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what is the best way to take missing courses before applying to MS?
I am holding bachelor degree in applied math and physics, which I received in Moscow State University. I have rather normal grades (average 4.3 out of 5). My BS thesis ("Weight optimization of monospar composite wing of russian unmanned aircraft) was recommended for publishing in scientific journal.
Everything seems to be ok, unless I have a passion for programming. I have implemented several mobile applications which are available in the AppStore and which are my main income now. Once I started to get enough money, I started to think about my MS degree in computer science field. However, I do not have enough minimum background for graduate program, hence I decided to take the missing core courses. The way of applying to undergraduate program and spend 5 years again seems to me time-wasteful (i am 23 now), so I come up with decision to become special/visiting student and get the necessary transcripts and become more competitive while applying to MS program. However, some universities do not provide engineering courses, some of them are too expensive (~50k per semester, I am able to spend ~18k); in some universities to become special student I must be invited by faculty member.. In other words, it is not as easy as I expected to take undergraduate courses. I kindly ask you to give me some tips how to enter to computer science field.

Is there any particular MS program you're aiming for that makes this answer insufficient? From the sounds of it, you'd be a a candidate for a MS in CS without taking more courses; or at least, it's not clear to me that undergrad courses are the way to go.

I am thinking to apply for McGill MS, which says If you do not have the background described, please do not apply. We do not offer any qualifying program for students with weak Computer Science backgrounds. Since I will try to reapply next year, I want to be prepared for my reapplying.

Ok, fair enough. It seems that there are two questions here really: 1) What to take courses in to transition, 2) Where to take them. The second question is going to depend on a lot of factors (geographic flexibility, cost, desire for credentials etc) that I can't really help with. As far as the first part, it'll depend on your desired speciality a bit, but,I'd repeat my answer from here: Focus on fundamentals; Algorithms, data structures, complexity especially.

Thank you for your prompt reply.So, in general it does not matter for university where I got credits for the missing courses as a special student? or it is better to get them at a university that is internationally recognized to be more competitive?

It's going to be a bit of a judgment call. Your goal will be convince the admissions committee that you have sufficient background to not struggle. It could be that your experience as a developer and your undergraduate degree could be sufficient; Adding MOOC courses might help get you over that hump, or might not. Accreditation is usually the safe route, but it's going to depend on how those accredited courses are seen by the admissions committee, which is beyond my ken. Others would answer this question better though, who know what the inside of that committee looks for.

I'm not sure that this applies to Russian Universities as my experience stems from the situation in Germany, but I'd recommend talking to the key people at your target University - academic counseling for CS, student representative, dean of students. See what you can find out about the admission process and whether they can give you any pointers.
I myself have a Bachelor in Applied Math and a Master in CS. Before applying for the MS, I visited the University I wanted to get into and met with the faculty member who was responsible for the academic counseling for CS students. I talked him through my undergrad courses and other experience from internships and he encouraged me to apply right away although I technically did not have enough undergrad CS courses according to the admission guidelines. He also gave me a few pointers on how to write the application in such a way that the admission committee would recognize my practical experience.
His advice: He gave me the list of mandatory undergrad courses and told me that I should match each course with something from my previous studies or my practical experience, to show that even if I had no formal education in some areas, I at least knew the gist of the subject.
I was admitted conditionally and had to complete the two undergrad CS courses in which my prior experience was lacking the most within the first year on top of my regular studies.
In my second year I became the student representative to the admission committee and had a few applicants approach me on the same subject. I gave the same advice, because I noticed early on that the committee would often just hold the list of requirements up to the applicants undergrad transcripts and tick of the boxes.
Even such stupid things as differently named courses could throw the committee off, so I made it my job to go through all the applications and check the matching with the requirements.
In one particular case, a student was very enthusiastic and even ran his own IT-startup business, but the gap between his undergrad studies in a different subject and a CS undergrad was just too big. We had to refuse him the first time he applied. For legal reasons, we couldn't do more than send the standard letter, but luckily he did the smart thing and approached us and between everybody in the admission committee and academic counseling we figured out a way to have him do undergrad courses for a semester and then delay the decision about his follow-up application until the exam results were out and we could make a case for him to be admitted on conditions, like I was.
Your second question, which classes to take, will only be answered when you know what classes they look for in an applicant from another subject.
The people in the application committee at my university really looked for theoretical background. Do we think this applicant knows what P vs NP is? Do we think he can analyze the runtime of an algorithm? Do we think he knows the difference between a proof and an experiment/example? Percieved knowledge gaps in other subjects like electrical engineering or computer networks or operation systems where often seen as less of a problem if the applicants motivation letter stated that he wanted to specialize in an area where he likely wouldn't need that knowledge.
When in doubt, the committee would often say that the funding depended in part on how successful the students were (i.e. it was better not to admit one than to admit him and have him fail) so they would discuss: Do we think that this applicant will complete his studies in a successful and timely manner?
So one more point of advice, which worked well during my time on the committee: Show in your cover letter that you have a clear idea of what you want to do in your masters, why you want to do it, and why you think you have the necessary background and motivation to be successful at it.

I am having same issue, i have done Bachelors in Elect. Engineering and with 6+ years of Exp in Software Development I want to join Masters in Software Engineering in Germany, however Study advisors are behaving as if its impossible. Elect Eng is way closely related than Applied Maths. Can you please guide me in this regards if you can provide me email so i can send all the possible details.

@MuhammadUmar Dear Muhammad, I'm not in academia any more, so I don't think giving you my email address will be helpful at all. Electrical engineering might be close to parts of computer science but math is close to other parts of it. The student in my story who had to study for half a year before even getting a chance was from electrical engineering, so you just might not have the theoretical background on paper, but you do have experience. Talk to the CS-"Fachstudienberater" at as many different universities as you can and you'll probably find one who's willing to work with you on this.

Dear, You are correct, i am missing mostly the Theoretical subjects. However i am not exactly sure how to take these courses. I want to do MS in software engineering, i have quite a lot of time before admissions are opened but i have no idea how to take these missing courses, i dont think Univ provide facility for studying specific subjects. If you can guide me it would be helpful.

The problem with Soft.Engineering is only 3 Univ provide this course , TUM, LMU and RWTH, RWTH Fachstudienberater have specifically said in mail that chances are low and i would have to study these courses from somewhere else. TUM and LMU aren't replying at least on emails. So mainly i am not sure from where to study these courses. I also dont think they will take into consideration online MOOC certificates for these missing courses.

You can take the missing theoretical courses at any university that offers a computer science bachelor, or maybe at Fernuniversität Hagen if you want to take them from home and have the money. But it's no guarantee that your application will be successful even after doing that. The programs you mentioned are very competitive. Btw, many universities offer CS master with the option to specialize in software engineering (i.e. to take mostly software engineering courses during the master) maybe that's an option for you? It would give you more chances to convince someone of your qualifications.

wont CS Masters will point out same issue related to missing courses for admission?

@MuhammadUmar Yes, but your chances are still better than when you only apply to the three most competitive programs in the country - and you might get almost the same content at many other universities. And once someone has admitted you and you're doing well, it'll be easier to get admitted elsewhere. So maybe you could start somewhere ok for you and then try to switch to your dream program after a semester. Just an idea though. Personally, I'd go back to the RWTH counselor with the idea of taking a few undergrad CS courses and then applying for next year. They might help you choose courses.


