How much detail to include in first email to potential PhD supervisor? First, I must mention that I found  these questions helpful:

Prospective PhD contacts potential supervisor but receives no answer after 2-3 emails, what to do?
What to do when emails to a potential advisor are not replied?
Should résumés be attached in a mail to a professor?

Yet, I am looking for more precise answers to the questions below.

I plan to apply for a PhD in Computer Science this year in several countries, mainly Europe, Australia and Canada. I am looking for a PhD  with funding. As far as I know, I should contact potential supervisor as a first step. However, I am not sure about how much detail should be included in this first email. Specifically, with regards to the first email, I would like to hear advice on on the following:

Generally, how much detail should I provide?
Should I ask about the chance of getting funding?
Should I send documents or only if s/he asks for?
Statement of purpose/motivation, what is the right length? Is s/he ready to read two pages about every applicant sends him/her email?

Taking into account that this is the first email to the potential supervisor and he might spend only 10 seconds scanning it, What is right answers for the questions above that make the supervisor starts a discussion rather than sending negative response or even ignore the email?

My answer is going to extend up this earlier answer to a similar, although broader, question.

Some background: I have worked with two pretty well-known professors in Austria and Switzerland, and can provide some insight into how they tend to hire. I assume other professors have similar MOs, but not every person is the same, so your milage may vary.

Indeed, for both of them, the first step towards starting a PhD is to send them a short informal mail stating your interest in joining their group. Your challenge is to get the professor interested despite him reading maybe a 100 mails a day. You can already see why a two-page text has a 0% chance of being read, same is true for an attached CV or an elaborate research proposal - you need to convince in maybe 10 seconds. Your second challenge is to separate yourself from the dozen or so other people that are trying the same every week, mainly coming from universities in the far east.

In that light, here are answers to your questions

  Generally, how much and deep details should I provide?

I would go for none, honestly. Discuss concrete research ideas at a later point, when the professor has shown interest.

  Should I mention anything about fund chances?

God no.

  Should I send documents or only if s/he asks for.

Yes.

  Statement of purpose/motivation, what is the right length? Is s/he ready to read two pages about every applicant sends him/her email?

Forget it. None of the professors that I worked with is interested in those formal application documents at any point during the process. They will either want to skype with you or have one of their senior staff skype with you, and then you would explain the things you would write into a SOP. To be clear - I have received a PhD student, a postdoc, and a senior postdoc position without ever being asked for a SOP or letter of motivation. Those are required only if hiring is done by a committee, e.g., for faculty staff.

Here is an example of a mail that might work on the people that I know.

Dear FIRST-NAME,

I am currently looking into options for getting a PhD. I have looked into your work on IMPORTANT-THING-PROF-IS-WORKING-ON, and I would be really interested in joining you on this line of work.

I have recently graduated from XY with a degree in YZ, and I have a background in SOMETHING-RELATED-TO-THE-ABOVE. I have done internships at BIG-NAME-A and BIG-NAME-B and already published X papers on SOMETHING-RELATED-TO-THE-ABOVE during my masters.

I would be happy if we could discuss matters further via Skype.

thank you in advance,
YOUR-FIRST-NAME

YOUR-WEB-PAGE

Note the informal tone. This might be a personal preference of the people I know, but an informal mail is significantly more likely to be read by both of my professors than a very formal one. Further, note that it will be required that you have some measure of achievements that the professor can relate to - graduating from a university that the professor maybe has never heard of alone will not be enough to get him interested. Already having published and/or having done internships at well-known companies (well-known also to the professor!), especially those that are known to have competitive selection schemes (e.g., IBM), helps a lot here. Do not bother sending your GPA etc. - people in Europe tend to not be interested in grades in my experience.

Another thing that might help with the people I know is work on open source projects (e.g., being a committer or committee member to one or more Apache projects, having a well-maintained Github page with interesting tools and Gists, etc.), but this may be mostly because I work in software engineering (and people that know how software is built in real-life are very valuable to us).

Another important topic is english language - if you cannot speak / write english well, let the mail be proof-read by somebody who can (according to the way the question is written, this should not be an issue for the OP, but this may be relevant to other readers). Mails in terrible english are almost always discarded immediately.

Finally, the above sample contains a link to a web page. Have a personal academic web page. This is the place where you would put a good picture of you and all your academic achievements (papers, CVs, research interests, internships, links to open source projects you contributed to, industry projects that you worked on, whatever). Make it look professional and pretty.

Note that this mail still has a high chance of being ignored. In that case, give the professor a week or so and then write a a one-line reminder as a reply or forward of the original mail. If he does not respond after that, move on. Then he is just not that into you.


Is there national/ethnic discrimination against Asians in U.S. graduate school admissions and in university faculty hiring tl;dr: please skip to the last paragraph.

I am currently an international undergrad at an US university, studying math. I am currently thinking of going to graduate school and becoming a university professor after that.

My dad thinks that there must be some unforeseen and implicit racial/ethnic/national discrimination against Asians in U.S. higher learning and that I must therefore invariably be more studious in learning.

However, today's America is more diverse than ever, every university have non-discrimination policy, and collge faculty hirers are in general (I think, at least) educated people. Also, based on my interactions, no one in my college seems to be biased against racial minorities/different nationalities. So I am thinking that there wouldn't be much national/racial discrimination on graduate school admissions and in university faculty hiring, especially as my major is math, which is one of the objective academic discipline. I also plan to do a career with pure math and not on industrial/applied math.

I am perfectly fluent in English and can communicate perfectly like a native except for a almost non-existent accent. I am also very aquainted with American culture.

Of course, I know that there still must be some implicit national/racial diacrimination in job hiring process in non-academic sectors (e.g. companies/restaurants) despite there being laws against it. But since universities are places were nondiscrimination is highly encouraged and there are lots of international scholars, I think my dad's claim is highly exaggerated.

I believe that my current status as a citizen of South Korea, which is a close ally with U.S., shouldn't negatively affect my image in graduate school admission/university faculty job hiring.

I found some articles like this one but I think this is an exception to a general rule.

Long story short:

Is there national/racial discrimination against Asians in graduate school admissions and in university faculty hiring/promotion in math (and/or Physical Sciences in general)? I am asking for anything in the United States (i.e., no answer needed for other countries). "Discrimination" for scholarship doesn't count,  -- nor does undergraduate admissions!!! I am looking specifically for an answer about math department or physical sciences. A general perception is a preferred answer rather than specific instances, though that too is good. Answers are wlecome from those working in the admission/hiring process. Also, lack of communication skills frequently attributed to international scholars doesn't count as racial/national discrimination in my question.

EDIT: In reply to the replies below, I am well aware that any sort of unjust racial/national discrimination is prohibited whatsoever in the U.S., and I am well aware that the mainstream media and the general consensus of the people is that any sort of unjust discrimination is absolutely bad. I've attended an American high school and watched tons of American news and TV. However, I am merely asking a professional view (that is not speculative, i.e. someone who's been working in the area for many years) to what extent some people's implicit biases against Asians seems to negatively impact grad admission/prof hiring. Of course, having been in U.S. I know that no one would say "we're gonna hire this white guy over this equally qualified Asian guy just because of race." Also, being in U.S. for many years do not always count as state residency, as I am not a permanent resident.

There is quite a bit of academic research on university entry and race, mostly in US universities, so if you are interested in learning about racial discrimination in academia, this would be a good place to start.  The phenomenon of discrimination against Asians in academia is well-known and has been identified regularly over the past twenty to thirty years, both in academic literature (e.g., Tsuang 1989, Wu 1995, Wong and Halgin 2011, Kim et al 2011) and in the press (see e.g., The Economist 2015).  The Asian-American Coalition for Education claim that there is widespread discrimination against Asians in academia, particularly in the elite Ivy-league schools, and they provide references to a number of articles and books discussing this issue.

This issue has been studied in quite a bit of detail by the economist Thomas Sowell in the context of his research on affirmative action (an overview of his ideas on the subject is here and his recent book on the economics and politics of race is here).  Sowell argues that affirmative action leads to discrimination against Asian applicants, as a consequence of this group having a higher proportion of applicants with high grades/skills.  Since Asians are the "model minority", Sowell argues that the use of affirmative action in academia tends to involve a raising of the bar for entry for this group, in order to try to avoid their "overrepresentation".

Anyway, this is a big subject, and a lot has been written on it.  Some users on this site may be able to give their own anecdotal experiences, but I recommend you examine this broader literature.  The links I have provided will get you started, but there is also plenty more on the topic.

UPDATE: There is presently a major lawsuit against Harvard University for alleged discrimination against Asian applicants.  It is alleged that Harvard admission staff have systematically down-rated Asian applicants on their "personality" in order to achieve racial balancing, consistent with the university's goal of racial diversity.  @BlueRoses: If this is a topic that interests you, I cannot think of a better example than for you to watch how this legal case plays out.


When is it proper to add someone to your research paper? I am an undergraduate working on a research project that is going to be published. My research adviser wasn't completely able to help with a certain portion of the research, so I contacted another professor (in a completely different department) at my university who was more than willing to help.

