Cheated on an exam when I was eight years old. Should I tell graduate admissions? I cheated at a language exam when I was eight years old. I finished early and noticed that I had accidentally left a dictionary in my drawer. I double-checked my answers and promptly got caught.
The incident is probably unverifiable at this point: The physical evidence is long gone; the teacher probably retired; the school probably didn’t keep records or has already destroyed it. I might be the only person on the planet who still remembers it.

Should I mention this incident when being asked about academic integrity in job interviews or similar?
Should I tell graduate admissions?

I suspect the answer is no since it was so long ago and I was eight years old, but I’m afraid I might be rationalizing.

As noted in the comments, actions committed long ago as a child are (and should be) entirely irrelevant to graduate admissions.

It is well understood that children do not have same ability as adults to comprehend the consequences on their actions.  As a result, many legal systems wipe a child's record clean of most or all juvenile offenses upon reaching adulthood.

I would thus similarly argue that any academic offense predating your undergraduate education should generally neither be reported nor considered in an application for graduate school.


Putting future professor position on CV I have already received and signed an offer letter for a position as an assistant professor. This position will start next fall, to give me time to finish my post-doc. I'll be applying for a number of grants over the next year. Should I include my future position on my CV for these applications? It seems like relevant context for reviewers to have, but I've never seen anyone do it.

Typically grants are administered by institutions, and therefore the grant is really to the university and not the individual. Therefore, it is likely that you will be applying for funds on behalf of your new, rather than current, affiliation.

In that case, it certainly makes sense and is more or less necessary to include that new institution.

From the perspective of NIH, for example, they say explicitly:

  For individuals who are not currently located at the applicant organization, include the expected position at the applicant organization and the expected start date.

referring to the "biosketch" document which for NIH grants serves the purpose of a formatted CV. And also:

  If your proposed career development award will be at a different site than your current institution, the proposed sponsoring institution will be the applicant organization. You must affiliate your Commons account with that institution so that you have access to records submitted on your behalf.

(this is referring to the class of NIH grants that would most likely be applied for by someone transitioning from a post doc to asst. professor position)

I would suggest looking for similar instructions for whatever organizations you are applying for funding from. You also likely should be working with grant support people at your new institution.


Recommendation letter from alumni I am applying for graduate school and one of the professors that I am considering to write my letter is an alumni from the school that I am to. Would this letter carry more weight?

If your professor did their graduate degree in the particular program you're applying to, this could help. The reason is that their letter can be more specific about the reasons you will succeed in that program: "She will be prepared to pass the quals in subjects X and Y immediately, based on her performance at Undergrad U., and will have no trouble passing the qual in Z at the end of the first year. Compared with the students who entered the Ph.D. program with me in 1992, she would have been in the top 25%." (This benefit can also apply when a recommender was previously on the faculty in the department you're applying to.) I do not think it matters so much whether current faculty remember your recommender personally. However, if the reputation or structure of the program has changed significantly since your recommender was there, their impression will be less relevant.

If your professor did only their undergraduate degree at this school, or a graduate degree in another department, then this will not matter or be noticed at all.


Why don't university courses report percentiles together with absolute grades? In any course in university, grades will be reported on an absolute scale, such as A+, A, B+, etc. Why don't these courses also report percentiles to indicate how hard the course was? This is very similar to what the GRE does. For example, I could be in the 95th percentile, which means that I did better than 94% of the students in the class. This would also eliminate the need to adjust grades to fit a particular distribution.

Actually there are many reasons that contribute to this, though as noted it isn't universal.
First, there is no real basis of comparison between courses, even in the same major, since the tests, unlike, say the GRE, aren't standardized, nor do they have enough data points for valid statistical inference. The numbers, if reported, would be essentially meaningless, though people would try to impute meaning to them.
Across disciplines the issue is even more extreme, of course. How "hard" is a Calculus class compared to one in Ethics? They can both be very hard, but it is impossible to compare them since the student activities are very different as is the basic pedagogy.
Second, and to me, vital, is the fact that introducing percentiles is a form of competitive grading that I find offensive. In my view, a student should be graded based only on their own, individual, performance. The typical A, B, ... grading scheme tries to capture this notion, even if imperfectly. If I get a C it should mean that I, individually, have some deficit, independent of what anyone else achieved or didn't. And note that the grading classifications are inherently broad and inexact as are all of the measures we use to determine grades.
One can do poorly on an exam for reasons other than lack of effort and learning. You might just have gotten too little sleep, or there is a family issue that requires your time and attention. Some instructors throw out the "lowest grade" to account for such things. Others have "fuzzy" boundaries between grade levels, giving the students the benefit of the doubt if they just "miss" a cut.
And of course, tradition plays a role. People know how to evaluate the general grades they see on transcripts from long practice. Even introducing A+ grades a few years ago caused disruption in this. Percentile grading has too much chance of being interpreted incorrectly.
Finally, implied by the above, percentile grades don't really measure "how hard" the course is, but something else. Someone has to be in the lowest percentile even if all students excel.
Don't look for completely "objective" ways to measure human performance and expect that it means exactly what the numbers seem to imply. Even Usain Bolt was sometimes slower than other runners.


Is it good to try to present every interesting paper I study? I am a Masters student in Mathematics. As part of my Masters project, I have to do independent study and try to "do" something: like tackling a problem of recent interest. So these days I am reading a lot.

However I also have a tendency of trying to present the things I know before my professors. I believe a lot in sharing of this knowledge. In my university there aren't too many lectures and people work on their own, so this social dissemination of ideas/information is not much in vogue. I wish somebody did that to me also as then I would be in a rather better position.

But is it stupid to try to expose the recent knowledge in my field? Now, when I say Mathematics, I really mean a particular subarea of Mathematics, where my interests lie. So please do not have the impression that I am spreading out too much.

I am just anxious that people will get tired of hearing my presentations if I hold such talks too regularly. But there are really so many things to learn, so many new things to do, how can one sit still without realising that life is short, and knowledge is progressing at an exponential rate? I often feel only I am the one really interested to know/do things, and others don't really share this spirit.

So, although I am reading a lot, should I try to present every small bit I have come across? Or only the major papers and recent breakthroughs? And what do you think about the frequency of such presentations?

Note, I have been told I am a very good expositor.

For me, -It really depends on who are you presenting to. Usually when I share something that seems interesting to my friends, usually they are happy but this won't suit to everyone. I would suggest to share a lot with people who is in same subarea of study with you or interested in your readings and do short presentations to others infrequently. The frequency of both of them will depend on your time and how interested people are.


Advice on applying for Economics graduate programs with a low GRE I took the GRE in August and scored a 301 and took it recently again and scored a 308. My field of work is primarily in Behavioural Economics so I plan on applying to specialized and general Economics grad school programs. I have a strong profile with internships in various organizations within my field and outside it as well as several publications and a good CGPA.

My questions are:

What are my chances of getting into good/top grad school programs in the U.S/UK?
Should I consider applying to places outside of the US that don't require the score at all?

Thanks in advance!

The only way to know is to apply to one or more programs. If your record isn't strong in some area you may need to apply to several different programs.

But for most institutions, no single number is likely to be an absolute block. You need to make your case. Why is it that you are a good candidate? Why are low scores not reflective of your ability? What can you add to a program you are part of? Some places may block you, but for those that don't, be ready to make your case through your other materials and especially in an interview. Showcase the positive.

I wouldn't take drastic action until I explored the terrain a bit, however.


Is it fair to use techniques I found on the web to solve my assignment? I'd want to get perspective on what I feel is an unjustified case of academic misconduct.

I am taking a mathematics subject and part of my assignment was to submit answers to questions given.

One of the questions I was unsure of what method I should apply, I searched on youtube and found tutorials on how to solve this problem. I should make it explicit the direct answer was not part of the video, however, using the same method I could substitute my values and get the correct answer.

I may be accused of plagiarism and apparently, my use of the video was unfair and plagiarism. I suspect it's because I used the same symbols which in retrospect I could have, should have changed however I still feel this is unjustified and comparable to applying the chain rule or any other mathematical principle taught through the increasingly powerful use of the internet.

Do you think there are ground to challenge this? I thought I was doing my due diligence sourcing methods, not direct answers.

Do you think this fair?

Whatever it was, it wasn't plagiarism. Whether it was within the rules set by your professor is another question. But, assuming that the rules permitted online research to answer the question, then that is all you did. You will have to judge conformance to the rules of your course.

If someone has accused you of plagiarism they are probably using the word incorrectly. That doesn't mean, of course, that you aren't without fault. That is for you and others to judge.

Using the same symbols in mathematics can hardly be faulted in any case, as many of them are standardized and used in the same way throughout mathematics. They might, however, have been a tip-off that you went outside the allowed bounds.

But, for your own educational progress, I hope you don't go to the web too soon to get such questions answered. Struggling with a problem expands your mind in a way very different from finding a solution or a solution framework. If you want to be a mathematician, you need to develop that skill.

Note that exercises given in almost every course, aren't given for the purpose of finding an answer. The professor already has the answer. The purpose is to help you grow your mental abilities. Work on the hard problems. If you want to learn more, work on harder problems.