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Chances of getting into a CS PhD program from a math/engineering background?
I have an undergraduate degree (B.E.) in Biomedical Engineering. Right now, I am working on a M.S. in Applied Mathematics and Statistics and will be done pretty soon. I have very minimal research experience, and no papers published. I will be working in industry for the next year (since I didn't apply for any PhD programs this application season). However, I would like to get into a PhD program as soon as I can.
My interests are in the field of AI and Machine Learning. From the research I have done, most AI/ML research is done by Computer Science departments; so that is where I must head. What are my chances of getting into a good AI/ML program coming from a different background and no relevant research experience (although I have no direct research experience, I follow the literature and learn as much as I can on AI/ML in my free time)? What can I do to best increase my shots of getting into a top CS department known for AI (Stanford, Cornell, etc)?
Instead of working for a year, maybe I should seek a research assistantship at an AI lab (less pay, but if it can get me into a top program then so be it)?
Any advice is appreciated!

Is it that you have no AI research, or no research experience period? I would hope your MS is providing you some research experience...

Matthew, I have done many projects (that involved coding) in the area of statistical computing; but nothing directly in machine learning or AI (I have played around with ML packages in python, however, to learn; but again not an "official" experience)

High GRE scores open the door (quantitative reasoning and to a lesser extent analytical writing).
Math / Statistics background will raise eyebrows.
Creating a portfolio of projects to show the department that you can in fact code, will get you assistantships.
Be pro-active but not a pest.

When applying to a university, you might want to peruse the various web pages of faculty to see what fields they are publishing in. If you find a field that piques your interest, or that you've done some similar work in, contact the professor directly and seek advice. Be careful though. I get emails all the time with prospective students phishing for assistantships. I can tell when it's a bulk / canned email that was sent out to a ton of faculty just looking for someone to bite.
I would start with a personal tone:

Hello Dr. ______________ I was looking at your work on _____________ and wanted to let you know that I am very interested in this research topic.

It probably would be even better if you could tell them that you already applied to their university, but I understand that you would go broke with all the application fee's if you applied to every university that peeked your interest.
Briefly explain what your seeking (cool research, with possible assistantship). Be patient, you might not get a fast response, if ever. These guys are busy, and probably getting a bunch of emails as well. Start early. At least a full 12 - 18 months out. This way you can narrow down your choices and not have to worry about application deadlines coming up too quickly.
Communication skills can be big. If your comfortable in front of a classroom, and your english skills are good, maybe looking for a teaching assistant position could increase your chances. This does mean you won't as much research, but at least your getting your foot in the door. This will give you more opportunity to show a particular faculty member what your worth.

In my opinion it is better to start the first e-mail with: Professor ______ I was looking...

I've read elsewhere that we shouldn't even email professors at all... I'm so confused. :\

Terry has a great answer, so I'll just add a bit more...
The biggest hurdles are your math, logic, and coding skills.  If you can prove you have these, then you'll be in good shape.  CS, on a theoretical level, is far less coding than you might think.  I had professors in CS who didn't even have computers in their office, and made a point to never use/require computers in the classroom.  Simply put, there's a lot of thinking, work, and research to be done on paper before you even attempt to program.
Of course, since you're into AI, that means you'll need to code quite a bit.  I don't know how much you know about AI, but I would recommend Artificial Intelligence: A Modern Approach which, in my experience, is the de-facto entry to AI in academia.  It's usually split between two courses, sometimes one of which is undergrad, and the other grad level.  It has used various languages over the years, but the two most notable ones are Lisp, which deals with list comprehensions, and Java, which is a typical Object-Oriented language.  Having experience in both would be very beneficial for you on your CV as well as when you actually start working/researching.

and made a point to never use/require computers in the classroom — Some CS professors actually require computers in the classroom? Weird.

Honestly if you can prove yourself in the field then you should have no problem. I would suggest reaching out to various universities and trying to prove your knowledge. For instance my math advisor has a bachelors in engineering, a masters in economics, and a phd in math. It just depends on how much you know and how much you want it. It is most definitely possible.

Ryan, thanks for the advice! By reaching out to universities, do you mean writing to professors whose research you are interested in, and explaining to them my interest + knowledge/experience?

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What can I do about a lecturer who isn't clear enough to understand?
I'm a Maths university student and I just can't seem to learn anything from one of my lecturers.
I understand we, as students, should do personal research on our subject. But he just doesn't make any sense.
He'll teach one thing, then during that, he'll RANDOMLY pull out something out of the blue WITH NO EXPLANATION.
Not even a "Well we do this because...".
He explains new concepts, like he's talking to PhD graduates.
I've spoken to him about it and all he says is "He loves teaching".
I've already failed 2 of his module exams because of this and am having to resit them.
What can I do?

Conduct research independently.

The first time this happened to me was when I was forced to truly learn how to read a math textbook for the first time. That became among my most powerful and important skills later on.

Ask questions. If no one else asks, be the one to break the ice - it will benefit everyone.

@ZeroTheHero - Yeah, I'm not the only one who says this. Others think so too, but I'm the only one who's spoken to him about it

Here are some ideas for you to consider.

Seek out a more advanced student who has already made it through the course, for guidance.
If the class has a TA, visit the TA's office hours assiduously.
If the course has a textbook, read it carefully.  If it doesn't, ask the professor for a textbook that is reasonably well aligned with his approach.
Make sure you have a course syllabus.  See if a careful perusal of the syllabus helps.
If you have an advisor or mentor professor, let him or her know.  If you don't have one, try to find one, by talking to another professor in the department that you think may be knowledgeable about the course content.
Let a department administrator know about your difficulties.
Consider withdrawing from the class.

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To include only academic titles in business cards of researchers with many positions?
Assume you have many academic titles, but you have also many positions.
I am thinking to exclude all positions, and just having your academic titles because I do not want to carry a pile of different business cards and in many languages – just one general for all.
So I would leave out all positions, which can be seen on my online profile if necessary, e.g., ORCid, ....
Format

Name
Titles
...

Example:

Leo
  MD, PhD (Med.), PhD (Tech.)

@Roland Which of them? - - It will be a hassle to include them all, but also awkward to include only one. Not an easy task.

It's diffucult to gibe an advise without knowing al these positions.

This may depend a lot on local culture. (For instance, the Austrian way of listing academic degrees differs from the German one.)

I am thinking to exlude all positions, and just having your academic titles because I do not want to carry a pile of different business cards and in many languages

That seems like a somewhat bad idea. The main goal of a business card is to serve as a reminder for the recipient of the card who you were once the conference or event where the card was given out is over. Hence, the more specific the information on it is, the better. "PhD" or "MD" usually carries really little information, as many people at the events that you frequent will have the same titles. "Works at IBM" or "Associate Prof at UCLA" is much, much better in that sense. Your job title(s) are also a much more fine-grained representation of your seniority than your academic titles. The holder of a PhD can be anything from a freshly-minted graduate to a senior professor, while saying "Associate Prof" transports a lot more meaning.
Further, many employers will actually not be thrilled about you rolling your own business cards. Employers typically have a specific corporate identity, and expect you to use that (and not mention your other gigs on their cards).
So what do you do?
Get separate business cards for all your major affiliations. These may include all your titles if customary, and only the job title and branding of this specific affiliation. You probably don't need a card for company X just because you are in the advisory board, or for university Y because you teach a course as external lecturer once a year. If you have multiple major affiliations, decide who you represent in any specific event, and use these cards (a good proxy for this might be who you are charging the event to, time-wise and financially). You can always verbally add your other major job(s) when handing out the card.


