (and still does) all the researches for my degrees in the fields of sociolinguistics, the politics of language, and political rhetoric. Area Studies is so broad enough that it can be considered multi- and interdisciplinary.

However, will writing and being able to have my works published in various fields in the social sciences affect my profile (positively or negatively) when I apply for faculty positions in the future?

To give a general answer: If you can show you have a significant, long-running research agenda, i.e. if you can bind the different publication or most of them with a single narrative - than it's probably ok. Of course, expectations depend by field, country etc.


How to deal with an uncommunicative advisor? So I have an advisor who seems to be kind of peculiar. He is quite famous in his field and has good reputation.

However, his way of working with students is more like waiting for him to come up with ideas for students. And since he has "good taste", he is always aiming for big goals which makes it take a lot longer to formulate any concrete project.

Research ideas from students are usually discarded. It's been over a year and I still don't have a research project. Also, for papers that he thinks aren't that important, he will ask his student to write it up and rarely take his time to read the paper or provide suggestions for revising which means that students have to wait a long time to get anything published.

The other funny thing is that he almost never replies back to his students' emails and rarely helps his students in finding postdoc positions. How do I work with this kind of advisor and is it a good idea to switch advisors?

If the advisor is well respected externally in her field and active (what is her publication/conference record in the last 5 years?) and relatively supportive in other ways (interesting conversations about research topics, is available in person when students drop, has funding) and if she has a group of supported students/postdocs in her group; then my advice is to decide whether your personality allows you (cheerfully or pretend-cheerfully) to take on some leadership roles in self-mentoring.

start a weekly or bi-weekly group meeting, journal club, or similar where also people in the group talk about what they are doing. (try to arrange that it is convenient time (check his class schedule/university meetings) but do the meetings even the weeks he cannot show.
schedule a 20-30 minute meeting with him once every week or two regularly to discuss progress, don't count on him to set it up. Make sure to prepare something (at the beginning) that isn't asking for help so much as showing off things you find interesting or have accomplished that week.

The point is to avoid appearing as if you need hand-holding, but to get some interactions going which are positive and useful for yourself to succeed. (And show of how much of a self-starter you are).

The delay in publishing papers - if there are senior co-authors, also look to them.

On the other hand -  choose another advisor
Sometimes email gets buried, but a consistent 'never replying or acknowledging an email from student(colleagues,department admin)'  gives me the heebie-jeebies. We have had several faculty in my department over the years who had that trait and in their particular cases it never made any sense except as some stupid passive-agressive issue. So, on the basis of that trait alone, I'd suggest finding someone else who is more excited about their work and respectful of other's time and energy.


Correcting a mistake in my journal article after it's been published My research is in humanities and social sciences and my article was published in a journal in Dec 2016. When the online issue came out, I immediately realised that a mistaken was made, where quotation marks should be in my article title. This was mainly my fault given that said quotation marks were removed from my original and revised submissions when the first proofread came through to me, and I mistook that as a journal style issue.

Now I'm asking the editor about erratum procedures but based on their responses, I'm beginning to think they don't have such a policy in place. If that is so, what would this community advise I do? Part of my title quoted a well-known figure and the last I want to be accused of is plagiarism! E.g. can I add an errata on my personal/academic webpages and will that be of any use? I'm a final year PhD candidate.

Appreciate any useful help I can get here. Thank you.

The official way of dealing with this (minor errors which don't substantially impact the conclusions of the paper) is with the errata/corrections section in the journal you published in. So you did the correct thing in contacting the editor about issuing a correction/erratum in a future issue of the journal.

Your problem at this point is the fact that the journal doesn't have a formal errata policy. There's two ways to proceed:

The first is to attempt to convince the journal to establish an errata policy, for which you'll be the first example. This is ideal, but the editors might not be willing to do it, as it may involve substantially reworking how their journal is structured. Keep in mind that even if they accept the erratum, they might not actually change the published version of the article (even on their website), instead just adding the correction as a separate "erratum" notice/page.

The second is to simply post the erratum on your professional website, preferably on an official(ish) "errata" page. If the journal doesn't have an official errata policy, then this is probably the best option. It's used extensively by people who publish books (including textbooks). Having it on your own website may limit the visibility of the correction, but it will indicate to people who care that you're being proactive about correcting your mistakes to the best of your ability.


Studying for mathematics comprehensive exams Should mathematics PhD students work through all of the past exams, if, say, the department makes the last 20 years of exam questions available to students?

Or should students mainly focus on the most recent years' exams instead? - and that perhaps one cannot do all of the exams, because it is almost not humanly possible.

Just seeking general advice.

Thanks.

Going through problems on old exams will give you some idea of the kinds of questions that are used in these exams, but the committees that write these exams will change over time.  This means that very old exams might not be representative of what you'll be given this year.  Even if you focus on more recent exams, the committee might have changed and you could well get an exam that looks very different from last year's exam.