It seems that this other professor is going to be providing a huge amount of help. Should I offer inclusion in the paper? Should I bring this up with my main adviser and/or should I be upfront with the secondary adviser?

You should discuss the issue with both faculty members.  I would bring it up with your primary advisor first...if only for linguistic reasons (i.e., the meaning of the word "primary").

When you say that the project is "going to be published", do you mean that it has already been written and accepted for publication?  (If not, how do you know?)  In general it is a good idea to discuss issues of coauthorship as early as possible.  If you are already writing the paper it is on the later side, and if you have already submitted it then it is very late (but maybe not too late).

That's all I can think to say on general principles.  It depends a lot on the field and what kind of work has been done.

tl;dr: As an undergraduate, you can't know the subtle expectations regarding coauthorship in your discipline.  So err on the side of graciousness and inclusivity.  The worst that can happen is that you get a "Aw, how cute: he thinks I want to publish with him" type of reaction.  If so, you will definitely not have offended the faculty member and you'll probably engender a lesson about how publication culture works in your field: no problem there.


How to express about getting informed about a specific position I am going to prepare a cover letter for postdoc position. I was informed about this position by my Phd advisor. I am looking for a proper statement about how I was informed about such that position, which must be express usually at the initial paragraph of a cover letter. May you please tell me how would be a good statement for this type of info.

I don't see any reason to express where you learned about a job advertisement, except if it was emailed personally to from whoever you learned about it, and not widely distributed. However, usually these are mass emails sent to a large number of people (recognizable by several factors). In that sense, I don't see any reason why you would need to state how you learned about the position - unless you want to make a point out of it, i.e. make it clear to Prof. X who advertised the job that their good friend Prof. Y (or maybe the very famous Prof. Z) suggested to you personally that you should apply, which hopefully reflects positively on you in the eyes of Prof. X.


How to motivate people to participate in a survey, can I include a call for participation in a paper? I am designing a system which is based on text sentences of a specific domain, so that no corpus exists. In order to evaluate, which types of phrases occur, and how often, and to not be biased by my own input, I need theses sentences from other people. Thus, I created a Google forms survey.

Despite posting on relevant mailing lists, offering a significant shopping voucher for a random participant and having my twitter call re-tweeted hundreds of times, I only received about 50 sentences, mostly from my colleagues. While this allows the development to go ahead, I fear that it doesn't give me a picture as accurate I would like of the typical input, especially the rarely used phrases. Also I expect it to negatively impact the credibility of my paper.

My questions:

How can I motivate more people to take part in the survey?
Is it OK to put the URL of the survey in the first paper and hope that this attracts more participants for an improved version later on or is that seen as unwanted advertisement?

Putting a call for participation in a survey in a paper is a bad idea for several reasons:

You would be putting an ephemeral request in an archival publication that people may be reading a decade from now.  That's just plain gauche.
It is likely to be difficult to get appropriate human subjects approvals
Scientists reading your paper are a highly distorted sample population.

As a more effective alternative, may I suggest looking into Amazon Mechanical Turk, which has gained a lot of popularity in recent years as a means of recruiting study participants?


IELTS Listening Complaint due to coughing I took the IELTS today and during the listening section and at the end during the last passage a student started constantly coughing. This made us lose track and miss the last part.

The center was playing the cd on a small portable cd player. When we went to complain the management of the center was shady and gave us 4 different explanations on what would happen if we decided to file written complaint each one nastier than before.

The last explanation they gave is that if IELTS investigates this and finds you are at fault then they will cancel this test and not give you a retest or refund. Hence we will lose out $300 and not get a test score.

I am not sure if this is true and was wondering if anyone can verify this.

(I am adding this last line because this question got put on hold for some reason of it being too general. I think that's invalid and this will prove very resourceful to everyone who takes this exam. So I am stating the country where this occurs making it general)

Please see this applies to all IELTS exam taken in USA where it's not standardized. It may apply to other countries as well where the exam is not standardized yet.

So I tried getting this resolved but was not successful. The center is responsible for the actions that need to be taken and IELTS (British Council I believe) will not participate in the process. The center decided that my inquiry was not valid and released my results. This obviously makes no sense to me. Also, I was told that it was my fault that I chose a center which did not have headphones so I have to bear the consequences according to IELTS. I hope this helps someone in the future pick a better center with headphones or a decent speaker system for listening.


Do the authors have to cite or make comparisons against works on domains such as arXiv? I'm reviewing a conference manuscript (computer science) and i found 2 other recent methods related to the same problem which were published on arXiv.
So, i think it is highly recommended to compare their method to those ones. The arXiv papers also claimed to beat the state-of-the-art, but on different datasets, so one cannot compare them based on the reported numerical results.

So, should/could i say that it is a weak point that the authors have not included/used those recent relevant works in their introduction or evaluation basis?
Or they do not have such an obligation as those papers have not been yet published in any proceedings?

I think this question is ultimately about standards within particular fields and societies. In math, where arxiv has been central for decades, it would be odd to overlook highly related examples, and using your language it's reasonable to assume authors would be obligated to check. In psychology, where I work, preprint repositories are still fairly unusual, and authors are not expected to review these sources.


Software/App for electronic research notebooks I want to keep a research notebook for my computational "experiments". Basically, I should at least be able to write text and attach images like plots. Other nice features to have would be

linking to past experiments/pages
latex equations
uploading papers, or other urls
being able to transfer data
dating and version control
open-source tool

I am already familiar with trello and tiddlywiki. Trello is good for attaching stuff and organising tasks, but I need a notebook where I attach a plot, write stuff around it, attach another below it. It doesn't have a paper or canvas. Tiddlywiki is a little painful for attaching pics and equations, the file bloats, it seems I am keeping a blog.

What is a good, free electronic notebook tool for research/lab work?

For the last month, I have been using Gitit for this purpose.  That link goes to a live demo where you can try it out.  It satisfies all your requirements:

It's a wiki, so you can easily make links between pages.
It's built on pandoc, which understands TeX and uses MathJax to render it (it technically renders a subset of TeX, but it's a pretty substantial subset)
It's actually a Git repository, so you can upload anything you want to it.  Or just put your figures out on the web (via figshare or a public Dropbox link) and link to them.
Same as 3.
Again, it's Git.
It is open source: https://github.com/jgm/gitit

As a bonus, you can put it out publicly on the web if you want (or just run it locally on your machine).  I run it on an internal server at my University and my students and post-docs use it to.  Thus it's a convenient way to share information as well.


Failing students: Avoidable or not? One college lecturer often does not care about failing his students, another does. Say we are talking about a Calculus I class.

A. One fails students because they simply do not achieve the minimum grade set by him and/or the university.

B. One fails students because they cheat or break rules or something.

However, for point A, there are reasons that can be talked about.

He might not be a good teacher. For this, either he improves his teaching, which more often than not means he needs more experience as he has minimum capability of teaching (he is not a school teacher any way), or the faculty just need to find replacement as this lecturer cannot deliver.
The materials are just too much for some students. How do we handle this?

a. Should the materials be reduced, which then it will not make this class a Calculus class, since some materials are omitted?

b. Should the faculty accept the fact that these students fail? What if for ALL students, this Calculus class is too hard?

c. These students passed the admission tests for the university entry, and they came to learn. Should they blame or change the admission process to get a better group of students? This can be done in the future, but what if this fail of students is happening now?

d. Should the lecturer raise the average grade of the class so that some, if not all, students pass the course? Or, just by lowering the minimum grade at the end of the semester? Won't this affect them in future subjects?

e. Should he just let them learn as much as they can without setting any expectation or minimum requirements and grade them based on how much they have improved?

f. In conclusion, in which part does he adjust? The materials (future), teaching method (future), grading system (future), the minimum grade, or just let them fail as there is nothing he can do without changing the grades, even after giving them second chance exam and still fail, even after also giving them more tutorial classes?

EDIT: To add more consideration, let's say the class attendance is really good. Practice quizzes are given more than once. In my department however, almost all lecturers agree that our students are just weak compared to other universities, since the good ones are usually going to those universities. I wish not to agree with this, since I believe there is something a lecturer can do to help improving his students. However, students rarely come to a given tutorial class. Also, based on the admission data, accepted students were based on ranked list, not passing grade. I have tried making more detailed syllabus. Some students (very few) succeed, but others pass courses with very low grades, and this happens to every lecturer including me. I'm relatively new to this department and it looks like other lecturers just raise grades eventually (it would be bad for the department otherwise) and mind their own business later, such as doing research etc, without even giving tutorial classes. I am refusing to follow it but it looks like it'll be easier for me to follow this culture..but nah!

This is a very philosophical question involving the overall education system, the area you are living in, the selection process of your students, the culture in your university, and, and, and. Therefore I assume the question will be closed, soon, even though this is a common problem which needs to be discussed.