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As a student, should I offer alternative ways of understanding a point in lectures?
Often, I’ll be in lectures and the lecturer will explain the point to me, and I make a comparison with something else that helps me understand the point, and it clicks. For example, in Syntax, the lecturer was talking about the difference between a noun and a determiner phrase; how the former describes a set of things, and the latter points to a specific thing. This reminds me of computing, so I think: ‘Oh, right. Nouns are classes, and DPs instantiate those classes.’
Is this type of rephrasing ever a useful thing to vocalise in lectures, for other students or the lecturer? I do sometimes vocalise these thoughts, usually in a smaller class setting though, not lectures. I usually try to keep quiet because I feel like either people won’t understand what I mean, or the teacher doesn’t consider it relevant or useful. So, my questions are: Is this kind of contribution in lectures valuable? Or do lecturers prefer that you ask questions instead of making statements?

This is a bit tangential to your question, but I wouldn't say a DP is to a noun as an object instance is to a class. I can kind of see where you're coming from, so I won't belabour that, but a more important point is how "good" ones analogy is; both in terms of fit and others' ability to comprehend it.

Sure, there's no real instantiation going on there. The thinking was, a noun refers to a general set of things, 'John' can mean any person called John. But 'that John with the hat' selects a specific identifiable being who fits the 'John' category. When the lecturer said that, the class analogy sprang to mind immediately; I'm aware it's not watertight though.

If you are in a small lecture that encourages participation, then it is definitely appropriate to participate, and understanding things in more than one way is often a great thing.  I would recommend phrasing your thoughts as a question rather than a statement, however, e.g.:

Would I be right in understanding this like [comparison]?

After all, you're only just learning the material and don't yet know if your comparison is actually right!  If you can concerned that you might be talking too much then a) a very good lecturer may be able to let you know gently in the midst of class and b) you can ask the lecturer their opinion after class.

Great idea! Also mitigates the problem of not having actually asked the lecturer a question; it could be incredibly awkward if the lecturer has to say the equivalent of "Yes" and leave it there.

I agree with this answer in general, but I think I would keep the comparison to myself (or "ask after class") in this particular example for the reasons given in David's answer.

Yes, certainly it can be useful.
However, it's more useful if your analogy is well thought through, and can be stated concisely in a way that you think can be understood by the other students.  If it's sort of rambling, or misses important aspects, or requires background that most other students may not have, it may cause more confusion than it clears up.  So in some cases you may prefer to make a note for yourself, think it through later, and discuss it with the lecturer privately (e.g. during office hours).  The lecture may then mention it in a future lecture, or invite you to do so.

To say it "can" be useful seems like it might be difficult advice to act on. It seems very unlikely that it is always appropriate even if it is concise and well thought out.

@BenjaminMakoHill I find your objection ironic, given that your own answer says "These types of comments may or may not be welcome"! There's no universal yes/no answer, so the best any answer can do is say "Whether or not it's appropriate depends on a whole lot of factors that we don't know about and you'll have to judge for yourself, perhaps with the lecturer's assistance." That's basically what Nate's answer says and basically what yours says.

@DavidRicherby, My comment was not meant as an objection and I voted this up. My point was that I read this answer as saying "be careful but go ahead" and mine as suggesting, "ask the instructor first." Perhaps I will unbold the first sentence of my answer to make this more clear.

@BenjaminMakoHill Fair enough. To be honest, since Leo has sufficient self-awareness to ask the question, my guess is that he can take appropriate care.

@BenjaminMakoHill: The question was phrased "Is this ever useful?" so logically the possible answers are "Yes, there are times when this is useful" or "No, this is never useful".    My answer is the former. (Can you tell that I am a mathematician?) I am not claiming it is always useful and my second paragraph included some suggestions on how to identify when it is.

To be honest, the specific example you give is unlikely to be helpful, since you're in something like a linguistics class and your analogy requires an understanding of a completely different field, object-oriented computer programming.  Most of the other students probably won't have that background and the lecturer might not, too. And suppose the lecturer doesn't have that understanding.  They'll likely be tempted to ask you to explain your analogy so they can evaluate whether you've understood or not. So now you have to spend a couple of minutes explaining OOP to the lecturer and all of that is time that would better have been spent on the actual subject at hand.  The lecturer might also feel that you're trying to embarrass them by asking questions about something they don't understand.
In general, I'd be wary of interjecting with analogies since, unless the analogy is perfectly accurate (which most aren't), it's likely to lead to a discussion of the accuracy of the analogy, rather than further clarification of the real point.
Beyond that, I'd give the tautological advice that interjecting with alternative ways to understand is useful if it's useful. If the other students find it increases their understanding, go for it; if they seem not to appreciate it, don't do it. If the lecturer already explained it once and most people already understood it, there's no great value in you explaining it to everyone again. In particular, if your interjections become interruptions which break the lecturer's flow, you're hindering rather than helping.

Good point, and well put forward. "it's likely to lead to a discussion of the accuracy of the analogy, rather than further clarification of the real point." Yeah, I think I will keep these thoughts to myself unless they're super relevant and no one else seems to get it.

Because these types of comments may or may not be welcome depending on the nature, topic and size of a course and the pedagogical approach of the instructor, you should ask your instructor if these kinds of interjections would be welcome. You can easily do this with a quick question after class or in an email. To make things concrete, it might be a good idea to come prepared with at least one concrete example of the kinds of clarification or reframing you might offer as a comment. As an instructor, I can see myself going way or another based on the class and the setting. That said, I would be always be happy to be asked ahead of time if this sort of thing would be welcome!


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How important is the statement of purpose in a PhD application for admission to a top school in the US?
According to this MIT statement of purpose guideline, the statement of purpose seems to be an important part of a PhD application.
However, I have also heard that, in the case of MIT, the statement of purpose is only reviewed after the application has been tacitly accepted.
So, how crucial is this part of the application, and what part does it play in the process of graduate admissions at top schools in the US?

I have never heard of "tacit acceptance," can you explain what you mean by this?

@RoboKaren: I guess, it means that the application was accepted considering everything but the statement of purpose and only then the statement is regarded (for whatever reason).

@Wrzlprmft - that is not how admissions at graduate departments work. We go through various rounds of culling and grades/GREs do play a role in some of the first round culls. But even when we are at the last round (16 people to be reduced to 8), in now way do we construe that these people are "tacitly accepted."

@RoboKaren: I did not claim that this is how it works, but that this is what Kurt heard how it works.

If something is in your application, reviewers will read it, and if you write a completely ridiculous statement of purpose, the reviewers are going to notice and turn you down. This "tacit acceptance" statement is absurd.

You have to specify which discipline, but for the social sciences the statement of purpose is the most important item in your portfolio.
We also look at grades, GREs, and letters but we scrutinize the statement the most. A good statement can resuscitate a candidate with middling grades, a bad statement can condemn an otherwise good student.