In any case, solving problems from previous exams should not be the only way in which you study.  You should also take time to review the subject and consolidate your understanding of key concepts, definitions, formulas, and theorems.

In my experience of grading these exams, I've seen that students who have difficulty typically fail for one of the following reasons:

Not knowing some required definition or theorem.  If a question is of the form "Show that A has the Frobnitz property" and you don't know what the Frobnitz property is, you simply won't be able to answer that question.  You can avoid this by having read broadly on the subject and by making sure that you have committed important definitions and theorems to memory.
Not having good problem solving skills.  Although doing old comprehensive exam problems will certainly help with this, doing problems from many sources is likely to be just as helpful.  The key here is to focus on solving hard problems that may involve several non-obvious steps rather than the trivial exercises that fill many textbooks.  Keep in mind that with a textbook you've been given a lot of context- if the problem appears in the chapter on contour integration than you can assume that the problem involves contour integration.  This won't be true of the problems on your comprehensive exam.
Poorly written solutions.  Sloppy logic in the solution to a homework problem might get substantial partial credit in an undergraduate class.  In a comprehensive exam this is much less likely to happen.  You need to give precise and rigorous solutions that cover all aspects of the problem, and there is no room for arithmetic or algebra errors.  The difficulty in preparing for this is that you need someone competent to critique your solutions.  If you have a study partner, I would suggest that you pick some problems to solve separately and then grade each other's solutions critically.   If you find that you're making seemingly minor mistakes but usually have the basic idea for a correct solution, this is an indication that you need to check your work more carefully.


What should the course leader do if some students were given less time for a quiz? I am the course leader for a course with more than 600 students.
This semester,
I decided to conduct our end-of-semester quiz
as a computer-based quiz using our school's learning management system.
We needed to reserve multiple computer lab rooms
due to the fact that the maximum capacity of a lab room is about 80 students.

Unfortunately,
we had always used a paper-based quiz in the past,
and it was the first time that we had ever used computer-based quiz,
so things did not go as smoothly as we would have liked.

We had requested that the students
should show up to the quiz venue 10 minutes early.
This would give them time to turn on the computers
and to log in to the quiz using
a special browser (Respondus LockDown Browser)
rather than the regular Internet Explorer browser.
Unfortunately, our instructions to the invigilators and the students
were not clear enough,
so even though most of the students showed up
to the quiz venue 10 minutes early as requested.
The invigilators did not make clear to the students
how to log into the computers and into the quiz,
so many of the students started the quiz 5-10 minutes late.

I attempted to communicate with the invigilators
to give the students 5 additional minutes to complete the quiz.
Unfortunately, due to miscommunication,
some of the invigilators ended the quiz on time
(so the students in their session had 50-55 minutes);
whereas some of the invigilators gave the students extra time
(so the students in their session had close to 60 minutes).

After the quiz was over,
some of the students who received 50-55 minutes complained to me
that they were disadvantaged because
they had less time to complete the quiz than other students.
It may or may not have been the student's fault
if he or she had less time for the quiz.

For some of these students,
they had less time because
they arrived late (which is their fault)
For other students,
they arrived on time.
However, because their computers booted up slowly,
or the invigilators did not make it clear
how to open the correct browser and how to start the quiz,
they started their quiz late by ~5 minutes
(this could have been avoided with better planning on our part).

Questions:

How should I respond to these student's complaints?
Is there anything that I should do to "fix" the situation?

Currently, I feel that the quiz was mostly fair to the students.
I am able to see in the learning management system that
fewer than 0.1% of the questions were not answered,
which means that 99.9% of the questions were submitted properly.
So although some students who had more time
had the benefit of double-checking their answers,
for the most part even students who only had 50 minutes
had enough time to complete all of the questions.

I believe there are a lot of circumstances that have to factor in to the decision, but to me, the most important initial detail is, do you have any way of reliably tracking whose time was cut short and who had the full time allotted? If not, it's going to be hard to analyze and correct the situation.

I'm assuming that, since it was a quiz, it's not a huge factor in their grade, so what I might do is either renormalize the grading or pro-rate it. Basically, if the quiz was supposed to take 60 minutes, and the most any students were shorted (by no fault of their own) was 10 minutes (still less than 20%), then the new baseline can be considered to be 50 minutes, or 83% of the original time.

To renormalize, multiply every student's grade by 1.2. For students over the new 100% mark, you could give extra credit or simply cap the score at 100%.

Or you can do a quick-and-dirty pro-rate by adding 17% to everybody's score, again, either up to a maximum of 100% or going over and giving extra credit.

I realize you have a huge class, which also implies you have a lot of early-undergrad students who might raise a bigger stink, but in my academic career, I've seen plenty of ex post facto shifting because of logistics, especially when a prof or the school is rolling out a new technological approach.