Are there people who have done so much work before PhD that they get a PhD automatically? This question addresses why it's a bad idea to try to do a lot of independent work before PhD in the hope of finishing PhD quickly.

Nevertheless, are there famous examples of people who have done so much work before PhD that they get a PhD pretty much automatically (say, 1-2 years or less)?

The closest example I can think of is Mihai Pătraşcu.  After publishing several extremely strong results as an undergraduate, Mihai earned an MS in one year and then a PhD in one year, all in computer science at MIT.


Does all computer science research involve heavy usage of mathematics? I am starting my graduate studies in computer science this year and am confused as to what quality research (some new innovation or discovery) domain I would choose specifically amongst virtualization, distributed computing, containers, and/or blockchain.

My main issue is that I understand but am not interested in algorithms and their efficiencies. Similarly, I can understand my undergraduate level mathematics but that does not interest me. I have good knowledge and understanding of operating systems, virtualization, and containers concepts.

I have researched regarding this online and came to know people normally only compare out the efficiency of one algorithm over another in problems of memory sharing, process switching, and other similar problems; is there any other method or means to do something new in the field of cloud computing, containers or blockchain?

It would be quite helpful if any expert(s) from these domains could enlighten me regarding as to what type of research is currently going on in these domains and how research work in these domains can be done (while staying away from algorithms and complex mathematics).

Thanks to all those who answered and commented. Answering some comments and to give some more context to my question:

I am looking to select my research area from the broad domains of Cloud (virtualization and administration), DevOps methodologies and tools (optimizing workflows and processes), Containers technology (for example dockers and kubernetes), and Blockchain optimization ( I am aware this one would involve complex algorithms).
I'm not looking to write PHP scripts or JS (I know that is engineering). I personally dislike front-end scripting. Some of my projects include setting up a private cloud infrastructure for a company in an internship, writing shell scripts for CI/CD purposes and creating a custom RHEL ISO which already has preinstalled software (no, not templates). Basically, I am proficient in Python, bash shell, Java, C and have a good understanding of how OS, Cloud and IT infrastructure generally works. You can say I am interested in the data center or infrastructure optimization.

So, my question's main perspective is: I find it hard to believe that computer science research (at least development of new techniques, tools, and platforms) is impossible without deep knowledge of mathematics and algorithm designing (I may be wrong but that's the point of the question). Is there established research work or progress done in these domains that do not involve very complex usage of algorithms and mathematics like integration, differentiation and such. Please note, I am trying to avoid complex usage and modification of algorithms and its maths. I am interested to discover methodologies of such research (I am hardly able to find much on the Internet).

The sad truth is that you absolutely don't need CS for most practical programming tasks.

But without a CS degree, you will have nearly zero chance for the better programming jobs.

Furthermore, without a high-level math/cs knowledge, your mental skills remain significantly under-developed, compared to your own possibilities or to the ones who actually got this degree.

The sad truth is, that the job of a programmer, the ability to write a program what a customer pays for, is hard, but it is an absolutely different type of knowledge, like to know the math of the General Relativity. This truth is so sad, so catastrophal, that you will likely spent some decades of your life, whining on it. But it is the truth.

CS, its math, yes it is such a knowledge. For example, to understand, why there is no such thing as "best compressor" (more exactly: there is, but there is no program what could implement it), is a similarly complex and interesting knowledge, like cutting edge physics. But you absolutely don't need this skill to be a well-going programmer selecting freely between well-paying jobs.

This is how the world works. You can fight it, you can whine on it. I did both of them, decades long.... and I never became a scientist, only a programmer.

These fights and these tears are yet before you.

My advice would be this: learn that math, and get your degree. So:

you will fight
you will whine
you won't ever use it
and you won't be ever a scientist.

But

you will be a better man
you will be a smarter man
you will be able to choose freely between well-paying programmer jobs.

Believe me: if you do this now, you will be pride for that in your whole life. Despite the lifelong pain of your never reached goals.


The importance of credentials in pursuing an academic career in pure mathematics I would like to get some information and opinions of how the prestige of your so-called "credentials" helps or hurts in getting an academic job. I'm interested in this with respect to pure mathematics (I state this since I'm not sure if this is the same of all STEM subjects).

I guess that it is universally accepted the most important factor in one's academic career is his research. Of course, there are some more intricate relevant matters like a relationship with faculty of the department you apply to, success in teaching and the intersection of your research interests and faculty members' research interests.

However, the I wonder how pure prestige of one's credentials matter. Let me state it more clearly:

1) The prestige of your graduate school. If we have two candidates for a postdoc/tenure track with relatively equal research experience, but one holds a PhD from Harvard, while another from University of British Columbia, or University of Pennsylvania, or something else good, but not as famous and "shiny" as Harvard (or MIT/Princeton, for that matter), would a Harvard alumni be in a better position?

2) The fame of your doctoral advisor. Again, I advise you to consider how much the pure "fame" of your advisor matters, all other things aside, like the fact that a strong mathematician could help you mature as a mathematician too.
Would having a Breakthrough Prize in Math/Fields winner boost on CV in way that math departments would more readily accept you as a postdoctorial researcher/assistant professor? Of course, this question is not only about Fields medalist, it was just an example.

3) The prestige of the institution where you did your postdoc. While points 1) and 2) were also related to getting a postdoc position, this matters only to getting an assistant professorship/tenure track. Usually, the advice for choosing a postdoc is to find a suitable researchers with respect to your interests. But this question again asks you to look on the matter from a different angle: the one of how being a postodoctorial researcher in a high-ranked institution assists in getting a tenure track.

Again, I wish to emphasize that this question is not about how a quality of a graduate school, a strength of a PhD advisor and a research atmosphere in a postdoctorial institution matters to an aspiring mathematician with respect to getting stronger as a researcher and a teacher. This much I know.
I wish to hear some opinions on more "petty" stuff like "shiny", "glowing" names of departments or advisors, or relatively less famous ones.

First, the statement that your research is the most important factor only applies to research universities.  Other academic institutions have, for good reason, other important criteria.

Second, the first thing you should understand about academic hiring is that the hiring committee is unable to evaluate with a high degree of accuracy your research.  The error bars on the evaluation of your research are very large, and, particularly for more junior mathematicians, the noise can be almost as big as the signal.

Third, for junior mathematicians, a significant portion of the evaluation of your research comes from your letters of recommendation.  The quality and significance of your publications is much more important than the quantity, and we all know the journal reviewing system is very noisy, with a very large difference between the best and worst papers in a given journal.  Furthermore, your most significant work may not even have had the time to go through the peer review process.  You might think that the committee could try to directly evaluate your work, but in almost all cases, no one on the committee will have the expertise to do so, and in the remaining cases, only one person on the committee will, and they still have to convince everyone else.

Now to actually saying something about your question:

The fame of your recommenders is generally thought to be a noise reducing factor in evaluating your letters.  If a mediocre mathematician thinks you are good, who knows?  They aren't good themselves, so what do they know about being good or not?  If a well-known outstanding mathematician has worked with you and thinks you are good, then it seems more likely that you are actually good.  (In reality, I'm not sure how well ability in mathematics correlates with ability to judge mathematical ability in others, but I'm talking about how search committees tend to think.  There is at least some positive correlation, in that people who aren't mathematicians almost certainly don't have anything useful to say first hand.)

The places you do your PhD and postdoc(s) also likely put some floor on your ability, so they are also noise reducing factors.

Generally speaking, noise reduction on the bottom end helps your candidacy.  So going to a strong department and having a well known advisor doesn't just make you a stronger mathematician; it also makes you look like a stronger mathematician, or, at least, look less likely to be merely average or good.

On the other hand, search committees also recognize that people who went to less prestigious departments and had less capable advisors have had less opportunity, and more of their success can be attributed to them alone.  This might lead the committee to think the candidate is more likely to be successful in the future.  This means someone from a weaker program who can be a convincingly strong candidate might have an advantage.


How do people have so many papers in just one year? I am a 4th year Ph.D. student majoring in computer science. My advisors don't do anything for me unless saying that my ideas are really simple. I've got so many rejections for my papers, on the other hand, I see people who write more than 20 papers in a year. Can someone guide me on how is it possible? I cannot change my advisors and I should do it on my own.

A few remarks:

Those who write 20 papers a year typically write with co-authors. At this level of productivity, the authors often take over a part of the research and writing for the paper. More senior authors often do not conduct the experiments, but rather have a share in designing the overall idea developed in the paper and a part of the writing process. If you are really on your own and cannot join a team (e.g., take over a role in some other project work in your research group), then you can't expect this level of productivity from yourself. And ultimately, it's also not needed.
If your advisors dismiss your ideas as too simple, there are four possibilities:

the idea is actually quite simple, and others have tried it out and published about it
the idea is so simple that it's non-publishable
the idea is simple, it has been tried out, and the results were bad
your advisors are wrong

I've seen cases where the second case held, but later another researcher tried it as well and successfully wrote a paper about it.