This is an extremely general question, since it doesn't refer to the discipline. Since another answer comments on the social sciences, I'll speak up for physical sciences. (I'm in chemistry.)
We look at every facet of the portfolio. To do otherwise is to ignore useful information on the applicant. Let's be honest, we don't have much data. We get grades, GRE general scores, GRE subject scores, and recommendation letters. Plus the statement.
I mentioned in my answer to another question that GRE scores will sometimes serve as a first screen, to cut the pile down to a level we can really analyze. But that's not a "tacit acceptance". (I don't even know what that might mean.)
Yes. After a first cut, we look at the statement of purpose 100% of the time.
And yes, if someone writes a lousy statement with an otherwise good package, it's a bad sign. It tells us that the student just doesn't care to do a good job. Is that someone I want as a grad student? Probably not.
Even if a student has stellar grades, GRE, and a paper in Science but the statement is poorly written, I'm going to think twice compared to a student who might be a bit behind, but seems to have a vision and sells themselves well in the statement.

"Even if a student has stellar grades, GRE, and a paper in Science but the statement is poorly written" that might be a bit of hyperbole :) would you really reject a student with a paper in Science based on a bad SOP? I wouldn't. (of course this extreme case is irrelevant to close to 100% of all applicants)

Yes, it's hyperbole, but certainly we're going to ask questions.. Like how much of the Science paper was from this student? My point stands. A good student with a poor SOP is going to get questioned because the pieces don't add up.

I serve occasionally on the PhD admissions committee in the computer science department at Stanford. To me, your grades and test scores are less important than your statement of purpose and your recommendation letters. To clarify: the statement of purpose is very, very important. I want to see how you articulate your future plans, how you think about and approach research.

Original Answer
I would add an exception to @RoboKaren's answer. Economics programs tend to place very little weight on statements of purpose. Econ is perhaps a bit different from other disciplines because the first year is all coursework.
In a statement of purpose for an econ program one should highlight relevant previous courses/skills (especially math/stats) and indicate a few areas of interest (e.g. "Macro labor" not a dissertation proposal). Minimize the fluff.
Several economists (including Susan Athey [Stanford] and Jeffrey Smith [Michigan]) have composed helpful guides on grad school admission. I'd bet others have done the same in other disciplines.
Edit In Reply to Comments
The general point that I hoped to make with this post (which was implicit but which I will now make explicit) is that the importance of the personal statement (and the nature of the application in general) is particular to a given discipline.
Why don't economists care about personal statements? First, it is costless for applicants to overstate/misrepresent their interests, talents, background, enthusiasm, etc. Second, given the other materials available to the adcom (see below), even a truthful statement is more or less superfluous. Third, deemphasizing the personal statement reduces the advantage enjoyed by native English speakers in admissions.
What do economists care about, then? By far the most important component is faculty recommendation letters. It means something if a faculty member is willing to say that someone is "the best student they've had in eleventy years in the profession". Suppose a faculty member misstates the qualifications of the applicant and the applicant is admitted (and perhaps offered a stipend). If the applicant fails out, then (1) the adcom will be disinclined from believing the recommender the next time around and (2) there may in certain cases be some informal social/professional consequences (i.e. "Hey remember that time you recommended that one kid and we wasted a spot and 25k on him just so that he could drop out in April of the first year?").
I don't think that this is a perfect system (or that admissions are perfectable) but that's just the way it works and has worked in pretty much any econ department for quite some time. Depending on your view of economics, it either more-or-less works OR goes towards explaining why econ is so messed up(!).

Thanks. But I believe that first-year course work is not sufficient to guarantee little-value on statement of purpose; could it be economists's "application" of "efficiency". I doubt the adequacy, and I believe the importance of statement of purpose. For otherwise one only admits a collection of scores.

@Kurt I talked to an admissions director at a top-10 econ PhD program recently, and he explicitly stated that (at his school) statements of purpose can never help you, it can only hurt you. I believe he recommended to keep it polished and generic absent extraordinary circumstances. Recommendation letters, research experience, classes taken, and grades are probably 95% of the decision at top schools.

Yep, then good luck to this school's future :)

@Kurt I'm sure that a school tied for the top econ PhD program (by US News) isn't doing too bad. I will also note that every academic economist that I know of assumes that top schools don't care about SOPs; that kind of consensus isn't born without reason. You can argue with the value of ignoring SOPs, but you can't argue with the fact that it is the current reality.

I have to agree with what one of the CS guys wrote above, that in CS we consider the SOP to be extremely important. Also, you should know that MIT does not usually 'tacitly' accept anyone based on only their grades and numbers. Usually, a tacit acceptance comes about because you have a funding source lined up; perhaps you've secured a fellowship or you've established very close contact with a faculty member in MIT or the college you're applying to, and that member has agreed to accept you into the group INCUMBENT on your getting through the general grad school admissions process. At that point, your SOP might not seem as important because it's obvious you've found your focus, and in most cases, the SOP is merely an avenue for you to articulate your focus ('purpose') in a convincing, objective fashion.


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What is the difference between a school and a department?
Some universities have a School of Something and some a Department of Something. Are they identical and just two common terms for the same thing, or they are different in the university structure?
My impression is that a School is generally larger than a Department. Probably, school is an academic unit between department and faculty. Maybe, a faculty has a few schools, and each school hosts some departments.

The term school and department are going to mean different things at different institutions. Generally speaking, the term school refers to a larger unit within a university than department and many schools will contain multiple departments. For example, Harvard University contains a School of Public Health (and other schools) which contains a Department of Epidemiology (and other departments).
That said, names are often not even used uniformly or consistently within universities. For example, at the same organizational level as the School of Public Health at Harvard is the Faculty of Arts and Sciences which runs both Harvard College and the Graduate School of Arts and Sciences. My current university uses the concept of an academic "unit". Many units are "schools" (e.g., the School of Public Health or the Information School) but others are not (e.g., the College of Arts of Sciences). There is also an organization within the university called the Graduate School which cuts across and oversees  work in different units and schools.
Sometimes, smaller "schools" will not contain separate departments. Sometimes, a large department in a large school might be larger than entire schools elsewhere in the university! Sometimes, the terms might be used interchangeably. In many other cases, they won't. In some cases, one or both terms might not even be used at all!

At my institution (US public), I am in the School of Mathematical Sciences.  We have no sub-departments, and are on the same organizational level as the Department of Physics and Astronomy, both directly under the College of Natural and Health Sciences.  My School is organized just like every other academic department I've ever seen, except that our "department chair" has the exalted title of Director.

In line with Benjamin Mako Hill's answer there may be no uniformity between different institutions. In general the following hierarchical structure is applied to universities in Ireland.

University Name
College Name
School Name
Department Name

So in my case in my university as a History Student it would be the Department of History in the School of Humanities at the College of Arts, Social Science at my university.
In this scenario the School is made up of a number of Departments of specialised study and the college is made up of the schools that would fall under its remit.

Although this is good general advice in the US as well, it's extremely common to be missing at least one of these structures. That said, if organizations with these names exist within an institution, it is likely that they would fall in this order in the hierarchy.

@BenjaminMakoHill Yes I agree, I have found in Ireland that it seems that the older (19th Cent) Universities can have all and newer (20th Cent) Universities have some missing.

In many universities School is used for units that confer a professional accreditation (e.g. School of Law). In contrast, Departments are units that refer to specific areas of knowledge that do not end up as a professional qualification (e.f. Department of Philosophy).

What kind of professional accreditation would a "School of Arts and Sciences" confer in this taxonomy?