Sometimes I feel we are in a similar situation at our university since we are accepting candidates with lower grades as incoming students. Some of them are not really qualified for studying at all, and it is just helpful for them to reflect this as early as possible, e.g. by early tests etc. Last year I had two students which quit after three weeks "because they did not expect they have to invest so much time in studying".

The only thing you can do is to decide to work with the students you have. Changing the selection process is difficult, the application behaviour can not be influenced too much, and sometimes the students with bad grades in school can show a great performance in their studies! So don't invest too much time in improving the incoming student's quality.

The next important step is: You are having a curriculum (and later on job profile) whcih requires certain pre-requisites in later courses. As a faculty, you should discuss which is the minimum level the students should have after your course - and this should set the level for passing the exam. It could lead to a reduction of the material, or you can classify some material as "advanced" and other material as "must have". Do not go below this level - the students will like it in the beginning, but they will have trouble in their later studies and in their working place. It's better to force them to do the course again. Be clear about this from the beginning, and if possible tell everyone in advance your expectations and - more importantly - whatfor the material is needed afterwards.

Regarding material and teaching methods I would like to reference to the field of didactics - many universities are having courses for improving the teaching style - take as many of them as you need! It helps a lot, and you are meeting local peers which are in a similar situation.


Do international students have a lower chance of getting accepted in STEM-fields PhD programs at US universities? The reason that lead me to ask about this is the following paragraph I found on this page (some guidance written by a STEM-field professor at CMU for applying to grad school), he says,

I'm not a U.S. citizen -- how does that affect my chances?
Unfortunately, if you are not a U.S. citizen and you don't hold a green card, your chances for admission are very significantly reduced. One simple reason is that we get an overwhelming number of applications from overseas. The extra work and time we spend on cultural acclimation and language skills for these students means that we can only accept a few of them, and of course this is a very few out of a huge application pool. If you already have a degree from a U.S. institution, that helps considerably with this issue. Also, it is more difficult to obtain funding for non-U.S. students, and so further increases the effort required to bring them here. Historically about half of our department's graduate students are non-U.S., although that proportion tends to be closer to one quarter in my research group.

The bold italics are mine. I personally find the "cultural acclimation" argument utter nonsense, and the "language skills" seems even more nonsensical, since almost all programs require quite good TOEFL/GRE test scores. So I suppose my question has two components really, and it concerns PhD programs specifically:

Did you experience difficulties funding a student in your department (STEM field) solely because he was a non-US citizen? If so, does this influence your decision of admitting non-US citizens?

Does your department has a specific quota of non-US citizens to be admitted?

Edit: In light of the new statistic I found, it seems absurd to say international students (i.e. non-US citizens) have a hard time getting accepted, especially in ECE. I think the professor's remark above doesn't reflect the bigger trend (he is with the ECE department at CMU), and his research group (where the proportion of international students is about 25%) is more of an exception to the "rule".

Since you can't change the situation and suddenly discover your US citizen parents, you can only apply for positions and make your best case. As I mentioned in comments, the quotes are from an individual who is clearly expressing an opinion, not the results of research.
Yes, you will find people who will mark you down a bit or a lot based on your circumstances, but you will also find people who take a broader (and IMO, wiser) view that applicants are individuals who should be evaluated on a relatively fair basis.
But, you will find that competition in some fields and in some universities is intense and you have to make the case that you are an excellent candidate with many expectations of success.
Note, that some parts of the article that you didn't quote are more general. The writer is correct that funding in the US for doctoral study is normally not a problem as nearly everyone has a position as either a TA (most common) or an RA. This provides sufficient funds to live (if a bit humbly) and pays all tuition and fees. While the funding may not come from the professor, it is almost always available to anyone who is admitted and who requests it.
Visa problems may be intense at the moment as is the difficulty of travel, but those are outside what can be advised here.
What matters, much more than trends, however, is what it means for you as an individual. If you present an excellent application, showing hard work and past success and people are willing to write you good (great) letters of recommendation, you will have a chance.
But don't apply to too narrow a range of institutions. Give yourself flexibility and backup.


Meeting professor for the first time to discuss ideas So I have been talking to a professor in quantum game theory from a unversity in my city whom I have never met. We have been going back and forth on mails discussing ideas. I did alot of research and presented my ideas to him through mails. He has asked me to come meet him to further share the ideas face to face and introduce me to one of his colleagues. The main purpose of me contacting him was that I wanted to work on some research with him and probably find employment along side him as an RA or along those lines. I am really nervous to meet him. I feel that I may fumble while discussing with him. Could you please help as to what sort of discussions usually take place in meetings such as mine and what i should expect. Would the discussion be extremely technical that would test my knowledge to the core or will it be a casual and light exchange of theoretical ideas.

Even Houdini can't provide a to-the-point answer to this question; because guessing about the flow of a conversation sounds tough.

But, as this situation has been occurred, with high frequency, among the applicant and the potential supervisors, you might be eager to consider below subjects, will which be, probably, taken into account, within the target discussion.

The professor has already heard your ideas. His/Her tendency to hear
them, face to face, is maybe due to his/her propensity to assess your
tone and realize how confident you are about them. Wrap up your
self-reliance and put away any hesitation within talking about the
ideas.
You had, noticeably, claimed about any potential abilities within
your emails, such as programming capabilities, acquaintance with any
specific scientific theme and etc. The professor might ask something
about them, trivially, to find out any proof for your claims.
Evaluating your mental status and personal reflections would act as
an important factor for the professor. He/She will focus on your
excitation, manner of presentation and the temper. He/She would maybe try to
trap you by anything just like bombardment by questions to see
whether the anxiety will overcome you or not. This case often plays
an important role for professor's final assessment upon you, as
he/she must decide about the gratifying characteristics, presented
by the applicant, to work with him/her, efficiently, within long
graduate-level studies.

Based on my own experience and the fellows, have who crossed this bridge, the main context would be within the aforementioned stuffs.

Good luck


ppt presentation for postdoc position interview I have to prepare the presentation about my previous research experience for 20 minutes. I don't know what I should include, how big and how  much specific it should be

The first suggestion: Ask the people interviewing you. There's nothing wrong with asking if they would like a deep-dive or a broader research context, or what kind of audience you'll be drawing from.

In a more general sense, if you Google academic job talks, you should get a fair amount of advice. In general, the goal is to present your previous research in a coherent narrative, establishing who you are as a researcher so they can put you in context. Tell a story, and supplement it with the results of your research. As it's only 20 minutes, my guess is they are intending it to be fairly high level, rather than a very detailed exploration of any one result.

As for "How Big"...it should be 20 minutes, and as big or small as you can cover in that time.


Writing two papers on two different topics with the same data = two protocols? I am a Ph.D. student and a member of a large interdisciplinary team of researchers working on a health related topic. We are shortly to commence data collection related to our topic of interest with a sample of around 250 participants.

I have two very different research questions in mind that I would like to address with the same data set.  Q1) relates to the accuracy of the instruments used and Q2) to the association of our variable of interest with a range of psychosocial factors.

Being highly aware of the potential minefield that is salami slicing, I am being careful to be very transparent about my process. So I have written a protocol in which I set out both of the two questions and list all of the instruments collected. Consequently, I have had (entirely fair) feedback that this makes the protocol a bit incongruous and confused.

So, I'm wondering at this stage what I should do? Write two protocols, one for each question? Abandon Q2 and stick by a rule of one data set = one research question (this doesn't seem to me to be very efficient given the costs of doing research)? What of all the longitudinal data sets out there that have been used hundreds of times by different research groups?

Would appreciate your advice, thanks!

Data sets can, should and are used many times over. Your two very different research questions appear to be candidates for two different research papers, since the one is methodological (instrument accuracy) the other is not.

Even if you keep them very separate in your protocol, lumping them together in one document may indeed be detrimental.

It also appears to me that the methodological question should be worked out first, since the conclusions/findings from this front will qualify positively or negartively the findings related to the other question.


Publish book chapters without giving away the rights I'm currently writing a book where I, during the writing process, would like to try to publish some individual chapters (more or less unchanged) as standalone articles . Once I've written all of the chapters, I would then like to be able to do retain the full rights to my text even though it would heavily overlap with articles published in different journals.

Are there any kind of code words or licenses that I could look for in journals when searching for potential places to publish my book chapters in order to be sure that I don't give away the rights to my own work in this regard? I realize that I could ask the staff of individual journals directly, but I would like to know if there's a better way to scan potential journals to find suitable ones.

You could give the publisher of the article a non-exclusive license (meaning, you retain the right to grant more licenses to others).
Or, you could negotiate that you retain the right to publish the article later on in a book.
Note that if the book happens to be your thesis, many (but not) publishers have copyright transfer agreements that allows you this particular reuse. I guess they got tired of allowing PhD students to reuse the paper for cumulative (stapled) theses.
And you could check your local copyright law: in some jurisdictions you retain rights for secondary publication.
E.g. in Germany you retain the right to use your manuscript for secondary publication under certain conditions (1 year embargo period, non-commerical secondary publication, the paper was written mainly by public grants).
I'd guess if you approach the same publisher about the book who also published the papers, they may be more open to license the papers for reprinting in the book.