About paper rejections at conferences: In my experience, the quality of reviews varies greatly between the conferences and the reviewers. Sometimes, reviewers take a lot of time to write precise reviews for why exactly they recommend a paper for rejection. These are very helpful reviews and should be taken very seriously. But then there are others in which for clear rejections the reviewer does not take the time to write up why exactly the paper should be rejected. Quite often, when the answer should be "the paper is overall not written well enough" or "I don't believe that the result is significant", the reviewer singles out something that is easily defensible objectively, such as a missing comparison against something else, missing references, or the like, and  bases their rejecting recommendation on that. The problem with these reviews is that while the reviewer is normally correct (but sometimes isn't), it doesn't help the author to address the core problem. Normally, your advisor should spot such reviews and tell you what to focus on, but if you get little help, that's not good.
If you see other published papers that are similar to your own ones, read them and then think about why they were accepted. What is the core contribution that the paper made? What is so cool about it that the paper was accepted, despite its inefficiencies? It may simply be that for the papers you are submitting, no program committee member has a good reason for why they should make a case for you that exactly your paper should be accepted. And then it is rejected even though it's not actually bad on any scale.
Solicit feedback from peers (fellow PhD students) if your advisors won't give it. Don't ask peers about feedback on grammar, spelling, and the like on your papers. Ask if they would be writing an "accept" review for the paper or not. Any why they would do that. Get feedback on the paper story and if the argument and structure is convincing.


Same review for Math Reviews and Zentralblatt I have been serving for several years as a reviewer for both Mathematical Reviews (MathSciNet) and ZbMath.

Earlier this year, I received an invitation for a paper for MR which I already reviewed for ZbMath. I dug up my old review and submitted it to MathSciNet without giving it much thought.

But there seems to be a pattern emerging. I received an invitation from MR for two more papers I already reviewed for ZbMath.

So here are my questions:

Do the editors of MR know/check who reviewed the paper for ZbMath in order
to find suitable reviewers?
What do I do about the double reviews?

My idea was to just refuse to write the reviews. But if the answer to the first question would be yes, then the editors know that I have a thorough review lying around. Just resubmitting this one would save a colleague from writing a new one.

The Math Reviews Guide for Reviewers addresses this explicitly:

  Reviews in other publications. You may find yourself asked to write a review of the same item for another publication. In general, the community is best served by reviews written independently. If you have already been asked by another publication to review an item, please let us know and we will transfer it to another reviewer.

So, if you have already reviewed the article for Zbmath, you should decline to review it for MR.  I didn't find a similar rule on the Zbmath side, but I would say the converse should also hold.

Also, per your agreement with Zbmath, when you submit a review to them, you grant them "exclusive exploitation rights".  So if you submit the same review to MR, you're infringing Zbmath's copyright.  I doubt they will sue you over it, but this shows it's actually illegal as well as unwanted.

In view of this, you may want to contact MR and ask them to withdraw your previously submitted review.

Evidently, one should not assume that the MR editors will check who reviewed the article for Zbmath in order to avoid inviting the same person, since they apparently failed to do so in your case.  (Another possibility is that they did check, but your Zbmath review hadn't been posted yet.)


What are the minimum contributions required for co-authorship In this answer  it is claimed that authorship is given away for "free" in some fields (e.g., obtaining the funding). The comments to the answer suggest that this is field dependent. I am looking for documentation from a field that suggests that authorship can be given away for "free". For example, the ICMJE has authorship guidelines that put a pretty high bar on authorship. Is there any documentation that suggests that supervising a student or getting funding is enough to warrant authorship?

Short answer: free authorship, also known as gift authorship, is a clear violation of research and publication ethics. The limit between “small contribution” and “no contribution” is not, however, easily defined; different fields put it at different levels.

I don't think the answer actually states that. It lists a series of contributions that are, in some field, considered important enough to warrant (in some combinations) authorship on resulting papers:

  they get grant money, they train you to use the lab, they train you to do statistics... or they might make suggestions for the research design, the main theoretical focus of the presentation / manuscript

All journals (or publishers) have policies or guidelines on how authorship should be determined. In all cases, it involves significant scientific or technical contributions to the work published. Authorship determination has to be weighted in each individual case, as no two situations are identical (and not simple rule of thumb can encompass all possible situations, as Peter Jansson highlights).

There are so many ways in which people can contribute to an intellectual work, such as a research project and academic papers. It happens that different fields of research have different habits in authorship determination, giving more or less weight to different types of contributions. My own background is in physics and chemistry, where authorship tend to be more generous that, say, computer science or mathematics. I'll thus argue two examples of what you (and some fields) may consider dubious basis for authorship, but which in my field would be considered fairly standard:

Getting funding. In this age, getting funding most often requires writing a grant proposal for a specific research program, with good and novel ideas, and convincing a tough crowd of other scientists (in a competitive environment) that your program is a good use of taxpayers' money. Thus, in most cases, the person who provides the funding also provides a clear scientific contribution: they identified an important problem to be solved, and provided a general framework for solving it. That's an important part of research! Identifying the right question to ask yourself is half of the job, it is known. (Yeah, I'm trying my hand at Dothraki style in academic context. By the way, thank you for reading so far down my answer.)
Supervising. Whether or not the supervisor actually provided the student with the research project in the first place, supervision implies guidance of the student, which is definitely a scientific contribution. The supervisor will, in many cases, provide a broader view of the field and ideas for related problems relevant to the research, scientific background, and advice on how to use one's research time most efficiently. All of that is highly valuable, and contributes to the publication.

(I've read somewhere “but the supervisor is paid for this, it's his job, so he shouldn't be awarded authorship” — that's plain stupid, pretty much everyone gets paid to do research, thus by that argument most papers would be authorless.)

In both cases, funding and supervising imply scientific contributions, which are the reason for authorship.


Can a psychology article be published without verifiable results? I wrote this article with a radically new idea what is the function of the sense of humor.

I sent my article to one journal. They said they won't publish because they publish only experimentally verifiable results.

In my article I propose several brain experiments, but they may provide only circumstantial evidence for my theory.

Also my cites list may be outdated.

I am not a psychology professional. Can this article nevertheless be published in a reputable psychology journal?

There is one piece of "meta-advice" I have for everyone whose goal is to publish in some journal: read it, a lot. You will learn for yourself what they will publish. For example, what the readers and reviewers of that journal expect in terms of result validation, what kind of jargon they use, and everything else that will help you understand where your work fits in. Then you can answer your own question about whether your manuscript is appropriate and developed enough to be published there (and know how to build from there to make it publishable).

This is really the main impediment in my view for "outsiders" who want to publish in a journal. Read and know the field as covered in that journal, and you cease to be an outsider. There will always be (unfair and wrong) biases of course, because this is a system of humans, but they are limited as the journal quality suffers from them.

I realize this seems like a lot of work, but look at it from their perspective. Publishing (and even reading) your manuscript will take precious time that might have been devoted to some other manuscript. You may perform this research and reading/writing as a fun past-time, but they do it as a job in which they probably never have enough time to do everything they want to.


Career path to professor with an engineering background in Germany I am in the final year of my master in mechatronics engineering in Germany, and I want to work as a researcher or a professor in a  university since i believe a professor/researcher has more freedom than an engineer within a company.

I don't have any experiences in the academic field, so I suppose I have to get some somehow.

What are good option to pursue as a career path in Germany to get a professor position at a university? Do I need to get a PhD? Is it better to become assistant professor on that path, or a research engineer?

Thank you

Your chances of becoming an academic researcher without a PhD are negligible. If you want to take this path, that is the first step. However, as far as I know long-term job prospects in German engineering faculties are not better than in other parts of academia (and maybe worse). Furthermore, many departments prefer if there PhD students have experience in the industry. You can certainly apply without such an experience, but competition is strong.

My advice is: Get an entry level job in the industry. If after two or three years you would still like to do research, apply for PhD positions at universities and research institutes. When you have your PhD, you can look for research positions in the industry or decide to stay in academia and start on the long hard road to a permanent position. If you then still want to become a professor (why would you? Usually you'd be a glorified manager and hardly do any research yourself.), you can do a habilitation. If you are extremely lucky (in addition to being very good, successful and a great networker), you'd might get a position as a professor someday. Chances for that are slim.


How does ibid work in footnotes? How does ibid work in footnotes?

Context

So I'm writing an essay, using footnotes for the first time. I was told that if I use the same source twice on the same page, then I should write "ibid", but this was not very clear. I was left with multiple questions (apologies if this ends up a duplicate, it seems like the type of question which might've already been asked but I can't find it):

Question

Where does the ibid go? In the superscript in text or on the footnote? In what combination?

How is it clear what the ibid is referring to? Say I have 4 footnotes, the fourth being an ibid, how is it clear whether the ibid refers to the 1st, 2nd, or 3rd footnote?

I've seen something about putting the page number of a journal - what about for websites, and videos? How does that work?