I have no idea. At least several NZ universities use the distinction I presented. I do not claim universal acceptance of this distinction. :-)

Just trying to understand the distinction :) In these universities, what school would e.g. grant the degree "B.A. in Anthropology"? Does this mean that nonprofessional degrees in this system aren't offered by "schools "?

In my university the B.A. in Anthropology would be a degree conferred by the College of Humanities, where most credits would come from different departments. No School involved in the process. Schools would be dentistry and law, for example.

School is a specialized one, which caters to only the studies beyond UG i.e Graduate and Doctoral one. Schools generally do not have UG studies
Deptt caters to dominatingly UG studies as well ....

You write without any qualifications, suggesting that what you say applies everywhere. However, this certainly doesn't describe the situation in the UK, where the terms "school" and "department" are used essentially at the whim of the university administrators.

-1 for blatantly wrong with regard to many parts of the world.


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What is the difference between a review paper and a research paper?
I have been working on a review paper. After publication, how will it add on my academic research profile? When I will apply for MS or PHD admission, will it count as publication?

A review paper is likely also known as a "survey paper", where you read (i.e. survey) related works in the field and then comment on them. Usually, a review paper should be able to contribute a small amount of knowledge in its own right to the field by providing a taxonomy of work.
Another type of paper that reviews extensively related work but isn't actually a review paper is a "systematic review paper" in which you usually ask a meta-question about the field.
If it appears in a refereed, peer-reviewed journal, then yes, it is a publication. In fact, if done well, these works can often have pretty high impact and can be cited very frequently. However, as already noted, since they don't usually involve substantial original research they need to be augmented with traditional research papers. If a graduate student has only survey papers or systematic review papers, I'd wonder as a search committee reviewer if this student did nothing but read related work rather than working on research.
With respect to MS or PhD applications, I'd think that the fact that you have a publication at all is already a bonus point for you. Most students who apply to these programs don't have publications.

One important distinction should be made between papers in the humanities and the sciences. In the sciences, it would be much more important to have "original research" papers where new ground is broken. In the humanities, by contrast, the act of studying the existing literature and critically evaluating it may, in and of itself, be considered an act of research. (Similarly, in medicine, "meta-studies" in which the reports of various experiments are synthesized to produce overall results and recommendations may also be considered very important, although they augment direct clinical research, rather than substitute for it.)

I have limited experience regarding since I am still a graduate student but from what I understand, a review paper is also a research paper. However, unlike a piece of research, where you study the existing literature, develop research questions and hypotheses, collect data, run experiments/analysis and make inferences which accept or reject your hypotheses, a review article is a summarization and collation of existing articles in a given, specific research topic.
There has been some semi-formal writings on this already namely, this and this. The consensus, so far, seems to be that review articles make fine additions to your publication record but not as fine as articles where you actually did your own research.

I have little experience, because I am still an undergraduate student but from what I understand:

Research paper: A paper in which results and discussion are derived from an experiment.
Review paper: A paper in which results and discussion are not described.

Welcome to Academia SE. I have to disagree with your definitions. A research paper does not need to be based on an experiment (e.g., many mathematical papers). Also, a paper which does not describe (or derive) its results and discussions is just a very bad paper – this has nothing to do with the paper being a research or review paper.

I would describe a review paper as different from a research paper. A research paper is one's original work that may be researched scientifically or otherwise, but a review paper is where someone goes through work already done/researched and gives suggestions as per that field of research. The suggestions would be if the objective, goal, problem were met by the researcher. Whether the research is of value now or in future, solutions to the problem, what is interesting, etc.

Welcome to Academia SE. You seem to be confusing a review paper with a peer review. The downvotes you are receiving are likely due to this, i.e., to  indicate that your answer is wrong. Do not take them personally.


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Does an updated chapter in a book count as a new publication?
I came across one of the edited books where authors contribute chapters that was published once in 2010 and the again in 2014. The two different books have identical (or almost identical) titles but different ISBNs and different DOIs. This means that a chapter that was included in both (same title, abstract and content, unfortunately I do not have access to one of the full texts) is counted as two publications. As far as I can tell, most of the content between the two books is the same.
Is this common practice generally or to certain fields? Is it ethical? How are these cases generally treated?

As a non-answer, but perhaps worthwhile, we could note that literal publication, revised publication, and so on, literally serves scholarly purposes. The potential objection is that this might score status or impact points unfairly. The error here is thinking in terms of status or impact points, especially as a back-forming regulator of permissible behavior.
That is, the real goal is not status/jobs/tenure – although those are serious things – but advancement of human understanding. In particular, rules of the game of status/jobs/tenure are not at all necessarily connected to issues about advancement of human understanding.
In particular, there’s nothing to treat. If some for-profit publisher’s self-promoting “impact factor” somehow counts this twice, this is no serious human being’s problem. The possibility that a corporation’s software misunderstands a new edition is in no conceivable way an ethical failure of people who write parts of something useful enough to be republished in a new edition.

But if you are saying that it is fine why do we seem so concerned about self-plagiarism? http://academia.stackexchange.com/questions/tagged/self-plagiarism

@o4tlulz, the self-plagiarism "concern" seems to have arisen only in the last few years. For one thing, until the last 20 years or so, there was scarcely the possibility of "copy-and-paste", since everything had to be retyped. Also, there was no "impact factor" stuff: it was all more ambiguous. For that matter, any publication was in the old-fashioned way, not really very "public" at all apart from being in libraries, and turn-around took two years, etc. At least in mathematics, it seems to me that there was more focus on substance/quality than "number" at that time.

... but/and the traditional publishers have huge interest in replacing the old processes with new ones that still somehow critically involve them... and surely that's a big part of the impetus to create various "impact factor" machinery. My own university has paid and maybe continues to pay a good chunk of money to one such publisher for some software that supposedly "rates" all faculty... When someone has a chance to make money on an idea, that idea will be promoted, but, of course, with other apparent explanations as to why it's "good"...

Different editions of books are different books and have different ISBNs.  In many cases, chapters don't change that much, if at all.  This is the way it's done - no ethical problems.

Some of my papers have appeared twice, first as "columns" in the Bulletin of the European Association for Theoretical Computer Science, and later in books that are essentially collections of these columns. Sometimes the book version includes some revisions.  Even then, I'd consider these two appearances to be a single publication, and I'd list them as one item in my CV.  I am aware, though, that some people have entirely different policies about such things, and I wouldn't call them unethical.

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How to get acknowledged by the right name even if people assume that they should use a longer formal variant?
I am currently an undergraduate who likes to think about research a lot. My email is “zachary.hunter@university.edu”, however in all my papers I am listed as “Zach Hunter”.
Frequently I will email people about their preprints, asking questions and pointing out slight typos or gaps in their proofs. They typically react very positively to my feedback, and often will put me in the acknowledgements. However, a large amount of the time I get acknowledged as “Zachary” rather than “Zach”.
I think it would be best to always be listed as “Zach” for consistency’s sake. Does this make sense? If so, how should I also about ensuring this?
Approaches I’ve considered
Personally I would feel quite awkward/presumptuous to preemptively say “By the way, if you do acknowledge me, please use ‘Zach’.” I want to avoid asking a “do X without Y” question, but I really want to avoid overselling the value of my comments which are just asked out of curiosity.
Another approach I’ve consider is using the signature “Zach (formally Zach Hunter)” in my first-time emails to people. However I fear this may be a bit too eccentric and not the most clear.
Any thoughts to these approaches or alternatives are welcome.