MS CS with thesis after online MS CS Due to some family conditions during my undergrad days, I could not focus completely on my studies. As a result, I have a mediocre GPA (2.7-3.0). In order to overcome this, I have decided to enroll for an online terminal MS CS program which I intend to complete within 1.5 years.

Provided that I am able to excel in the online course, is it possible that I can leverage the degree to get admissions to a top 10 MS program in computer science with thesis option?

Certainly it is theoretically possible, but it may not be possible in practice. There are two issues to consider, even beyond your unknown performance in the online degree.

The first is that the probability of any single candidate getting in to a "top ten" program is effectively zero. There are too few slots and too many well qualified candidates. The competition for entry is intense. Most of those candidates will have near perfect academic records. You will need some "edge" that will appeal to any admissions committee. An online degree may not be that edge.

Second, an online degree usually gives you little personal relationship to professors and, probably, very little feedback on your work. If the online degree is largely "passive" (videos, readings, and exams), then no one really has an idea of your potential since you interact with them so little. There are a few programs that are different, of course, such as Open University UK, which does provide tutors for the students, but even there, little interaction with professors.

That doesn't mean the an online degree is bad for you and may be one of your only options. But if you set your sights on a very narrow target for it, then it will be very difficult to hit that target. Think about how you can widen your goals or, alternatively, choose a more effective path to them. Say a path that lets qualified people see your potential and give you great letters of recommendation.


What to do after PhD? I obtained a PhD in Microbiology. I have some papers and a competitive CV. I would like to continue in Academia or to try industry.

Is the normal path to find a postdoc job in naturejobs.com? I'm overwhelmed by the high number of jobs that are being offered, I just need one!

In the sciences, it is almost expected if you want to go into academia that you will do at least one postdoc.  (In some disciplines like astrophysics, you might even do more than one!)  There are a lot of different job boards out there for finding a postdoc, but your best source (assuming you are still on speaking terms) is your thesis advisor.  He/she will likely have friends and colleagues looking for a postdoc.  Those folks will then know the background you are coming from and likely put you on their short list.  Good luck!


Is it common to feel anxious when reading papers? I am a graduate student, and I often feel strangely anxious when reading papers. I was wondering whether the same is true for other people.

There are basically two scenarios where I feel that way:

a) I start reading up on a topic and I find that people make outrageous claims, are methodologically unclear, seem to be warping data to make it fit to their premises or their conclusions, or (which mainly happened when I had to read philosophy for my BA) make highly disputible claims backed up by verbal shows of authority more than good arguments; or even if they have good arguments, they start by making their claims which makes me very anxious about having been wrong about something all my life. To sum it up, I get physically anxious by reading papers which defend ideas contradicting my own. What makes me clam up is a mixture of the discomfort of having something you think is wrong be boldly proclaimed in writing, possibly without ever having been contradicted, and the discomfort of engaging the possibility of being provably wrong.

b) Once I've done a lot of reading and I believe that I have spotted an error that has been made in the past and that is being passed on from paper to paper, I usually try to tackle that error and prove it to be wrong. Now when I read new papers, there's a feeling of dread because either they might again argue for the position I believe is wrong, but might be so convincing that they prove me wrong, in which case all work I've done on my idea so far is wasted, or because they might have spotted the error too and laid it bare, in which case all work I've done so far is wasted too.

My question is: Is this feeling of dread, anxiety, or clamming up inside usual when reading papers on contentious points, and if so, are there any good techniques for avoiding it?

It's good to be passionate about your studies.

It's not good to suffer to the extent that you are.

The objective view of the academic problem you described is that getting better at analyzing logical arguments is good training for you in your studies, regardless of which argument turns out to be valid in the long run.  However, it sounds like you have a hard time detaching your self-esteem from the question of which one is valid.

There is a way to desensitize, and develop more detachment.  It's called Exposure and Response Prevention, and it was discovered as a treatment for Obsessive-Compulsive Disorder.  (Important note: I am NOT expressing an opinion as to whether you do or do not have OCD.)

Here is an interesting quote from an article about OCD by Fred Penzel:

  In the 19th century, OCD was known as the "doubting disease." OCD can make a sufferer doubt even the most basic things about themselves, others, or the world they live in. I have seen patients doubt their sexuality, their sanity, their perceptions, whether or not they are responsible for the safety of total strangers, the likelihood that that they will become murderers, etc. I have even seen patients have doubts about whether they were actually alive or not. Doubt is one of OCD's more maddening qualities. It can override even the keenest intelligence. It is a doubt that cannot be quenched. It is doubt raised to the highest power. It is what causes sufferers to check things hundreds of times, or to ask endless questions of themselves or others. Even when an answer is found, it may only stick for several minutes, only to slip away as if it was never there. Only when sufferers recognize the futility of trying to resolve this doubt, can they begin to make progress.

I'm not sure your particular trigger of discomfort could be found in any of the books on self treatment for OCD.  I used Amazon Look Inside to check one such book with very positive reader reviews and it seemed to me that it would be quite annoying for you to try to work with.  However, the description of the technique and what happens physiologically might be useful for you.  It's in Chapter 4 of The OCD Workbook: Your Guide to Breaking Free, by Bruce Hyman and Cherry Pedrick.

I have written about my family's experience with ERP in this answer.  (But note, that question is quite different from yours.)

Here is your description of what triggers your strong reaction:

  When I hear people talking loudly about things I (like to pretend I) know something about and their opinions sound just wrong to me and it would be inappropriate to go over there and have a discussion. Or listening to authorities on the radio when I disagree with them. I seem to hate disagreeing with people without having a chance to tell them so.

If you want to work on this with ERP, on your own, Step One would be to make a list of situations that make you itch to show someone the error in his reasoning.  It would be good to try to come up with at least ten different situations.  You could write a draft and then come back to it a few times to see if you can add some situations to the list.

The next step, after you have a good-sized list, is to rank them according to how hard it is to keep quiet about the person's erroneous reasoning (or "reasoning" if you will).

It is often possible to do the ranking in one sitting.  However, it's probably a good idea to put the ranking away for a few days before proceeding on to the next step.  The list, with the ranking, is called a "map" or "hierarchy."

To explain the next step, let me suppose that the situation that ranked as a "1," in other words, that caused the least discomfort, is the following:

  I am in at the fish counter in the grocery store, waiting my turn, and the fish counter clerk is telling a customer absolute nonsense about how to cook the fish the customer is buying.

Let's say this is something that has happened to you at least once, and is reasonably likely to happen again, because a particular clerk at your local store likes to shoot off at the mouth, without really knowing anything about cooking fish.  (This is just an example....  Bear with me.)

Now you could structure an exercise around this.  It could be, for example, hang out at the fish counter for a while at a high-traffic shopping time.  Listen to the clerk spouting nonsense.  Write down at intervals how strong your itch is to make a correction.  You could use a 1 to 7 scale or some other scale.  You can find out what a good interval is for you through trial and error.  My son was told to check his "temperature" at one minute, two minutes, five minutes, ten minutes, twenty minutes, etc.  But we found the following to work better for him: 10 seconds, 20 seconds, 30 seconds, 40 seconds, one minute, one and a half, two, two and a half, etc.  (Those are approximate.)

You have to hold yourself back from making the correction.  As time goes by, you will see the urge to correct subside.  It often increases before it decreases, and sometimes the curve has two humps.  But it does subside eventually.

It is possible to do this alone or with a friend or relative in a "coach" role.  The coach shouldn't reassure you, but it is okay for the coach to help you find something funny about the situation.

You have to repeat the exercise approximately every day.  It usually takes my son about 10 days to get to where the exercise is no longer challenging.

When you're done with Item 1 from your list, you proceed on to Item 2.

You may find it helpful to take notes about your physiological response as you are resisting the urge to provide a correction.

What's going on: your body cannot sustain the high adrenaline response indefinitely.  After some time (it might be five minutes, it might be two hours), your body will stop fighting, you won't feel that strong urge to explain just how wrong the clerk is, and you'll be able to go home.

The key to the whole approach is that you progress through the situations in a very graduated, step by step way.

It can be helpful to use calming breathing techniques as one is doing the exercises.

Alternatively, you could work with a therapist.  The International OCD Foundation helped me find someone in my area.  (There is a shortage of therapists trained in doing ERP.)


How do you organize your research? I am doing a lot of reading and experimenting to dig deeper into my research topic. In our institute we have weekly meetings, were we present our latest research. Often my professor asks me questions about specific details or numbers in ongoing discussions during the presentation, which I cannot recall so fast. For example, what is the current GDP of X country? I have understood, what the GDP is, but I do not know the number, which he would really like to hear in that moment.

I often have read this, and also re-read it in other reports and papers, but I cannot recall it in his moment exactly and I do not have the number available during the presentation? Btw often it is unclear before the presentations, which numbers are relevant during a presentation and also my peers feel that way.

How do you structure your research?
Which tools are you using?

I really appreciate your answer!