“Ibid” is short for the Latin “ibidem” meaning “in the same place.” It is used when referencing the same work as the immediately preceding reference and appears in the same place the reference usually would. For instance (assuming the below are a list of footnotes on the same page):

Isaac Newton, Principia Mathematica, p. 67. <— this should usually be a full reference, unless the full reference was already made in a previous footnote (which need not be in the same page)
ibid. <— same work, same page
ibid., p. 98 <— still refers to Principia
Gottfried Leibniz, Explication de l'Arithmétique Binaire, p. 4
ibid., p. 8 <— Now refers to the Leibniz text
Newton, op. cit., p. 83 <— another short hand; “op. cit.” is an abbreviation of the Latin phrase “opus citatum” meaning “the work cited” and like “ibid.” refers to the most recently referenced work, with the difference being it refers to the most recently mentioned work of the named author.

How this works with non-dead-tree media is highly dependent on the citation style you are using and probably not that well codified since “ibid” is fairly rare these days. But a decent approximation would be to replace the page number in the above examples with whatever you would use to locate the specific reference normally. For web pages, there might very well be nothing following the “ibid”. For video, you would generally include the time frame in the video referenced, e.g.:

Fight Club, 1:15:07-1:18:54
ibid. <— same film, same scene
ibid., 0:33:56-0:38:21 <— same film, different scene


PhD consisting mainly of programming work I'm currently a second-year PhD student, in computer engineering.
My research area is in computer graphics and virtual reality.

I currently don't have a specific goal or problem to solve, except generally to improve the state of the art in some regard. (i.e. develop a method/algorithm that gives better visual quality output than others described in the literature). According to my supervisor I'm supposed to find during my work a more concrete path to follow (like an existing method, and an approach on how to improve it).

So far I have mainly been doing programming/software development work, and developing a C++ framework for flow based programming. My question is if such a software development project can qualify as a PhD topic. There are plenty of complex problems to solve, involving time synchronization, guaranteeing that the system is lock-free, scheduling, etc. Here there is a clear goal: The user defines a graph for the data flow with various attributes (time windows, parallel execution, ...), and the framework does the necessary transformations, etc. to be able to execute it.

However it seems more like an open-source programming project than like a research work. I'm basically choosing for myself which features I'm adding to it, and how to implement them. Most of the time is spent programming and refactoring code.

What you are describing is a common situation in applied computer science.

There are many academic sub-fields where a good chunk of the work is a bit menial. For example, in robotics, testing a new approach may involve several months of work in the lab even if the new approach can be concisely described on one page. This is because roboticists care about stuff actually working - it does not suffice to construct new algorithms that work well in theory, you have to demonstrate that they really do - and a video taken in the lab is one of the best ways to do so. A lot of code needs to be written for getting all parts of the robot working together, and often research groups develop software frameworks to support their work. The frameworks themselves are normally scientifically not so interesting, but they prepare the actual scientific work. The situation in your research group seems to be similar.

So how does scientific work in such an applied field? (1) First of all, once the framework is done, the interesting scientific questions can be tackled not only theoretically, but also experimentally. Also (2), when you try to put together something that just works, you often realize that the current state of the art is insufficient in some aspects. You improve them to get your example running, and then you check if your improvement is sufficient for publication.

You seem to have been told that case (2) is how things are supposed to work in your case. But you may also want to ask your advisor about her/his plans on research work of kind (1). Often, these frameworks are built with a question of part (1) in mind. Note that it may also be that during the research work, a lot of technical debt has accumulated in the framework of your research group. Often, Ph.D. students are the only ones who are working on that as BSc or MSc students are not experienced enough, and postdocs and professors are too busy for this. That is often seen to be OK as long as there is sufficient interaction in the group such that Ph.D. students working on the technical debt can still participate in the scientifically interesting work of the research group at the same time.


Students who want to take higher courses early I'm a first-year undergraduate student (studying Pure Mathematics) at a university that has a mediocre mathematics department, in a country where there are no really good math departments compared to other countries abroad (as an example, there are only 2 known professors in my country that work on research in Algebraic Geometry)

Through what I've studied on my own, currently I have completed everything up to mid 3rd year courses at my university and I shall within the next 6 months/1 year have learned the content offered in all undergraduate honors (fourth year) courses and some graduate-level courses.

I however feel that the courses offered by my university's mathematics department are not at all challenging for me, and that is quite frustrating. I currently achieve 100% on every paper I write and I do not attend any lectures. Instead I opt to study on my own.

I spoke to the head of our university's mathematics department, explained my situation, and asked if I could be granted permission to take higher courses, and his response was essentially 'Who are you to ask me such a question?'

The difficult part is that there is almost nobody whom I can talk to about mathematics that I'm studying. It feels as if I'm working in complete isolation. The only people I can really talk to are some of the Masters and PhD students, who are perhaps the sole reason I even go to university to study.

I feel that this lack of competitiveness and being forced to go through courses that have content which I've already studied on my own is hindering my development. What's more, my university's math faculty does not have any official undergraduate research program, nor do faculty members interact much with undergrads (apart from lecturers taking questions from students of their courses).

I feel stuck, frustrated and depressed as if I'm being held back. In the US I've heard that it's fairly common for students to take courses at higher levels as they choose to do so, but alas I'm not in the US and don't have this option at any of the institutions in my country.

So in my situation, is there any advice one can give me? Also if there are any students who've been in the same situation as I find myself in, I'd be highly interested to hear how you managed to stay motivated and competitive.

(As a side note, I would like to mention that I learned what I learned not to complete courses but out of a genuine interest in what I was learning, it just happened to be that what I learned were the courses offered by my university.)

Also I do plan to move abroad for my graduate studies, if I receive a scholarship to do so, however if I don't, I won't have the necessary finances to pursue this.

My main problem is on how to stay competitive and motivated, and pushing myself in an environment that is not challenging nor conducive to research or to those who want to progress faster than the normally accepted rate.

You may consider:

Transferring to another South African school that would be of a similar level but more flexible about the upper level classes.
See if you can find a way to go abroad.
Stay where you are but try to get into those higher level classes.

3a. Try to get permission directly from the instructor.  Maybe you won't get credit for the class -- but if you are permitted to sit it (audit) the class, that's progress.  A good way to start working on this would be to visit the instructor's office hours with a couple of good questions that will show your aptitude, level of knowledge, and communication skills.  After getting to know the instructor in this way, you could then ask for permission to attend his or her class.

3b. Try going above your department head.

I personally favor method 3b as the preferred approach -- if it works.

Now, what to do about your feeling of isolation?  Here are some ideas for you to consider:

Do some tutoring/mentoring/teaching.  This can be rewarding and can help you break your isolation.
Take some classes in fields where one might be able to apply some tools of applied math or statistics.
Get started with one or more interdisciplinary projects with folks in other departments.
Interact with mathematicians in other countries with email, letters, etc.  Here's one way to get started with this: read some papers you're interested in.  Write to an author of one of the papers, to say that you read the paper with interest; say what you found most interesting; ask something.  You could mention that you would be very glad to be able to correspond with grad students.  Then see if a correspondence relationship develops.


any limit of putting too many videos/animations in presentations In the context of applied maths, physics and engineering. Videos/animations beat pictures and thousands of words, as is known to all. Is it bad to put too many videos/animations in a presentation? It's hard to define 'too' though.

If you have "too many", then, of course, it's "bad". This is more or less the definition of "too many".

How many is too many, is dependent on the situation and who you give a talk to. I have seen good presentations with videos illustrating a point and also short animations/memes which made the audience laugh and gave them time to breath after a long and heavy theoretical slides. (I don't like memes, but nevertheless I enjoyed those animations).

(Keep in mind that here are many mathematicians and a typical math talk has no animation/video, so you will probably get a lot of answers/comments  similar to "I've never seen a good talk with animations in my life". It would be best if you would write your field.


How to report on an academically required internship with a bad supervisor relationship I am a few days from completion of an industrial internship that is required for my Masters degree.  I have had a bad experience with the supervisor of this internship, who has insulted me several times during my internship period. He is mean, he gets angry very easily, he is bad-tempered and most importantly he is ignorant: he never knew what I must do as a trainee, it is me who proposes the tasks to him. Finally, now that I have finished the main task of my internship, he says it is useless.

Completing the internship and the degree involves reporting on my internship to an academic jury.  Given this bad experience, how should I handle my report?

In particular:

I do not want to give an acknowledgement to my field supervisor in my report: is this a bad thing to do? I mean, will the jury ask me why I did not write an acknowledgement?
If the jury asks about my evaluation of the company where I did the internship, should I be honest in telling them what happened, or should I lie and tell them everything was fine?

If the jury asks about my appreciation of the company where I did the internship: should I be honest in telling them what happened and that my advisor is too incompetent? Or should I lie and tell them everything was fine?

You should do the same as in any other case when a professional relationship goes wrong. You need to:

Focus on the facts. "The project was not going smoothly" is a fact. "We had communication issues, so I ended up delivering not what they wanted"  is also ok. "The project was going badly because the advisor is incompetent" is you trying to assign blame. Stay clear of that. You do not need to lie to the committee and pretend that all was great, but try to refrain from presenting your own interpretation of the events. It is understandable that you will want to make sure that the committee understands that the issues were due to no fault of yours, but by badmouthing your advisor (no matter how warranted) you are likely to reach the opposite.
Take the high road. If it is customary that students write an acknowledgement to their advisors, write a short, polite acknowledgement thanking him to allow you to  work in his team, if you can thank him for nothing else. Rocking the boat over something so minor seems unwise.
Whatever you do, stay professional. Acting out of anger and a lust to "get back" on your advisor for his insults will backfire on you.