This also depends on the citation style. I would expect many to name you "Z. Hunter".

@StephanZ. I don't usually see initials in acknowledgements. Maybe that's more common in math?

my field is math. while I see first initials in citations, I have generally seen spelled out first names in acknowledgement sections.

Do you care about this because it bothers you when people call you Zachary, or just for consistency so people are attributing these contributions all to you? In the latter case, I feel you are overthinking it, unless you have a really common name.

Beyond being eccentric, if I saw "Zach, formally Zach Hunter" in an email signature I would assume it was a typo for "formerly" and then get confused about you possibly removing your surname.

I'd go for 'Zach (formerly formally Zach Hunter!)'.

What is your name in your email client? Also, note that acknowledgements are not really counted and mostly not even noticed anywhere. They are a courtesy, and make the person acknowledged feel, well, acknowledged, but they're not going to appear in any official list of publications or contributions so it really isn't important if they call you Zach or Zachary or even Bob.

Couldn't you change you email to zach.hunter@...? and setting Zach Hunter as the displayed name.

it’s a school email, I don’t know how to do that. but I’m looking into that now.

You know you can fix your email application to send emails as Zach Hunter <zachary.hunter@university.edu>, right?

@ypercubeᵀᴹ my university email is connected to Microsoft 365, and it says that I need an admin to change my displayed name. so I’m seeing what can be done on this front.

Do you have an ORCID? Setting your name explicitly to 'Zach' in ORCID and giving your ORCID directly when asked for author details may be one way to do it, since ORCID is pretty standard these days.

@ZachHunter No other email clients can be set up? Hard to believe. And if yes, that'd really suck.

If you want consistency, the solution is to be consistent yourself and not send out emails that present you as either Zach or Zachary. If your emails give people the information that your first name is either X or Y where X is a common abbreviation for Y, they will assume that Y is the legal/formal name, and assume that that is the correct name to use for acknowledgements. And this is what you are doing now by sending your emails from the address “zachary.hunter@university.edu”. So, get your university to change your email address, or create your own email address using a non-university email service.
I suspect that that will largely solve the problem. It’s possible that some people will still assume that Zach is short for something else even without any indications that that’s the case due to a strong cultural conditioning (just like some people from certain cultures occasionally assume my real first name is something other than Dan), but by and large people will go with the information you give them.

Even changing the name next to the email address in the "from" field might already do the job.

@user151413 Not necessarily. A lot of people will assume that if the email address has a more formal/complete sounding name that it must be "official" and use that for acknowledgements.

assume that Zach is short for something else even without any indications Fortunately, Zach is ambiguous - can be Zachary or Zachariah - so if there is no expanded name anywhere then they have no choice but to stick with the stated "Zach". Even more interesting is a name like "Pat" which can be short for Patricia or Patrick - no way to safely guess which one it is and the problem of getting it wrong is far worse than Zachariah for Zachary.

@manassehkatz I don't think most people look for the most formal form of the name they find in an email. It is just that the way people sign off their emails is sometimes less formals (initials etc.) than they would like to be referred to as, so one might pick the name as it appears in one of the formal parts of the email. Moreover in the "From" field said "Zach Hunter zachary.hunter@uni.edu", people would understand that "Zach" had been put there on purpose. And finally, many email readers will not even display the email address by default if there is a name as well.

@user151413 I may not be typical, but if it were me in the exact same situation and I didn't know Zach really well (i.e., well enough to know he always wants to be just "Zach") then I would likely (a) be too embarrassed to ask "what do you want to be listed as"; (b) not actually want to ask out of fear of getting a "don't bother to list me, it was no big deal" response and then being unable to list him; (c) default to reasonable formal name based on email address out of sense that "Zach" isn't likely to be the real, searchable, documented name listed "everywhere".

@manassehkatz If he had himself written "Zach" in the "From" field of his email - a field which every addressee of any message, as formal as it might be, will get to see? This wouldn't be real enough? Really? You'd rather base it on an email address which is formed according to some unknown university rules?

@user151413 Yes I would. Unless it was unclear like zhunt001@university.edu

Does this make sense?

Not really, no.
In all English-speaking countries, it's normal for people to commonly be called an abbreviated version of their name, especially for longer names. Formally, their name is the full unabbreviated version. There is no inconsistency between the two, and no-one native to an English-speaking country or familiar with English names could ever find this inconsistent.
You may prefer that people call you by the abbreviated version, and that's fine. You can tell them that when you meet them, and you can put that in your email signature and on your business cards. But it doesn't make any difference for anything except what they call you when you meet.

What you say used to be the position. But now, in these days of electronic transactions and ID checks, things are changing -- unfortunately. Anyone with identity documents showing 'Christopher' who books into some transactions as 'Chris' is increasingly at risk of being excluded, upon presentation and inspection of ID, as not the person who made the booking!  The machines are blockheads, and sometimes the people who operate them are encouraged, if not forced, to act like blockheads too.

@terry-s For a passport check, that's always been the case. For academic papers, it's never been the case, nor is ever likely to be.

If it was me, I probably wouldn't mention it to them directly. When you have publications and an 'academic presence', you can go by Zach (although Zachary would be slightly more normal). But if some people refer to you as Zachary in acknowledgements, it's fine. It won't hurt you down the line, as acknowledgements don't go in a database and nobody will be confused anyway.
If you happen to be emailing someone and you know their current draft is not final (e.g. they have acknowledged you on arxiv but the paper isn't published yet), you could definitely mention it as an aside. But I wouldn't bring it up otherwise, if it was me.
It's good advice to try to get an email address with your preferred name and always use it in signatures, etc. But again, I wouldn't worry too much if this isn't possible.

I don't see a solution, since you want to use something non standard for scientific/academic work. Most people prefer a more formal name rather than one less formal. I'm Buffy (no not really) but everyone IRL calls me Buff (ha ha). But for any formal purpose most people who haven't been told otherwise will default to the formal version.
I think that if you really want to be Zach then you need to keep informing people of it. If you want a non-default solution then you need to be vigilant about it. They aren't going to grok it on their own.
Alternatively, since you are still at the beginning of the academic journey, you could, perhaps switch to the formal version for formal communication. Even my university email signature (applied automatically) has the formal version of my name.

Thanks for the insight. I realize that it is non-standard to use the less formal name. I intend to stick with Zach though.

You could also ask a court to make the change formal, though people will still think "Zachary", unless you are a famous internet cartoonist

@Buffy Zach Braff achieved the same as a movie actor.

I've seen people get everyone to refer to them by an informal name - even the strictest style guide wouldn't refer to Bill Clinton as William, Joe Biden as Joseph, or Ted Cruz as Rafael. Of course, it's more difficult if you don't have a few million dollars to spend on billboards bearing your preferred name....

@mjt William, Joseph and Rafael are the first names used to begin Wikipedia's articles about those three people; certainly in some formal contexts their formal names are still used.

Is it possible that you just see a problem where there is none? Do you really need to seek consistency or perfection in this matter? You seem to be OK with people using the short form of your name, then why worry when people use your legal first name?

This seems non-responsive.  It seems pretty clear what the OP's goals are here.  "You shouldn't have these goals" isn't an answer.