Learn to say I don't know. Practice how to gracefully say "Thanks for asking about that. I don't know but I will look into that." Do it to a mirror, make it look like it's your right to not know something, not a crime or even a weakness. After the meeting, go check the facts and then follow up with an e-mail.

Google it right there. It's getting more and more common and socially acceptable for anyone just to whip out a handheld device (smart phone, iPad, etc.) and Google it. If you're not sure about that, do ask "I don't know but would you mind if I search for it now?" Search phrase like "GDP [Country's name]" will actually result in a nice trend graph in Google, like this one for Vietnam. It would take less than 5 seconds; much shorter than time taken by people to apologize.

Prepare some fact sheets. If your work is heavily related with countries, consider printing out some fact sheets like the one on CIA the World Factbook and bring that with you. Similar devices like tip sheets or cheat sheets for basic information like formulas or acronyms will also be useful. The process of preparing them can also serve as a revision.

Use bookmarks and highlighter. If you are carrying some reports with you, use those write-on bookmark stickers to mark the potentially useful charts and tables.

Ask yourself why, for 5 times. While preparing your major arguments, you may consider a technique of asking yourself why for 5 times. For example, you have picked Haiti as your target country, why? It's a poor developing country, why? Because its GDP per capita is only US$820, why is that low? It's at 157th as of 2007. So on, so forth. This technique can help you think about unexpected questions, and also come up with strategies to deal with the "So what?" questions.

Knowing small details is not as important as knowing the big picture. Contingent on the last point, for research  (in my opinion) it's more important to know the big picture: rationale, theory or theoretical framework, pros and cons of methods, validity and reliability of the results, and what these all add to the literature or application. While planning for the research meeting, it's most crucial that you having given these components a good thought and be able to justify your interpretation and decision. Random statistics can come later.

Recalling small details is not as important as discerning pattern and anomaly. As the use of mobile Internet browser becomes more prominent, getting random details and facts is no longer our burden. Instead of using our precious brain power to memorize trivial little facts, it'd be more useful to tightly incorporate critically asking questions while going through the data, noticing patterns and exceptions, and synthesizing more questions or speculations.

Deduce it right there. Sometimes, the audience may not be expecting a perfect answer but rather a "guesstimate." Simply saying like "the GDP is likely low, it's the poorest country in the west hemisphere" can already address part of the question. If you really have no clue, it'd still be great if you can suggest how someone can get that information: "I'm really not sure about that, but I'd look for that in the US Census 2010 Fact Finder online."

While I do notice that you're also asking for advices on how to organize one's research. I don't think I can answer that given how little I know about your work, personality, and affinity to technology. Great research can be done with just a shoebox, index cards, a pencil, and an eraser; it can also be done with a state-of-the-art computer, various software packages, and cloud storage. It's likely something you need to discuss with your supervisors and other experienced researchers, and take and practice what is likely to be useful to you.


Should I leave the first authorship of our paper to the student who did the project whereas I solved it? I (as a Ph.D. student) supervised a masters project.

In particular, I defined the problem statement and prepared a sketch of the solution, that is, the steps which had to be done to achieve the solution. The masters student basically followed those steps which were mostly programming implementations. I composed the paper. Now, the paper is ready to be published, and I'm in a dilemma in selecting the first author of the paper.

On the one hand, I feel I am the right one because I solved the critical part of the problem, and the student just implemented what I had already planned. On the other hand, he may want to apply for a graduate position later, and I understand that he would morally expect to be the first author as this paper is his only serious research output. My supervisor left the issue to me by stating that my opinion would be his.

We unfortunately didn't set any specific set of expectations beforehand, particularly regarding papers and authorships.

According to a neutral mind, who most deserves to be the first author?

PS. The field is electrical engineering.

It would, perhaps, be generous of you to do so, but not necessarily wrong. In math and CS, listing authors alphabetically would probably be appropriate with little or no attention to "first" authorship.

But an academic being seen as generous is not a bad thing. Too many questions here are just the opposite, demanding first authorship, sometimes properly and sometimes not. But such generosity is more typical in a professor with an established reputation than in a current grad student.

But a serious consideration would entail looking at whether the student made a significant intellectual contribution to the work. If not, then first authorship is probably overly generous and might set a bad precedent in the mind of that student.

I'm with your professor on this. Your call. But the advice in comments (BrianH) on setting expectations at the start is good - even essential.


PhD in pure mathematics for a student in computer science I'm a student currently pursuing my masters in computer science.
My present area of research is computational algrebraic geometry (theory of grobner bases and tropical geometry).

Afterwards, I'm interested in pursuing my PhD in pure mathematics.

I would like know if I'll be elligible for applying to pure math PhD programs?
And if yes, do I have any realistic chance of getting into one?

What else can I do to improve my chances of being accepted?

Short answer: Yes.  Absolutely.  You are already doing mathematics.

A few bits of advice:

Ask your advisor and other references to specifically address your mathematical depth and maturity in their recommendation letters.
Include a technical summary of your past research, including pointers to ArXiv preprints if possible, in your statement of purpose.
Apply to math departments that employ computational algebraic geometers.  Three that come to mind immediately are Saugatu Basu at Purdue, Frank Sottile at Texas A&M, and Bernd Sturmfels at Berkeley.

(I know at least half a dozen former CS grad students who successfully switched into mathematics.)


Should I tell my supervisor that I added his/her name as a reference for my next academic position? Recently I finished my PhD level and I did an interview with a research group for a postdoc position. After my review, they asked me for some references to contact them.
I choose my supervisor and other visiting professors as references.
At this point, should I contact each of the professors that I added in my references list (including my supervisor) and tell them that they might be contacted soon to be asked about me?
I am asking this question as I am not good in "academic protocols". It could be yes (kind of respect as I am asking for his/her "help"), or no (it's something obvious that s/he could be asked by someone about his/her students).

You should ask anyone who you intend to serve as your reference if they are OK with it, before doing so. It’s not an academic thing specifically; the same would apply in other situations.


How do I get better at giving talks/presenting research? I read many papers and try to present some of them at a reading group of some sort in my department (these are all quite informal). Both my most recent talks were what I consider quite bad, and I really want suggestions to get better.

I only choose to present papers that I understand reasonably well, but when I start talking about them, I often fumble, fluster, and feel the need to constantly look at my notes, even though I know the math (I am in Theoretical Computer Science). I often start saying a sentence, then pause and start afresh since I forget to add a "modifier" like, "given an epsilon > 0" or something like that.

I really don't know how to get better. Due to classes and research, I didn't get time to rehearse my talks before. I also recently gave a formal talk as part of my Qualifying Exam, which went very well (as the committee told me, but also, I felt it too!), but I'd rehearsed it six or seven times before the final talk.

I can't spend so much time for every talk. So I want to know if there are any suggestions to get better at talking. I know stage fright isn't an issue as I'm quite an outgoing person.

EDIT: These are all whiteboard talks.

One important thing, for both casual talks and more formal talks, is your notes. Too many details and you can't use them without interrupting the flow of the talk, too little and you can get lost.

After some time, I converged to the following solution. I usually prepare one or two pages of main notes, not too densely written, with the main items I want to speak about and large signs for important things to mention at some point. Beyond two pages, I just end up caught in the moment and diverge from the planned path and improvise too much.

Usually there are some points where I could need a complicated formula, a precise statement, or a question might occur that needs one of these in order to be answered; then I simply make a mark (circled capital letters of color) where they might be needed, and write down the details along with the same mark on a second set of more detailed notes. Then I can refer to these when needed.

Another, general advice: be careful of what you do not like in other's talks, think about why, and be sure not to do that. The flaws of talks are often broadly shared, and this can only happen because we do not realize we do exactly what we blame others for.


Should I mention in my PhD application that I'm quitting my job in a month to spend time learning about the subject? I'm working as a software developer right now and am applying for PhD programmes in robotics and environmental conservation. I've put in my notice at work recently and should finish working there mid-February, about a month after the PhD application deadlines. I am quitting for a number of reasons, one of them including wanting to focus on learning how can I help the environment with my tech skills. One of the ways I can is to do research in a relevant field - hence the PhD.

I was wondering if I should mention my quitting in my PhD application. On one hand it demonstrates dedication to my interests. On the other hand, leaving your job without anything else lined up is an... unorthodox move in the professional world and I can see how it could be taken as a sign of volatility. What does stackexchange think?

From the admissions perspective, it shows dedication but also chutzpah in a bad way.

Many competitive programs have an admissions rate between 5-20%. Even if you are a strong candidate, it is not guaranteed that you will get in anywhere this year. This is why you have to apply to multiple programs as well as have a backup plan if you don't get in anywhere. Staying in a job (you might hate) would be such a backup plan and would show that you are someone who has Plan Bs.

If I read your application, I would have a nagging feeling at the back of my mind that you are rather sure of yourself and/or desperate and/or headstrong. None of these are good qualities for doctoral programs.

There's also a slight feeling of being extorted - as in, if you don't admit me, I'm screwed. But that's not our problem, you put yourself in that situation, yet it still leaves an unsettling feeling.