Important Edit:

Based on your follow-up information:

(retracted - some racist comments as well as statements about unduly long work hours)

The fourth, maybe even more important point is:

If something really bad went on (like in your case), find out what the correct official action to take is. File an official complaint with your university, or even talk to a lawyer and have him look into filing a law suite (racist comments in the workspace are certainly grounds for a civil law suite where I live). Don't take a placebo action that does not hurt and does not help, such as not including him in your acknowledgements.

The other 3 points stay in place - even if something terrible went down, you need to stay professional and you need to focus on the facts, in your official reports as much as when you talk to your jury about the incident(s).


Why are research papers written in language that's difficult for undergraduate students? As an undergraduate student, I find it hard to understand research papers on any particular subject.

Why don't researchers use simple language for their reports, so that everyone would understand?

Update: I will leave this post as a general discussion on this topic. Feel free to edit question.

In short, because it is difficult to express something concisely, and precisely in language that any undergraduate can understand.

Conciseness is required not just because without it every report would be inconveniently long to write and to read, but because it would be harder to understand.
It would be harder to understand because the jargon neatly encapsulates a bundle of concepts (e.g. its definition and related properties) into a single concept.
And we can only be thinking about so many concepts at a time.

Consider the statement about the Stone–Weierstrass theorem:

A mathematician might say:

  Polynomial functions are dense in C[a,b] ⊂ (ℝ→ℝ)

To expand out the math, so that one does not have to know the notations on gets:

  Polynomial functions are dense in the space of continuous real-valued functions defined on a closed interval.

But still perhaps the word dense is beyond the understanding of an undergrad.

So let's expand it to not use that:

  For every continuous real-valued function defined an interval; then for any positive real constant one might care to define, a polynomial can be found such that for every point on that interval the absolute difference between the value of that polynomial and the value of the real function at the point is smaller than the constant.

So that is how much most space it took and how many more ideas one has to keep track of for that fairly simple use of jargon.
When thinking about such a problem rarely is the mathematician thinking about what is going on with the distance of points in a hypothetical polynomial.
They are just thinking "it is dense".

Now imagine expanding all the terms in the generalized version of the above:

  Stone–Weierstrass Theorem (real numbers). Suppose X is a compact Hausdorff space and A is a subalgebra of C(X, R) which contains a non-zero constant function. Then A is dense in C(X, R) if and only if it separates points.

(This last is a direct quote from the Wikipedia page on the Stone–Weierstrass theorem, the preceding quotes are not, though are to some extent paraphrases.)

Then to go the other point on preciseness,
There is a really high chance someone is going to comment on this answer saying that actually my statement is not quite correct, that I've not fully captured the definitions in my explanation

While, yes, every paper could repeat some introductory information,
then that would inconvenience any reader who is looking to find the core idea,
since it would be drowned in a sea of background material.

And you might say that "this answer is hard to understand, in the expanded form, you did a poor job at making it understandable to an undergraduate.",
and I'ld say "Fair enough; I'm not great at making things easily understandable."

And that statement holds for most other researchers too.
Not what most are good at -- it is why there are specialists in scientific communication.


Is it appropriate to guess page numbers of a book from its translated version? Short: It's easy to find bibliographical info, but how to guess page numbers?

I'm writing a paper in English. I want to cite certain book, originally published in French. It is translated to English and Russian. I own a Russian translation. I'd like to reference English translation. I don't have access to other language versions and I'm not going to purchase them.

Regarding your original question, if you have access to a Russian translation and you want to cite the English translation, but you do not have access to the English translation, then you really need to focus on citing what you have access to.

Now, I understand it turns out you do have access to the English version as stated in your answer but for future reference, you should not cite a version of a text you do not have acces to. The reasons are more than simply that you don't know the page numbers. It is possible that there is a problem in the Russian translation but the English version does not have that problem. Likewise the opposite could be true. Basically, the two versions could be slightly but meaningfully different. Because of this possibility, you should only cite what you have access to. Otherwise, cite through a third-party "Jones wrote in 2001 (cited in Simpson, 2005)."


Is it typical for a medical researcher to attend an industry conference? An industry conference in my field of research (medical) is being held soon. I am wondering is it typical for academics to attend non-academic conferences?

Several academics have been invited as keynote speakers but it is predominantly aimed at industry professionals. The talks sound interesting and relevant to my work and it would be a useful networking event.

There are no similar academic conferences being held that I am aware of. This is an area of research that is more active in industry.

However, the fees are very high compared to an academic conference. Is it normal for travel funds etc. to be spent on non-academic conferences? If I cannot attend are they other ways to make connections to industry? I am a postdoc currently.

I occasionally attend non-academic medical conferences, or attend the industry-focused sessions at mixed conferences. In my experience, these conferences are excellent for generating a couple things:

Contacts. Even if you want to stay in academia, knowing people in industry is occasionally useful - for example, if you want to be a PI, someday you will have students. Presumably those students willl need jobs.
Ideas. I actively refer to one conference I go to as a "hypothesis generating conference" - I leave it with a notebook full of ideas, and some followup emails to send.
Funding. Following from 1 and 2, industry contacts are a decent way to drum up industry funding.

That being said, they are more expensive to go to, and in my experience using travel funds for conferences where you're not presenting is a very hard sell.


Quantum Information in Math Departments I'm currently a graduate student in mathematics getting my master's degree. I am interested in a bit probability and partial differential equations, and, secondarily, a bit of mathematical physics; most likely quantum information theory. I'll most likely be moving to a different graduate program after completing my master's degree from my current institution , and I'm currently trying to figure out whether there are mathematics departments that have research groups in quantum information theory.
I believe I will want to stay in a mathematics department, as I'm not awfully interested in the experimental aspects of quantum information. I'm more interested in the mathematical aspects of the subject, and I'll definitely be applying with the approach where I'll try and cash on my undergraduate background in physics/quantum mechanics, and use my knowledge of math in topology, functional analysis, real analysis etc. to put it to good, meaningful use to solve inter-disciplinary problems.

However, I'm not sure whether there are a large number of math departments in the US that have research groups in quantum information? I know there's one at UC Davis,

http://qmap.ucdavis.edu/,

and I think the math department at UT Austin collaborates heavily with the physics/cs departments, so I won't be surprised if they have people working in quantum information over there.

I'm not, however, sure whether these departments/research groups are anomalies. It'd be great if someone could nudge me in the right answer to this direction? List of math departments doing quantum information? Or should I look at CS/Physics departments*?

*I don't think I will apply to physics schools because I am not really interested in the experimental aspects, and I don't think I can sum up the courage to take both the math/physics GRE this year, for which I will have to study from the scratch.

Sounds like Applied Math.  In terms of a specific PI doing quantum information*, I don't know which school.  But when you mention your course interests and wanting to collaborate with people on real problems that is applied math all the way.

Here is a list of top programs:  https://www.usnews.com/best-graduate-schools/top-science-schools/applied-mathematics-rankings  Not passing judgment, but list gets you started.  I would look at some of their webpages and reach out via email to one or tow and just start educating yourself on what they're like versus what you want.  Maybe do a visit if one near.

You could also consider statistics grad programs.  That is a wonderfully applied field and one where there is some connection to industry, the sciences, etc.

*Music on CDs as opposed to vinyl?


Can I upload a Book to Arxiv which I have already Published? A few years ago I published a book on mathematics and physics.  This book received positive feedback from people who read it, but was never widely read and has not sold that many copies.  At this point, I would prefer if the book were just made freely available as it is probably never going to make a huge amount of money anyway, so I was wondering if I could make some alterations to the manuscript and then upload it to Arxiv with a summary of the content and the intended reader?

Would this be copyright infringement as I suppose I have already signed a contract with the publisher?  I don't remember the details of the contract, but I suppose the publisher would not want me to do this, as it means people who might happen to want to read it will do a Google search and see that there is a free PDF copy, whereas the publisher would want to make money from the book wherever possible.  Is there something about Arxiv which sidesteps this copyright issue, as I am uploading a slightly different document to Arxiv which will exist independently of the physical book.

It's very dangerous to say "I suppose I have already signed a contract". This is legal stuff. The exact wording is important! If you have signed a contract, take it out and read it. What exactly did you agree to?

The odds are good you'll have to ask the publisher about whether you can do this. Even if the contract said you can't do this, it's possible they'll still say yes, especially if they've stopped actively trying to sell the book. Nonetheless, they might impose other restrictions - for example they might say you can only post the raw manuscript (i.e. no redrawn figures, no title & half-title pages if they were prepared by the publisher, no book cover [again if it was prepared by the publisher], no special fonts ...).

In any case asking the publisher is never going to be wrong, so I recommend doing that.