@ScottSeidman : No, it is not clear "what the OP's goals are here". The OP wrote: "I think it would be best to always be listed as “Zach” for consistency’s sake. Does this make sense?" And my answer is "No, it doesn't". So, clearly, the OP is not quite sure if he should do something about this matter at all. Therefore, I respectfully disagree with your comment.

In business (at least at the academic hospital where I work) I usually look at how an email to me is signed to choose a response name.
So if RobertEatonSmith@fancy.edu writes to me:
"Can you send me a copy of the NPO guidelines?
Bob"
I know how to respond.
And when someone writes to you as Zachary, respond as Zach.
The second time: "Please, just Zach -- only my mother uses Zachary"
And these days we also have pronouns to list and check, so being pedantic about your name is not a big deal.

I think the downvotes may be because you've misunderstood the issue. The question is not about the response in emails, but about public acknowledgment in papers. I can certainly see someone responding to the email using the shortened form of the name thinking that Bob/Zach uses an informal tone in emails, and then using longer and more official-sounding version of the name in the formal publication.

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Do GRE verbal scores matter for graduate admissions in mathematics?
For the next 6 months or so, I plan to study hard for GRE. Since I don't have much time, I plan to ONLY study for the mathematics portion of the test as I would like to score at least in the 90th+ percentile for the Mathematics Subject Test. But in order to have the capability to achieve such a task within my time frame, I plan to spend no more than 3-4 days to study for the analytic writing and verbal reasoning portion of the general test.
So my question is: Do graduate schools focus or take into consideration the (possibly low score for the) analytic writing and verbal reasoning portion of the test if you were to score high on the mathematics part? Advice from those who are familiar with how selection committee of graduate schools (in Mathematics) pick applicants would be great!
Some clarification: I feel as if I was not too clear with my question. By "studying hard" I don't mean to sit down and just study "specifically" for the GRE test but rather to enhance my knowledge in Real Analysis, Abstract Algebra, Topology, and Differential Equations among other topics such as Set Theory and Logic. GRE Mathematics Subject Test will be something that I will be preparing for along the way. My reason to spend ~6 months has nothing to do with scoring high on GRE. I will perhaps spend no more than 1-2 weeks reviewing the Princeton Review. I just don't know if I will have much time to work on my writing skills if I'm deep-neck into learning Mathematics.

You are wasting your time. GRE is just a test. If your goal for going to graduate school in mathematics is to do mathematics, why waste the time test-scumming when you can use that time to do mathematics? If your goal for applying to grad schools is different, do not apply to the grad schools.

@BorisBukh You make a good point. I am, however, not going to take the GRE for the sake of scoring high on the test but rather to learn mathematics. For me, taking the test is nothing more than an excuse to study harder.

Are you talking about the quantitative reasoning part of the GRE general test (as opposed to the mathematics subject test)?  I find it hard to imagine any circumstances under which spending six months studying for it would make sense.  The quantitative reasoning section doesn't involve a lot of sophisticated background (basically high school math).  Most applicants to math grad school do very well on it without little or no practice.  For those who don't, I tend to think it's because they don't take standardized tests well, not because they don't understand the math.

If you haven't done well on standardized tests in the past, it's certainly possible that you might increase your performance by getting used to them, but spending six months doing so sounds terrible.  My gut feeling is that it could be worth taking a few practice tests and thinking about strategy, but six months of your life is a huge amount of time.

@AnonymousMathematician I'm not too familiar GRE. When I said Quantitative Reasoning, I actually meant the GRE Mathematics Subject test.

OK, that makes more sense.  I'm still not convinced it's important enough to be worth six months, but at least there's a lot more mathematics on the test (and therefore more to learn from studying).

@AnonymousMathematician As I said, it is nothing more than some excuse for me to study that much harder.

Parkinson's Law suggests otherwise. In the real world, none of us are given the opportunity for unlimited time. Time should be used as efficiently as possible, regardless of whether we choose to go on into private work, research, or teaching. Spending 6 months to study for a test is a waste of time. Trust me, I've done it. Take 2 months, tops, and give it your best.

I also am of the opinion that spending 6 months studying for the math subject GRE is not a good use of your time.  The majority of this test is on relatively elementary mathematics (calculus, linear algebra, differential equations).  These are of course fundamental and important, but they aren't the subjects that will make or break your mathematical career.  Higher subjects like real analysis and abstract algebra are much more important.  You can get through a lot of grad school just knowing the basics of differential equations, but if you aren't strong on real analysis you're sunk.

@Nate: While over 50% of the GRE subject test is on calculus, linear algebra, and differential equations, the GRE subject test also contains questions on abstract algebra, number theory, point-set topology, geometry, and real analysis. You've just said that these last topics are invaluable for graduate school. So maybe the question is: which part of the GRE subject test should the OP study for?

Yes, a decent verbal score is definitely desirable.  I mean it: I have done graduate admissions for my math department, mentioned low verbal scores as a point against the applicant, and had the point taken by the rest of the committee.  But I would think that spending three-plus years in a university would be the best possible way to study for the GRE verbal: if after all that you need separate study in reading comprehension, sentence completion, and so forth, something has gone wrong!
(I remember the GRE as the SAT all over again, to the extent that my GRE scores were each within 30 points of my corresponding SAT scores.  The GRE has been retooled multiple times in recent years with the unfortunate effect that a lot of people doing graduate admissions, like me, are now a little vague on what it actually contains.  We tend to assume that the changes are cosmetic and that the exam is more or less the same as the one we took years ago.)
The math subject GRE is not a hard test in the sense that you need to devote much (or any, necessarily) time to study for it.  I remember contemplating studying for the Math GRE (circa 1997), learning that the study guide was really pretty miserable, and maybe spending a weekend flipping through a book on differential equations because I had never taken a course on that.  More pertinently, I remember that at least one third of the test was rendered trivial by my deeper study of subjects like topology and analysis: e.g. I think there was a question like "Which of the following properties does the real line, as a topological space, not have?  Hausdorff, compact..." To me this read more like a mathematical joke than anything else.
Here's the bottom line: please don't spend six months only, or even primarily, studying for any/all of the GRE.  What a terrible waste of your time.  If I am honest, the fact that you think this might be a good use of your time makes me concerned that you might not be a good candidate for a graduate program in mathematics.  I would not say this if you provided any distinguishing or identifying information whatsoever, but as you are completely anonymous it is something to think about.  The way you prepare for graduate school in mathematics is by learning math.  That means absolutely mastering truly basic, undergraduate level topics like linear algebra and deepening your knowledge of algebra and analysis.  This knowledge and mastery will serve you well at every step of the graduate process, starting with admissions.

Hi Pete! just to let you know about the actual GRE changes, since I took the Revised GRE when it came out. Scoring scheme is now 130-170 instead of 200-800 (why this was necessary or even helpful, I have no idea). The biggest issue is that a 130 is the arbitrary zero that was the old 200. Saying I got a 165VR means nothing to most people (It was actually 95%ile). I think the Writing Section probably has changed the most. All the prompts are provided to test takers online now, so you can actually practice them beforehand.

@Compass: Thanks.  That's about how much I know.  Because the new raw scores are so unfamiliar to us, we look directly to the percentile scores now (which is not a bad thing: probably people should have been thinking in those terms all along).  When I was involved, the writing/analytic score was not much used [although perhaps by the Graduate School in the computation of an "academic index"]: we don't know what it is, and anyway we get a writing sample of our own.