Neither of these are enough to tank your application but it could sway someone on the cusp of denial/admission towards denial.

tl;dr: A much stronger application would be one that says, "if I am admitted, I plan on quitting my industry job in May and spending the summer ahead of matriculation preparing for graduate studies by doing xyz."


How graduate admission committees choose between TOEFL scores? I recently took the TOEFL test and my score didn't satisfy me, even the result is above the minimum requirement for almost all universities. If I will retake the test and send my new score for graduate admission, will the admission committees always choose the best score between two attempts or is it possible that only the recent score will be taken into consideration? I want to clarify it  before retaken decision, in case if my score will decrease.

Unless your score is significantly low in one particular section (for instance, having a 105 with 30 on all sections but a 15 on Speaking) or if the committee has a strong reason to doubt your English skills, I don't see why you should worry about resubmitting TOEFL score. You will be making far better use of your time strengthening other parts of your application (i.e., SOP, GRE, etc). Given
a sufficiently strong application, even if they doubt your ability to communicate in English, some schools will interview the applicant via Skype/phone to establish whether their English is sufficient, and not automatically discard the application.

The TOEFL score serves, in general, to establish that you have a basic ability to communicate and work in an environment where English is the main language. Meeting the usual 100+ TOEFL score for graduate applications is sufficient and higher scores are not usually heavily weighted.

To more directly answer your question about which score they will consider, that will strongly depend on the school. You can e-mail them directly to know how they will consider multiple TOEFL scores. I suspect it would be analogous to the GRE (i.e., some departments choose whichever has a higher total score, some schools pick whichever is higher by section, some schools pick the latest, some schools analyze holistically).

Note: the answer to your question may depend on your field. I am in engineering.


Who writes the recommendation letters for returning student PhD applicants after a big hiatus? The answers to previous questions indicate it's possible to apply for and complete a PhD even at age 65+ (example, another example).

If these applicants did undergraduate studies at a conventional age of 20+, by age 65+, their undergraduate supervisors are probably retired or deceased. Who writes the recommendation letters then (especially if the applicant's job did not involve research)?

If the answer to this question is also applicable to all students whose supervisors are retired or deceased (e.g. a campus shooting kills all of a student's supervisors), I'll edit the question to include the broader scope.

I am not aware of a specific rule requiring academic references. It may be more a matter of common sense. If an applicant has recently completed a lower degree, the committee may expect to hear from professors who saw the applicant's work.

I was admitted to a PhD program over 25 years after my master's degree was awarded. What I had done in the last quarter of a century was far more relevant than my last academic experience.

I got references from my manager, my prior manager, and a chief technology officer. The last person was less familiar with the details of my work, but had a PhD and connections to the department where I was applying.


Asking a commitee to replace a letter of recommendation? I have asked one of my thesis committee members for a letter of recommendation for a position I was applying to. He is a well-known and well-connected figure in my field, we have a good relationship and he has written me letters in the past which I am fairly certain were very good.

The only problem is that he is quite busy, and therefore unreliable: During my latest job search he submitted a letter two months late and forgot to submit another one.

The position I applied to was very important to me and I did not want to risk applying with a missing letter, so as the deadline approached and I still hadn't received a letter, I asked another, lesser-known colleague to write me a recommendation instead.

The deadline has now passed a couple of days ago and I just received my committee's member's letter on Interfolio today. I already submitted my application and I can not amend it anymore through the online application service.

Should I try contacting the search committee directly and ask if I can get the letter replaced?

I'm afraid it might sound disrespectful toward the colleague that nicely wrote me the last-minute letter, but on the other hand I think the new letter would go a long way in helping my application...

You can ask. They can say yes or no. But it might be an even better option to ask them if they will accept an additional letter that arrived too late to include. This respects everyone.

If the answer is still no, then the professor who wrote the "replacement" letter might be convinced to send it directly to the hiring committee on his own initiative. It might be harder for them to reject it if he has a well established position that is known to them.


How do I reply to a potential postdoc supervisor who has no funds at this time for me? I am in the process of contacting potential supervisors for a postdoc position, and I need a bit of advice on how to reply to one of them. I have a PhD in urban planning, and I am applying to some American Universities for a postdoctoral position.

After contacting a supervisor, I got a positive reply, however he wrote to me: "You have impressive credentials, and I'm sure you could contribute  to our group. However, I have no additional funds at this point to support a postdoctoral position. I would be happy to talk if you have funding from another source. But at this point, my funding has been allocated to ongoing students. I am sorry that I do not have better news."

What and how should I reply? On one hand having some financial support is quite vital to me, but on the other hand I don't want to lose this opportunity. I would like to show how much enthusiasm I have to work in his group. I would like to suggest to write a proposal in order to give a grant, or asking him if he know somewhere I can find a financial scholarship. Or I ask him to let me know when he has a vacant position for me. I am unsure what to do!

You have pretty much answered your own question.

In a reply, consider including the following:

thanking the professor for his reply.
state that you would be most interested in contributing to the group should a position open up - even mention a specific common aspect of the research.
ask if he knows of scholarships/ similar funding opportunities etc.
suggest co-writing a grant proposal/application (be specific about which grant and what it would be for).
perhaps even state that you would like to collaborate on projects/research in any case.

On that last point - leave the 'door open' for a continuing link through research etc. - this may put you in good stead for future opportunities.


Is it plausible to change my major from pure math to applied sciences when applying for graduate school? I am currently a third year undergraduate student in university. A year ago I decided to study pure math because I liked its rigorousness. As time moves on, frustration accumulates because I don't know what I can do with all the things I've learnt. Maybe it's partly because I haven't learnt enough, but you know what I mean. Since I am already in the third year and it's impossible for me to change my major in my undergraduate study, I am hoping to change to another major when applying for the graduate school. Not that I don't like math anymore, but I want to be able to do something with it.

The following fields are of my consideration:

applied math
computer science
electronic engineering
artificial intelligence, machine learning, image processing
physics

These are the difficulties I believe am facing:

My GPA is okay, but not great. If converted to US standards, I have a GPA of 3.5+, ranking approximately 20%~30%. My university is world top 50 (maybe even top 20, but different ranking systems do differ a lot).
Lack of research experience. Honestly, there's just not much research to do for an undergraduate pure math students. We spend most of our time studying existing theories, and there's not much experiment to do for pure math.
Most courses I have taken are centered at pure math. I may lack sufficient knowledge of the fields mentioned above. For example, a CS major student studies data structure in his/her undergraduate years, but I don't. This certainly weakens my competitiveness if our applications appear together on the desk of the admission office.

On the other hand, based on what I've heard and my understanding of my own capabilities, I do think there are some advantages.

A professor who taught a CS course actually said to us that other departments (engineering, CS, etc.) are actually very fond of math students and that we are very welcome to join them.
Ever since I've gotten used to pure math and have built a solid foundation, I find it considerably easier to read literatures from other fields. Sometimes my friends would ask me (nontrivial) questions in their own majors (physics, chemistry, economics, etc.) and after a little research, I would be able to provide answers.
I have taken some graduate courses. And I am studying a graduate-level (maybe even research-level) topic under the guidance of a professor.

That's basically my situation. And I would like to know:

How possible is it for me to change my major when applying for graduate school? What kind of school can I hope to get into (preferably in North America or Europe)?
Is it true that other departments welcome pure math students, as is said by the professor mentioned above? Would an admission officer focus more on my advantages or disadvantages?
What other fields can you suggest?

p.s. It would be helpful if in your answer, you can tell me whether you have experience being on an admission committee.

How possible is it for me to change my major when applying for graduate school? What kind of school can I hope to get into (preferably in North America or Europe)?

This isn't all that uncommon. In the CS Msc programme at my university (Leiden) for example, we get a lot of people coming in from Statistics. The emerging field of Data Science has caused Statistics and CS to become much more closely related fields.

Exact requirements will probably vary by university, but at least in the EU the system is set up to make it possible for people to combine pieces of education from multiple universities. A BSc in mathematics together with some catch-up CS classes will probably get you in the door in a CS master.

That's not the of the story though. Individual courses often have their own requirements; a masters' course on advanced data mining might require prior basic data mining knowledge. But that doesn't mean you have to have taken the data mining class offered at that university. Our CS master attracts a lot of students from other universities. The requirement just means that if you don't know anything about data mining yet, you're going to get thrown into the deep end.

Since these requirements are mostly "you should already have a foundation in", not "you must strictly have this particular class", you could also fill in those blanks with online courses or reading relevant handbooks.

  Is it true that other departments welcome pure math students, as is said by the professor mentioned above? Would an admission officer focus more on my advantages or disadvantages?

What the admissions officer focuses on will differ from institution to institution. However, you should not be too discouraged by lists for formal requirements. People move from all kinds of places to all kinds of places, so partial matches are extremely common. Often you should be able to come to an agreement along the lines of "You already match ABC, but you need to pick up XYZ as well before you can enter".