My (ex-)advisor is holding our paper hostage I left a PhD program in statistics last August after nearly four years in the program. The department graciously allowed me to finish out my Masters, so I graduated in December and have since started a new job in a related but unusual field for my degree. One of my reasons for leaving the program was my relationship with my advisor, which was causing me daily stress that I decided was no longer worth enduring.
About a month before I decided to leave the program, I submitted what was to be the first paper of my dissertation to a well-regarded journal in our subfield. I was first author and my advisor was listed as second author. In December (right as I was about to graduate with a Masters), the paper returned as an acceptance with minor revisions. There were only a half dozen or so reviewer comments, mostly minor.
I got to work addressing the reviewers' concerns, which didn't take long. My advisor, however, raised a major concern. He insisted that one part of the algorithm described in our paper was incorrect and that I should fix it. I asked him why he thought it was wrong and his reply essentially boiled down to "I'm convinced it is wrong". I stubbornly refused to do the additional work of another proof until he could identify where the original error was. This led to a very contentious Zoom call where my advisor told me that we should re-check essentially every part of the algorithm - because if one part was wrong, then perhaps everything was.
I eventually did the proof he had asked for and showed that I had been right all along. I sent the proof to my advisor and asked him to read it so that we could submit the paper. He said he would, but now almost two months have gone by and I have not heard from him. My previous experience with him leads me to believe that this radio silence is intentional and that he has not just forgotten about the whole project.
My options are:
A) Do nothing and (presumably) let the paper go unpublished. Given my career trajectory, it is not hugely important to me that the paper be published, although it would be nice to see my name as first author.
B) Nudge my advisor for a response, potentially provoking a demand for more work that I consider superfluous. Dealing with my advisor any further will almost certainly cause me a great deal of stress (or relationship is very strained).
If you think I should take option B, how can I be clear that I do not wish to put much additional work into the project and believe it should be submitted now that I have answered every reviewer comment? Should I make an ultimatum, or try to offer some sort of compromise?

If you really don't care about the paper then A seems ok as long as the paper isn't published without you.
But you could nudge the professor and then decide what you want to do. If you get unreasonable demands then you can back away which should prevent the paper being published (ethically, at least). But it is possible that your worst fears won't be realized and you have a simple way forward.
But I would save any ultimatum for a later round after you hear a response to a request to submit. You want to be the "reasonable party" in any conversation.


Should I put funded projects/grants on my CV where I am not PI? I helped writing some project/grant applications. In those applications, I am not the PI and not a funded member. Still, I am listed as an external collaborator, or a person of interest, or potential hire. So, my involvement is as "co-author" of the application (although only the PI is listed) and as "person to be involved". I guess this is the case of several other researchers.

Is it usual to put those instances on an academic CV? If so, how?

In my mind, this will depend on how much you contributed to the grant, and what stage of your career you're in. I'll also ignore things like the NSF or NIH requiring reporting research support even if you aren't the PI for biosketches and the like.

If you're a graduate student or (depending on the grant) a postdoc, it's reasonable that you wouldn't be the PI, because you can't be the PI by institutional rules, or because in the current funding climate, or with the scope of the grant, etc. there's just no way a postdoc-PI grant is going to get funded. Never the less, putting it on your CV shows that you're thinking about funding and participating in the process, even if you aren't heading it up. It's the grants equivalent of being a middle author on a paper as an undergrad.

What's important though is, as with every element of your CV, that you be able to cogently talk about what it was about, and how you contributed to the writing of it. It's one thing to say "My supervisor was the PI, but I did the bulk of the writing and planned out the grant" and something else entirely if you were just along for the ride.


Is the expression "Deputy Head of Research" correct? In my university department there is a professor who holds the position of Head of the department, and then there are also several Deputy Heads, who are in charge of different management areas  —more precisely: Research, Teaching and Infrastructure. Notice that, in our case, the Head and the Deputy Heads are not necessarily 'senior professors' or 'full professors'; they can be also (young) 'associate professors'. They are in fact elected by popular vote within the teachers belonging to that department.

My question is just this: What is the right way to refer to the Deputy Head who is in charge for the Research matters of the department?

Research Deputy Head?
Deputy Head for Research?
Deputy Head of Research?
...

Actually, I am not sure whether the term 'Deputy Head' is right or not, in this context.

I would appreciate your feedback on this terminology question.

"Deputy Head of Research" is someone who deputises for the "Head of Research".

By contrast, "Deputy Head for Research" (or, sometimes, "Deputy Head (Research)") is someone who deputises for some generic "Head" in the specific area of research.

"Research Deputy Head" is unidiomatic and sounds like a command "go and research the deputy head" rather than a title. The "research" coming first somehow stresses it as a verb rather than a noun.

Even more common than any of those constructions, at least in my part of the world, is the simpler "Head of Research".

In practice, there will be a definitive answer to this question which you can only find out by asking within your university.


Research advice needed: How to make a move from web development to PhD research? I am a web developer reasonably proficient in PHP and front-end development. I had completed my Masters (by coursework) more than 6 years ago and have been working as a web developer. My Masters' grades weren't very good (pass in average with few distinctions and credits). When I did my Masters, rather than focusing in one area, I was pretty much experimenting with different subjects such as natural language processing, multimedia, visual info processing, distributed programming, etc 'cause I wasn't too sure what direction to take.

I contacted few research supervisors after completing my Masters but didn't hear anything positive from them. Then I pretty much gave up and started pursuing career and moved into web development.

I am not sure how to go into research now and whether it is even possible for me. How do I prepare myself?

Here are a few suggestions (not necessarily in this order):

Read up on the latest research in your area(s) of expertise and interest.
Narrow the research interests down to a few and make contact with the academics involved - make contact with them, asking good questions about their research.
Contact the admissions offices of your selected universities, explain the situation truthfully - put an emphasis on the experience you have gained through your employment, which is now an area of expertise, despite your masters going in many directions.
In your readings, you should be able to find an area that is in need of more research, where something new can be contributed.

Remember, your situation is different than it was when you completed your Masters, you have several years of specialised work experience behind you now.

Good luck.


Where can I find information about upcoming special issues in a field of study? How can I find information about upcoming special issues related to a special field of study? There are good websites for upcoming conferences but I could not find any place to search for special issues.

In addition to the two sources mentioned by William, I can add professional societies or their equivalent. It is usually these that organize meetings that result in special issues. It is rare (may differ between disciplines) that journals themselves, unless they somehow specialize, provide open special issues around a theme. Usually, it is then by invitation, or papers emanating from a workshop or symposia etc.

Hence, looking for especial issues may be a dead end and you should be looking for activities that lead to such issues.

As a final note, the term special issue signals an unregular issue in a scientific journal open for submission of manuscripts. Many conferences issue proceedings but then the prerequisite is usually attendance at the meeting and presentation of the paper there.


Masters in US or (Masters + MPhil) in UK I am an engineering student studying in India, and I will complete my Bachelor's in Electronics Engineering in June. I am looking forward to pursue a career as a researcher in Machine Learning, Signal Processing and Computer Vision.

Which is better :

a 2 year master's degree in the US.
or a 1 year master's degree  + a 1 year MPhil degree in the UK.

What I think is the advantage of the UK approach is the following :

Since the Master's course in UK is mostly coursework based and I don't have a formal background in computer science, it would be much more efficient if I learn't the relevant concepts first, before starting research.
After the Master's course where I would have completed all the required coursework, I could spend a year in a more research oriented environment (during the MPhil degree).

As a result, I think the UK option is more suitable for me (it would be a more structured approach) as a student having completed his Bachelor's degree in Electronics engineering, and wishing to pursue research in a more computer science oriented field.

What I think is the advantage of the US approach :

I plan on pursuing a PhD degree in an institution in the US, because (please correct me if I am wrong) the chances of fully funded PhD's are much higher in the US, than in UK. Thus, it would be easier for me (from the admissions point of view) to study in a Master's and a PhD program, both in the US.

Basically, what I am asking is :

What are the merits/demerits of both the approachers, from the point of view of :

Me as a researcher in the future
Admissions to a PhD program

In terms of PhD admission prospects, both the UK and US have top quality schools with international renown. However, if you're planning to study PhD in the US, having a masters in the same country can help in creating more relevant connections between other researchers, and therefore affecting your chances for PhD admission.

In terms of program structure, there are differences like you mentioned. However, even US institutions start off with a more course-heavy workload and gradually move on to a more research-focused program (second year). Also, getting familiar with basic research concepts and ideas early on (as with US programs) is not necessarily a bad thing and you shouldn't worry much because there are many cases like you who have come from a non-CS background. If you get accepted, the department is well-aware of your background and potential capabilities

EDIT: Empirically, UK institutions offer less funding options especially at the masters level. Even at the PhD level, most of the funding I've came across are offered as partial awards that don't cover the full tuition and living costs. It is still possible to obtain full funding at a UK institution, but overall, funding is usually an important factor in deciding your place of study


Does one always accept good funding (Marie Curie)? I have recently started a postdoc in a prestigious US university, making a leap between scientific areas. Right before starting it I have applied for a rather competitive European fellowship (Marie Curie Individual Fellowship), also in this new scientific area.