Me for example, I wanted to switch from History to CS. For CS I needed a particular flavor of high school math as an entry requirement, but the remedial course they usually used was already fully booked. I found a remedial course at a different university and proposed that one, and they accepted that.

So approach the advantage/disadvantage discussion as a discussion where you look for a mutually acceptable solution. Be imaginative and constructive.

Right now, about halfway in the current academic year, is actually a good time to do this. If you can come to an agreement with regards to requirements, there is still a whole semester to take some remedial courses in a university or an online course that the admissions officer considers acceptable.

  What other fields can you suggest?

As a CS student I'm a bit biased of course, but if you want to apply math, I'd definitely consider a  CS Master. Machine learning and data science tends to be a significant part of that, and a strong math background is quite useful there.

Apart from the hip neural network side of things (which is much more about matrices than you'd expect), I would also recommend optimization/decision support as an area of study. This has a big mathematical component to it, which "native" CS students aren't always as strong in. In the field of natural computing in particular, there are a lot of people doing projects based on interesting proof of concepts, but lacking theoretical/mathematical analyis. That's something that a math background could help you with.


What are the main factors driving popularity of US higher education among international students? Observation: According to OECD stats, the number of international students at US higher education institutions is the highest in the world and still rising (see also Wikipedia here and a report here).

Question: What are the main factors underpinning the observation above?

I am interested in (partial) answers pointing to studies, or sources of statistical information on the topic, not solely opinions.

This is a reformulation of this question

Abstract

Firstly, the answer will tackle the question's false assumption that the US is the most attractive destination for international students. Secondly, I will cite some of the factors making a country/region's education system attractive to international students. Finally, to tackle some of the comments, I will present a chart showing number of international students per capita in selected countries.

USA is not the most attractive destination for international students

According to the OECD Factbook 2011-2012: Economic, Environmental and Social Statistics, the number one destination of foreign students among OECD countries is Europe followed by Northern American region:

  European countries in the OECD were the destination for 38% of foreign students in 2009 followed by North American countries (23%). Despite the strong increase in absolute numbers, these proportions have remained stable during the last decade.

To put the numbers above to global perspective, observe also that

  Foreign students enrolled in G20 countries account for 83% of total foreign students, and students in the OECD area represent 77% of the total foreign students enrolled worldwide.

Factors driving attractiveness of higher education in OECD countries

Again, according to the same source (emphasis added):

  Language as well as cultural considerations, quality of programmes, geographic proximity and similarity of education systems are determining factors driving student mobility. The destinations of international students highlight the attractiveness of specific education systems, whether because of their academic reputation or because of subsequent immigration opportunities.

Commenters to the question cite the ratio of international students per capita as an indicator of attractiveness of education system for foreign students. While I do not see any direct correlation between attractiveness of an educational system and the ratio of foreign students per capita (countries can be arbitrarily protective, or non-protective w.r.t. their own citizens), I prepared the following chart from the OECD data (relevant to year 2009):

The chart was constructed by merging data from the OECD.Stat with OECD countries population data from OECD population 2009 as published in the corresponding section of the OECD Factbook 2001-2012. The computation is done on non-citizen students column for the year 2009, except for United States it is the number of non-resident students (due to lack of a non-citizen students datapoint).


How to specify in presentation that permission to use a particular image is taken? I am presently undertaking research on a particular topic in control systems. That particular topic has a long history and I found a image which summarizes the history in one image only. I want to use that particular image in my presentation. I have also taken permission from the authors of that image to use it. But, while using it in my slide, I want to show in the same slide that I have taken permission to use that image so that professors understand that I am not stealing that image but I have taken the requisite permission to use that image. What line or a sentence should I include in that particular slide, so that the professors get that point automatically. I mean something like "Used with permissions". Like that what is the precise line which can be included ?

You can cite it a number of ways. I usually do this:

Right below the image, (Smith et al. 1998) if it's a paper where the image comes from. Then at the end of the presentation, you can have a slide called "References", there you can list the paper in the reference style of your choosing (e.g. APA). This way it's very clear where the image comes from.

I don't think the phrase "used with permissions" is necessary in a presentation. But I'm not certain. I'm sure others will comment on this. However, that phrase IS necessary if you were to publish the slides of your presentation, or if you will use that image in a paper.


What are the main reasons postdoc applicants get rejected? I'm applying for postdoc jobs right now (math). I was put on the short-list for one position and had an interview but the PI for that postdoc made the offer to someone else. I'm starting to get discouraged and wondering what I'm doing wrong. I showed my research statement to a few faculty members and they said it was fine. I also got a letter from one very well-known mathematician. Maybe I didn't make enough faculty contacts? Was I supposed to have a contact at each place I applied to? Maybe what I am doing is not trendy enough.

Question 1: What do I have to do to get noticed by the hiring committees?

Question 2: What are people getting postdocs doing that people who don't get postdocs aren't doing?

There are two big issues: competition and potentially poor fit. Either can knock you out. In some fields, at some times, the competition is fierce. Be happy (a bit) that you made the short list.

On the other side of the coin, it is possible that a candidate is seen as a poor fit for the position. This is more likely to happen early in the process unless it comes down to personal issues - arrogance, or indifference, or ...

Your materials can be fine and you can be fine, but someone else is just seen to be a better fit at the moment. Soldier on.

You may not need the rest of the advice, below, since you seem to be able to reach the shortlist, but for others, note that your written materials have to be positive/strong enough to move you from the "all applicants" pile into the "we should look at this person" pile. The second pile is very short and if you don't get into it at a quick reading, you are done. Once you are in the shortlist it becomes more of a personal and less of an institutional "game". If you know you are a marginal fit for a position, don't bother applying except in exceptional circumstances.


Whom is a diversity statement written for? This is related to the "what to say in a diversity statement" question, but I'm asking something slightly different:

  Who reads a Diversity Statement in a faculty application (exact sciences/CS/math) at an R1 institute?

Anticipating answers like "anyone on the department can read it", let me be more specific: Who usually reads diversity statements and takes relevant decisions on their basis? Is it faculty members? Is it administrators? Are they generally used as a first screen, as an appendix to the teaching statement, or as a tiebreaker?

The purpose of having a diversity statement is that you can honestly say that you have one if anybody asks.

The people who will read them would include:

People who are told they have to read them.
People who have nothing better to do.
People who want to confirm that you really do have a diversity statement.

Don't assume that anybody takes any relevant decisions based on the diversity stament.  The people who make decisions will either continue to be fair to all candidates, or will continue to be prejudiced.  Writing a diversity statement won't change that.


What should I do to maximize my chance at grad school (mathematics)? I'm a second year student who has had a terrible semester. I don't live in a great place this year and I became really unhappy because of it. I'm also involved with too many extra curricular activities and took an extra course (biochemistry) that all together brought my GPA (and motivation) down incredibly.

I'm positive next semester will go much better, I've taken a step back and analyzed my situation and what I need to do to bring my GPA back up (I might take some summer courses too). Lucky for me, the course I'm doing terribly in isn't a math course that contributes to my major, and the other two courses I anticipate I'll end with a B/B+.

If anyone has any advice on what else I can do to make my applicant profile look better for grad school, I'd really appreciate it. I'm planning on asking professors to see if they'd be willing to take me in for research, hopefully my stellar math grades will make up for the crap ones I've got this semester.

Otherwise, I'm hoping to take the Putnam and GRE of course, but if anyone has a similar experience, I'd really appreciate hearing about it.

Thanks!

If you are a second year student in the US looking to go to a PhD program in math, here is a list of some "standard" things to do:

Take as much math as you can, and excel at it. You should aim to not only have As, but high As, in many upper level classes.
Cultivate relationships with professors for letters of recommendation. This could involve research, but it could also involve class interaction, or attending appropriate seminars, or other ways of interacting with your professors.
Take the subject math GRE seriously, and study well for it.
Consider applying to REUs for the summer after you junior year. At more selective schools, many of the U.S. applicants will have gone to REUs. At the same time, the value of REUs is highly debated, with some favoring them and others suggesting that other kinds of preparation could be equally valuable, if not more valuable, in their opinion. In any case, you would apply to REUs in the fall or early winter of your junior year. Similarly, you could consider semester-long programs like the Budapest Semesters in Mathematics, the Penn State MASS program, or similar.
Begin researching graduate programs early; you will apply in the fall of your senior year, and the deadlines always seem to approach too fast.
If there are extracurricular activities you enjoy, continue to participate in them, but avoid getting too busy.

Other than the standard things, do what you enjoy. If you want to go to a PhD program in math you need a very strong track record in math. But that does not mean you need to be one-dimensional. Many of my friends at graduate school had other hobbies that they took very seriously.


To what extent should I mention unpleasant undergraduate experience in a graduate school statement of purpose? (pure math) I have not enjoyed my undergraduate math program, primarily because it is not challenging enough - not enough advanced courses offered, too few research opportunities, classes are just not at the level I feel they should be for junior-senior math majors. I am choosing to apply to grad schools (pure math) which I know have elite and challenging programs. I do not want to spend 5 years repeating this undergraduate experience. In the statement of purpose one is asked to explain why they are applying to the particular program. Should I mention this desire to have a more challenging, competitive environment, as compared to the undergraduate program, as a reason? I do have other substantial things I will write about, but I'm wondering if I should also mention this, as it is one of the main motivations I have for applying to the programs I am applying to.
Thanks.

I think you'd disserve yourself by making such a "complaint". Colleges have limited resources, and especially these days tend to be squeezed by administration... to offer ever-fewer courses, as ridiculous as that sounds. (Our graduate program at an R1 in the U.S. currently is under even-more-extreme pressure in this direction, for financial reasons that are themselves fairly non-sensical, but nevermind. It's essentially impossible to "argue" with higher administration...)
Read books (or notes, from on-line). Get advice from faculty on books/notes.
Do not be passive. Be eager. Even if the environment wasn't what you'd have wished, that's not really an obstacle, just "less help".
And, as in comments, it would be unwise to give the impression that you "need to be pushed" to do anything. I am aware that there is some notion that this is ok, but it is corruptive to one's thinking to sit and wait... Do not be passive.
EDIT: in response to your comment appended to the original question... I'd recommend that you not feel disappointed that your were "not challenged in class". Things don't have to work as challenge-and-response. Can be opportunities...
I'd agree that a sluggish environment can drag a person down... but, well, don't let your environment determine you, even if it has an effect.
If anything, a person could argue that a not-too-stimulating environment is a nice quiet environment, so that a person is not coerced...


How do I get back into Mathematics after graduating with BSc 14 years ago? Ive always loved Maths but for numerous reasons I bounced along in general/non-profit admin/management. After maternity leave I have found myself at the bottom again and seriously thinking how can I get back on track. Im 37, I graduated in 2000 with a UK BSc in Math 2:1. Anyone I chat to (non-mathematicians) always say, "it will come back to you" " go for it" etc but what do they know? What do those working in Math think? I especially was drawn to discrete maths, logic and computability. Where are the doors?

Sarah, why not just register to an MSc? It will give you an opportunity to refresh your memory and your skills and to test yourself. Also, if you'll do well, you should be able to get support letters and might even open the door to a PhD in the same place.


Pros and cons of not having PhD advisor's letter of recommendation after postdoc? I have finished my PhD and am currently a postdoc. Since receiving my PhD, I have not worked with my PhD advisor. I am planning to apply for jobs for after I finish my postdoc — mostly tenured-track positions.

I am considering not asking my PhD advisor for a letter of recommendation. I feel this might be appropriate because I plan to ask my postdoc advisor to write a letter, because my PhD advisor may not have kept up with my current research, because my coauthors know my work better, and for other reasons.

What are the pros and cons of not having my PhD advisor as a letter writer?

The only time that you shouldn't ask for a letter of recommendation from your PhD advisor is when you are not allowed to ask for one. This is not often the case, but it does arise in a few instances. The best-known one I can think of is that in Germany a Doktorvater (supervisor) is not allowed to write a letter of recommendation in support of an applicant whose PhD he supervised.

Other than that, you should have your PhD advisor write a letter; it is expected by just about everyone that the supervisor will write a letter, and it will definitely raise questions for you if you do not submit such a letter. If there is a particularly compelling reason, then, you should have that well in hand at the time when you are writing your applications. Otherwise, you'll have a lot more explaining to do, and probably a lot of potential postdoc supervisors may not even bother giving your application a second look.


Should there be a theorem or proposition that uses lemma? I was thinking the following: suppose that one writes an article or lecture notes where he or she uses some lemma. I have understood that every lemma should be used somewhere in the document. But is it enough if I use some lemma in an example, or should there be a theorem or proposition that uses that particular lemma?

But is it enough if I use some lemma in an example, or should there be a theorem or proposition that uses that particular lemma?

I don't think it really matters.  An example would be fine for most readers, while a few really formal people might disapprove.  However, even someone who disapproves wouldn't consider this seriously problematic.  I.e., they wouldn't think less of you or negatively evaluate your paper because of this.  The worst case scenario is that someone complains about it in a referee report, and even then you wouldn't have to follow their advice.


How do I convert my PhD dissertation so that it can be published as a book? I have just completed a PhD by research, which I think has some merits in being available as a book (This is, of course, my personal opinion). The research cuts across several fields (e.g. sociology, public policy).

I am wondering what I need to do to take the next step.

In particular:

How do you turn an academic piece like the dissertation (which is written for the examiners) into a book (which is for the general public)?
How do I find publishers who specialise in my field?

Why do you want the book?

For prestige?: publishers who contact you, don't do any review and charge high prices will only increase your prestige to those that don't know them (and these are probably not those you want to impress).
For dissemination?: why not just put the pdf available (as was already recommended)?. Those who are interested will find it, those who are not will probably not buy a PhD thesis
For money?: I doubt you will really make much out of it.

My recommendation: put it as a pdf on your website / your school's dissertation repository. If you see that lot's of people download it, consider an improved version as book.


Engineers/Scientists to break into management consulting Engineers and Scientists are probably not the kind of people management consulting companies look for. But I think many of such would be highly qualified and a good fit for management consulting positions, especially where vision and strategy are needed.
What would you suggest for a scientist or an engineer to succeed in getting a job, considering that the hardest part is to even get a phone call?

I'm afraid I've got to say that many of the things that one might consider an asset, are in reality going to be a hindrance.

Rigour, consistency, reason, domain knowledge, ability to describe uncertainty, always prepared to put appropriate caveats on findings: these are all encumbrances in almost all management consulting.

What you need to cultivate is the ability to form strategy on the basis of a fairly superficial understanding of a business; and the ability to persuade people to pay you lots for you to borrow their watch and then tell them the time.

Oh, and do watch House of Lies through, end to end, a couple of times, to get a feel for it.

Having said that, there is a tiny niche in management consulting available for the skilled technician who's prepared to say no to clients who want "regular" management consulting, and only take on clients who want a thorough, rational, informed job done. There aren't many of those clients, whch is why it's a tiny niche. And it's more likely to be a boutique subject-specific consultancy. But if you find one (or found one, i.e. you are the founder), and it gets the right kind of clients, you'll be very happy (and completely exhausted much of the time), and financially very comfortable while the clients are there.


Does McGraw Hill Connect improve student learning outcomes? I am debating if I should adopt the McGraw-Hill Connect system for my course next semester. On one hand, I am worried about the students' backslash because of the cost. On the other hand, after the pandemic teaching experience this fall semester, I want to utilize every opportunity to improve the students' grasp of the material.
The course in question is a quantitative one, taught to business students. It requires a lot of practice with problems, but in the current situation I cannot simply give a problem and circulate among the desks, helping to those who struggle. Another important feature: I have three sections for this course, each having about 50 students, so individual approach is problematic.
I have already coded quite a few "instant feedback" assignments in Blackboard LMS, but I feel that's not enough. Besides, even just importing and aligning them in LMS takes more time than I would spend lecturing in the classroom. Also, Connect allows me to monitor if the students actually read the textbook, and I expect that it would encourage them to actually read it. There is also an automatic text-to-speech narration, which is bad, but better than nothing -- they can listen to it while commuting, hopefully something sticks.
I will highly appreciate if someone shares their experience with me. Does Connect really improve student performance? If it does, how do you communicate to them that the hefty price is worth it?
Update:
I saw some commenters concerned about the ethics of making the students pay for it, so I have changed the thread name to make my question more clear. More context: I work in a private US university, where the tuition is about $50,000 per year. Hence, the students are paying roughly $5000 to take this class. The publisher price for one semester access to Connect is over $100, which is outrageous, but if this allows the students to make the most of their tuition, I believe the right thing for me to do will be to adopt the system.
Of course, there are long-term consequences of this decision. A significant part of that ever-increasing tuition is what the universities have to pay to LMS and database providers: once their product gets adopted, they keep raising the prices, because switching to another textbook/system is very costly for the university. But I believe my responsibility is to do what is best for my students.

I use Connect for one semester. Some comments

About the cost: what is the alternative if you don't use Connect?  Probably a printed textbook.  Connect is probably cheaper than a printed textbook, at least it was for my class.  I did not have any students complain about the cost (out of about 80)

"Also, Connect allows me to monitor if the students actually read the textbook".  Yes, but it doesn't monitor if they understand the textbook. I had many students asking questions during class that made it obvious that they had not understood the content from the book, even though nearly everyone had done the reading assignment.

The instant feedback feature is very nice. I personally gave students several attempts at the problem.  i.e. if they got it wrong they had a chance to correct it. At least for me, this ended up driving a large number of students to attend office hours.  i.e. without instant feedback, they assume they have done it right, turn it in, and a week or two later I grade it and they see they're done it wrong, but by that time we are already onto another topic.  With instant feedback they know immediately that they are wrong, and then come to office hours to ask questions.  I think this is a plus for student learning.  You can, as you mentioned, code this into Blackboard or Canvas yourself, but have pre-coded questions will save you a lot of time.

I do plan to use it again.