Today (5 months after the application) I learned that I got the fellowship. I have not actually expected it and I was applying more to get experience in writing grants, to apply seriously a year or two later (since in general I would like to end up in Europe in the long run). I honestly do not feel like a really experienced independent researcher I pretended to be in the proposal. Also, knowing the things I have learned during my new postdoc, if I were to write this proposal right know, I would write a very different one.

Now I have to choose whether to accept the fellowship and learn scientific maturity the hard way learning new science and managing new funding in a new country simultaneously, or to stay in the US and develop my knowledge of the new scientific area more calmly (and have time to publish something in a reasonable journal). I have some other more mundane concerns about moving from the US to Europe right now, but they are less crucial.

I was told before that when one applies for permanent positions, there is a rather hard rule that on never rejects it, if offered. In the sense that if one rejects it once, one has zero chance of getting another one in future. This funding I am talking about is not a permanent position but it is still a rather big thing, as I far as I understand.

So finally, I have two questions:

Is there some more or less firm "rule" about rejecting major fellwships/fundings, like with the permanent positions?
Overall, does the idea of rejecting a respected fellowship on the grounds of not being confident enough sound reasonable, or typically one is supposed to go ahead and ride the rare wave of opportunity?

There is a difference between good funding and prestigious funding. The Marie Curie fellowships are prestigious funding, but not really good funding. They pay a lot in salary (in some fields it could be twice what you are making in the US) but don't offer much else. The duration of fellowships are no more than 24 months, I believe. There is no funding to hire a PhD student or even an RA or funding for the actual research. There is no guarantee of a job at the end. The Marie Curie fellowship is nothing like a permanent position. Again, it is very prestigious, so congratulations.

Apart from the salary (which I am guessing is higher), what does the fellowship give you that your current supervisor is not (e.g., how long is your current contract and can it be extended). This is really the type of thing you need to talk to your post doc supervisor about.


Should a reference letter for a student always be positive? I am finding the following moral problem, and possibly people with more experience could help me.

One of my Master students (who recently finished his master studies) is applying for PhD positions. Despite my good scientific opinion about him (and his master thesis research), my personal opinion is starting to change. He is a good student, but not an exceptional student. This means that he can of course prepare a good PhD. The problem comes when I start suggesting places he could apply (and you know, getting PhD funding is not straightforward), he has many obstructions: things like 'I do not like this country', 'in this country phd's are of 3 years and with teaching', 'The subject of this phd is the same area of my master, but not directly related', and things like these.

I am happy to help, but this is becoming tiring. As a master thesis advisor I am the one who is expected to write the recommendation letter.  After having these encounters I do not feel I should write a very positive letter.

How should I manage this situation?

The general answer is yes, a reference letter should always be positive.  If one cannot write a positive letter for a student, one should decline to write a reference.

In this case, the student is having difficulty, perhaps even internal conflict, in choosing programs to which to apply.  Captain Emacs has it right in the comments; that's not relevant to his ability to complete a Ph.D. program.  If repeated requests to suggest programs are becoming tiring for you, say, "Repeated requests to suggest programs are becoming tiring for me.  You are an adult.  Find and select the program that you believe will suit you best.  I've already suggested those I believe will best suit you."

While you are having that discussion, set a limit, perhaps three to five, on the number of recommendation letters you will write.  Applications are usually kept to a reasonable number by the fact of application fees, but sometimes students get carried away anyway.


A career path for synthetic biology I am thinking about a career in synthetic biology, but I am not sure what route should/needs to be taken. I don't want to do technician work--I want to be involved in the planning. Y'know, the exciting stuff. :)

[By 'planning' I mean things like, for example, looking at symptoms (assuming we are looking at a person), pinpointing underlying causes, designing a molecule that stimulates X, modifying it to avoid inadvertent binding to Y, etc]

I'm wondering whether I should go for a Master's or a PhD (or is a Bachelor's enough?)

It's a young field, so I'm having trouble finding this kind of information online. Any help would be much appreciated!

Generally speaking, if you wish to be involved in designing, proposing, and interpreting experiments, you need to be a PhD. (This isn't specific to synthetic biology.)

That's not a hard and fast rule. There are certainly Masters and Bachelors out there who will propose experiments and do analysis, and any organization worth their salt will consider intelligent proposals for experiments from technicians. However, a PhD is usually taken to be the sign that someone is capable of designing and executing an independent research program. -- In some respects, that's what a PhD degree is. It's a certification by your peers that you are able to intelligently propose and carry out an independent research plan that is sufficiently novel. (Cue grumbling from older PhDs about the dumbing down of modern degree programs and lack of intellectual rigor these days.)

So that's where the line is usually drawn. The PhDs design the experiments, and the Bachelors and Masters (and lower-ranking PhDs) carry them out. The Bachelors and Masters may do some routine post-analysis, but ultimately they hand the results back to the PhDs to interpret and plan the next round of experiments. It's not that you can't find positions where Bachelors or Masters are significantly involved in planning and analysis, it's just that if you want your primary responsibility to be planning, you should probably shoot for a PhD.


How to cite a paper as shortened first author name and year [Ste2002]? The way I'd like to cite papers in my work is 3 characters of the last name of the first author + year of publication without spaces, 'et al.' and comas.
I'd like to use Citavi, as it has convenient Word add-on, but I haven't found how to shorten last names there so far. After all, if it is possible in another program, I will give it a try.

Such citing style was chosen to enhance reading experience, as reader can relate to the cited paper much easily by the last name and the year of publication and trace it throughout the document. This style is yet shorter, than patterns officially available in Citavi.

There's an easier LaTeX solution (compared to another answer):

\documentclass{article}
\begin{document}
\section{First section}

First statement \cite{gascuel97}, and a second statement \cite{sokal58}.

\bibliographystyle{alpha}  %Sets [Ste2002] bibligraphy style
\bibliography{sample}      %Imports bibliography file

\end{document}


Ways to get free and legal access to research papers as a researcher I’ve discovered that website like ResearchGate offer the possibility to ask the paper editor to provide his paper for free. Many are collaborating.

Are there any other ways for researchers to obtain free access to papers?

I always use the following methods to get many inaccessible papers.

Open Google Scholar.
Search the title of the paper.
Click see all versions (you can see many places where the same paper is available)
Check one by one whether they are downloadable

Another method, I always use when I really need an inaccessible paper, is just to write an e-mail to the corresponding author to send that paper. My experience is that I have always received the paper in a return email.


What are the requirements for admissions to a masters degree in computer science in Canada for an international student? I am a double major in Physics and Computer Science from an underdeveloped country. I would like to apply for a masters in computer science in Canada. What requirements do you think I should fulfill?

Currently, I have a CGPA of 4.0 (and I have only four additional semesters to go), although that CGPA is likely to go down by a small margin over time.

You should check the minimum requirements of the program you are aiming to apply.

But, generally speaking; you may need some proof of language skills (depending on whether your language of study in your BS was English or you are native English speaking, you may not need this document) and official report of your grades and GPA.

Some universities may need a statement of purpose and depending on the entry requirements, you may have to sit an entrance exam or an oral interview via internet. Some universities may require a report of GRE score which you should prepare for separately.

Also you need to find a way to pay your tuition fees and living costs. If you are not self-funding, it is a good idea to check the scholarships which you are eligible for (some of these scholarships are reported on the website of the departments and universities).


Do faculty members get additional compensation such as bonuses in industry? Do faculty members get bonuses similar to industry such as cash bonus, stock bonus, profit sharing, commission sharing, and tips? Or only for teaching more courses?

Since most faculty members are employed by non-profit institutions, there is little in the realm of corporate benefits that directly carries over for all faculty members.

However, there can be some carryover if faculty have intellectual property which has been licensed through the university to a corporation. In such cases, they usually share in whatever revenues the university receives from the corporation.


Is there any benefit applying before the deadline? From what I have seen, academic position usually have 1-2 months deadline.
I know that for non-academic positions if a suitable candidate is found, the position may be filled in advance.

Does applying one month or some weeks before give particular advantages? Is it risky to apply close to the deadline?

Surely country dependent. For Germany: There is no difference in applying early or just in time. The review process for all applications does not start before the deadline is passed. I you are one day late you may or may not be considered - I think more often than not you application will not be considered if too late.


Are mathematics REUs absolutely limited to undergraduates? I had an amazing time at my REU (Research Experiences for Undergraduates) last summer.  I would really love to do another one this year.

Problem is, I am about to graduate, so I will technically not be an undergraduate this summer.  I do intend to continue my education in graduate school in the Fall, and have been admitted somewhere.

I've been told that I should just kick back and relax this summer so that I'm fully unwound for grad school, but I don't have any money to travel, all my friends will have left for their grad school already, and there's really nothing that would stress me out more than sitting around and doing nothing for three months.  I love to travel, make new friends, and learn cool stuff, so I think doing another REU would actually be the perfect way for me to unwind.

At my last REU, we had a student who had graduated that year and was about to go into a Master's program.  It was rumored that she had omitted/lied about this on her application and the admissions people just didn't look into it carefully.  I don't know if this is true, though.  It seems possible that the program staff simply felt her application was strong enough to warrant making an exception - after all, she wasn't going to grad school yet.

  Is it possible to be admitted to a mathematics REU the summer between undergrad and graduate school?

If not, would offering to go without pay (for only room and board) make any difference? What about REUs in physics, or compsci, or other sciences which might want somebody with a math background?

I quote from the NSF REU guideline (emphasis mine):

  Eligible Student Participants: Undergraduate student participants
  supported with NSF funds in either REU Supplements or REU Sites must
  be U.S. citizens, U.S. nationals, or permanent residents of the United
  States. An undergraduate student is a student who is enrolled in a
  degree program (part-time or full-time) leading to a baccalaureate or
  associate degree. Students who are transferring from one college or
  university to another and are enrolled at neither institution during
  the intervening summer may participate. High school graduates who have
  been accepted at an undergraduate institution but who have not yet
  started their undergraduate study are also eligible to participate.
  Students who have received their bachelor's degrees and are no longer
  enrolled as undergraduates are generally not eligible to participate.
  For REU Sites, a significant fraction of the student participants
  should come from outside the host institution or organization. Some
  NSF directorates encourage inclusion in the REU program of K-12
  teachers of science, technology, engineering, and mathematics. Please
  contact the appropriate disciplinary program officer for guidance.
  Within the framework of the basic eligibility guidelines outlined
  here, most REU Sites and Supplements further define recruitment and
  selection criteria, based on the nature of the particular research and
  other factors.

So this means that (a) your host will not be able to receive funding for you from the NSF if s/he accepts you into the program (b) on the other hand if you and/or the PI of the grant is able to secure funding otherwise, there's generally no rule saying that a student in your position cannot be involved in research in some way.

You will need to individually contact the REUs you are interested to find out whether they'd be willing to grant you the leeway.


How to mail a professor informing that I am interested working at different place I have asked a professor for summer reading project(he agreed). Later, I was also selected for summer internship programme a top institute in the country, how do I tell the professor that I don’t do the summer reading project and want to go there?

The professor is a very chilled guy in person to the people he knows. I have barely talked to him. He knows that I exist on earth and that’s all. I don’t want to sound like a poser. Please help me.

These sorts of things are best handled face to face, not by email which is less personal. Go see him. Tell him about the situation and that it is an opportunity that you don't think you can pass up. Thank him for his help and interest. Let him know that your project will need to wait or be abandoned for you to do this internship.

If he is doing his job properly, then he will support you. And the face-to-face can actually strengthen your relationship for the future.

You can, of course, say all those things in an email, but it won't have the same effect or impact.


Google Scholar intitle and OR search combination I would like to use the following type of search in Google Scholar:

virtual reality and retention intitle:"Visual cues" OR "cueing" OR "signal" OR "signalling"

Thus, I want to search for Google Scholar entries that have "Visual cues" OR "cueing" OR "signal" OR "signalling" in their title. However, this search does not seem to work as intended as it leads to more than 40,000 results which clearly do not all include the keywords in the title: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=virtual+reality+and+retention+intitle%3A%22Visual+cues%22+OR+%22cueing%22+OR+%22signal%22+OR+%22signalling%22&btnG=.
Is there a different syntax to achieve my desired search?
Thanks in advance for your help!

virtual reality and retention  intitle:"Visual cues" OR intitle:"cueing" OR intitle:"signal" OR intitle:"signalling"


How to transition from lectures/exams to research/thesis? So far, University was mostly lectures, seminars and exams.

The scope of problems to solve was usually very narrow and the necessary knowledge was taught in the lecture or seminar.

Solving a given problem in a seminar or exam was done by picking the right tool from the toolbox that one gathered over the year. There was often one specific workflow/formula/strategy/etc. to solve a particular problem. Sure, some of them allowed for some tweaks to get the job done faster, but for the most part the goal was the solution that the problem was asking for. There was never a need nor time to explain the reason to choose a certain method.

Now doing research for thesis, things appear to be different. There's one bigger problem to be solved. There's also some paper to be filled with text about the solution I came up with. I could just solve the problem and document what I've done. However, I got the feedback on previous smaller "publications" that such a document should not just be a manual to understand the solution, but to show the research that was done.

Research seems to have the inherent property to be open ended and unpredictable. Whenever I make a decision, I have the nagging doubt that I should explore more/all the choices and compare them, so that nobody asks me at the end why I haven't tried that other option, too. Previously, the reason to solve a problem in a certain way was because I was taught to solve it that way and arriving at the solution was good enough.

For research, that seems to be different. As the existence of a solution is never guaranteed, it's not so important to actually arrive at a solution, but how to get there. An attempt at solving the problem (or any sub-problem) or really doing anything at all might fail or not, which begs the question why if failed or not. How do I make an educated decision about when to dig deeper and when not to? How do I choose the right level to explore variations? (for example, when to just modify some parameters of a program, use a different mode of the program, choose a different program altogether, use a different computer[, set everything on fire, throw it out of the window and start from scratch])

It's not possible to try everything and making the right decision on what to try and what not to try seems to be a matter of (a lot of) experience, which I do not have at all. How do I make those decisions? Should I just follow my gut feeling and try things, because even if they fail: that's a result? But what if it turns out that even trying those things wasn't a reasonable thing to do in the first place? That would be bad then, wouldn't it? How to get out of this dilemma?

Firstly, don't worry. This anxiety that you describe is extremely common and completely normal. You're right that it stems from the transition from very tightly-constrained styles of work to something that is much more open-ended. You are half-way there - you have recognised that you have many different possible paths to follow. But I get the impression that you are still thinking in terms of pass and fail. You talk about finding the "right decision", and that a given approach "might fail or not", but research is not so black-and-white.

Of the many different paths that you are considering, it's not that some of them contain death-traps where you will be forever doomed, whereas some are shining paths to glory. It is likely that you can make a success of any of them (just so long as you don't stay rooted to one spot for too long...). Even a "failure" to find a solution is useful. In the words of Thomas Edison:

  "I have not failed. I've just found 10,000 ways that won't work."

You might find inspiration for something else, or you might just be able to rule out one method - that is still progress.

You also talk about whether to pursue a single issue in depth, or take a radical change of direction. Both those approaches are valid, and it's up to you which style you prefer. Eventually, with experience, you will start to get a bit of a nose for what sorts of approach work best for you, and maybe be able to head in a slightly straighter line through your research. But even professors are not perfect in that regard. Until then, as @user37208 suggests in the comments, your advisor should be a great source of advice here and can help you to break down the problem into more manageable chunks, and give you a bit of direction when you feel you are wandering around without success.

You may be thinking "that's all very well, but at the end of the day, my thesis will pass or fail." While that's true, this will depend far more on how well you can explain what you have done, and whether you can demonstrate that you have made reasonable efforts to tackle one or more problems, than on whether you have actually found "an answer" or not.


Is it ethical to have results in your PhD thesis that are not strictly yours? In some disciplines (such as theoretical computer science), it is typical to have papers where you have co-authors. Especially when the set of co-authors is large, and work is being done at different universities, it is possible that person X works on one part, and person Y on one part. Thus, perhaps you wrote and came up with one result, and another result was the result of the work of someone else. Finally, you publish that paper together.

Then, in your PhD thesis, you typically have a list of publications. From what I've seen, the author usually declares what is his/her contribution was for each publication, but this is quite vague. For instance, it might say e.g., "Publication 1 is joint work with X and Y, and partly written by the author".

So consider a particular result that appears in a paper where you are a co-author as a PhD student. My question(s) are:

Is it ethical to include that result in your PhD thesis, supposing that you did not contribute to the result? Perhaps you only proof-read the theorem.
Does it make a difference if you couldn't have come up with the result, or don't deeply understand it? Maybe professor Bigshot Superstar came up with it, wrote it, and it is using advanced machinery with several technical details.

It is nice to just say "this is joint work with Bigshot Superstar" to make yourself look good. I see it being done, but it makes me feel uneasy. On the other hand, while it seems honest, it can potentially hurt you to say "the author did not contribute to Theorem X".

It may be good to report results that is connected to your reports in your thesis even if you did not directly contribute to it as long as you attribute main contributor of the result from an ethical stand-off. But this would not be applicable if the concerned result is to play a major role in your dissertation. I which case, IMO, you try to do something more or different to make up for the major result.

Apart from my views, the your thesis advisor ought to be the best person to clarify this particular doubt.


Are there style guides for lists of figures / list of tables? I am currently writing my thesis and I will add a list of figures and a list of tables.

Are there any style guides how to / not to write the text shown for each entry in those lists? (e.g. I could imagine that somebody already wrote a list of common mistakes)

Example

This is a part of how it currently looks like:

Hence some questions are:

Should title capitalization be used?
Should it be a sentence?
Are braces ok?

As I have not seen this before, I'm not aware of any guidelines how to write those. I think it should be written in such a way that a person who has already read the work can quickly find the table / figure again.

I don't know of any style guides, but you should first check with your university, as they may have a thesis manual of sorts for you to follow (mine does, and part of my job is to make sure students follow it). Usually students will likely follow a journal format in their field to format the captions. Again, contact the appropriate office at your university to get help with formatting the captions, if they have guidelines. Otherwise - almost anything goes, and you should be consistent in how you format the captions.