Yeah. As long as it's above 3, I would honestly interpret that as "You can write! Hooray! And no one edited it or spell-checked for you!" A 6 vs a 4 (as someone who magically got a 6) will most likely produce the same quality of written work given a reasonable amount of time to actually write.

Hi @PeteL.Clark, your sentence "spending three-plus years in a university would be the best possible way to study for the GRE verbal: if after all that you need separate study ... something has gone wrong!" made me a bit worried! I'm not native speaker but finished my masters in Europe and lived here for more than 4 years, studying, working and living all in English but when I saw an online practice sheet I did not know almost 90% the words! All my native friends tell me that even natives are not familiar with some words in this GRE exam! (I have never taken actually)

@kasramsh: I meant that to apply to native speakers of English (and especially American students: the GRE is an exam for American grad school).  If you are not a native speaker of English, you need to take the TOEFL.  If you have a good TOEFL score, a poor GRE verbal and are studying something STEM-like, you should not get dinged too much.

As a graduate student you will have to write a thesis or dissertation.  Your communication skills are important!
When I'm evaluating applicants to our graduate program in mathematics, it goes without saying that the applicant had better have a very high quantitative score and anyone who doesn't isn't going to be a desirable applicant.  What separates the desirable students from the undesirable students are reasonably high scores on the other sections of the test.
Keep in mind that students in many disciplines take the GRE.  I don't expect a mathematics student to be as good a writer as a student in English, but if the student has a ranking in the 10th percentile, I've got to wonder whether that student will be able to write an acceptable thesis without me doing a lot of editing.

+1, except I'm not completely confident that (say, American) students who go on to grad school in the humanities score better as a group on the GRE verbal than those who go to grad school in STEM fields.  I might suspect that the latter group does a fair amount of reading and writing too, whereas their much greater exposure to problem-solving challenges and timed tests in a university environment might confer an advantage.  (I would expect humanities students to do better on the analytical writing part.)  But I don't really know; probably someone has looked into this!

@PeteL.Clark: See https://www.ets.org/s/gre/pdf/gre_guide_table4.pdf for GRE score distribution by major.  It turns out that students in the humanities do better on the verbal section, but not by nearly as much as science (and especially math) students do better on the math section.

My fairly extensive anecdotal experience is that "verbal" scores are harder to "cram" for, perhaps harder to "game", than the math subject test and "quantitative" exam... so that, perhaps oddly, a high verbal score seems to be a very positive indicator of future success, while subject test success has a more limited indication.
Lowish verbal scores, even with high Subject test scores, seem to be correlated (again, extensive-anecdotally) with a certain brittleness moving forward into PhD-level mathematics, ... perhaps after considerable success in lower-level mathematics. (We can observe the substantially non-verbal, nearly cryptic stylized form of much low-level mathematics.)
So, yes, some people on admissions committees (e.g., me...) pay attention to those other numbers. On the other hand, it's not at all clear that these things can be "studied-for", much less studied-for for several months.
As Pete Clark noted, learning more sophisticated mathematics is often far more effective at more-than-gaming the system, since quite a few of the prankish-shallow questions that would stump novices are transparent to a person with some experience, perspective, and context.
Even so, self-coaching about how to take a timed, multiple-choice test, and some prior samples, are surely helpful to best represent one's knowledge of the subject matter. And being rested, not over-caffeinated, not hung-over, etc. Despite the potential silliness of the last observation, I have observed many people disserve themselves by putting themselves into bad physical states for these and other exams... If diagnosable anxiety is an issue, it should be dealt with forthright-ly...


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Do research grants from USA governmental agencies (e.g. NSF, NIH, DOE, etc) require that all of the PIs be affliated with a university?
or to other research organizations for example government labs?
I am currently a post doc at large and would like to co-write a proposal (probably NSF) with a Professor at a nearby University. With the funding, I'd be getting a salary and doing the majority of the work and the lead PI (the prof) would work partial time and time in the summer.

Related (possible duplicate): Does the NSF support researchers with no academic affiliation?

Every US funding agency has its own rules, and most agencies have many different types of programs with different intentions.  For most (maybe all) agencies, this includes both funding to universities and funding to corporations, particularly under SBIR programs.  Some agencies will also fund individual consultants directly for various specialized roles, but that tends to happen mostly with rather senior individuals.
Your options are even larger if you are not the PI, however, but a co-PI (I think this is actually what you want to do).  For most agencies and most funding vehicles, the PI's organization can subcontract work with a fair degree of freedom.  Also, there is only one PI, from the point of view of the contract: it doesn't matter if you call all the leaders PIs, the government is going to negotiate with one organization per contract, and that organization is going to be asked to designate one person be the PI, and in practice everybody else is co-PIs.
For you, then, there are three main paths to take:

Propose, with the professor as PI, under the plan that if funded you will become affiliated with the PI's university
Propose, with the professor as PI, where you will be contracted as a consultant.
Set up an LLC, from which you can propose as PI, and subcontract to the professor.  You'll have to comply with government contracting rules, which are painful, but much less so for SBIRs.

Number 1 is probably the best, unless you have some reason to avoid affiliation, in which case #2 is a good alternative.  #3 doesn't have much advantage unless you intend to apply for SBIRs, and is still a pain to get started.

See the NSF web site at:
http://www.nsf.gov/pubs/policydocs/pappguide/nsf15001/gpg_1.jsp#categories
Individuals don't generally apply directly for NSF funding.  You could apply for certain grants as a non-profit or for-profit corporation, but the funding opportunities for these are limited.
The most reasonable way for you to work this would be for your colleague to submit the proposal through the prof's university with an arrangement where you'd become an employee of the university if the grant is funded.  It's also possible for the prof to submit a proposal and budget for you to work on the project as a consultant, but it can be harder to get such an arrangement approved.

In the document you link, point 5 says that unaffiliated individuals can be proposers. So I'm not sure your answer matches with the NSF document. Thanks for pointing me to that though. I couldn't find it with my google searches. And if I'm a Co-PI with a Prof at a major research university, then that seems even more likely.

Notice the second requirement "The proposer agrees to fiscal arrangements that, in the opinion of the NSF Division of Grants & Agreements, ensure responsible management of Federal funds."  I think you'll find it very difficult to satisfy this requirement.  I've edited my answer to correct this.

You should read the guidelines for the program you are applying for to see who would be eligible in that program. My guess is that you may not be eligible to be PI, but possibly co-PI.
Also be aware that success rates are pretty low with NSF and many governmental agencies (typically 5-25%), so don't count your salary before you get funded. It is a competitive world out there, so have many backup plans.


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What is the average salary of a life sciences post doc in Singapore and what is the average living cost there?
I am from India and I am about to submit my PhD thesis (Biotechnology) and considering for a post-doc in Singapore. Can you help me know what is the average post-doc salary in Singapore in an institute like NUS or TLL? From my contacts I have come to know that the cost of living in Singapore is quite high. Please guide me what would be the average monthly cost of  living for a family of 3 (me, my wife and an infant)?? or Should I look for a post-doc position in any other country like USA, UK, or anywhere in Europe?

I usually consider this site, but I have no idea if it is accurate for singapore.. http://www.numbeo.com/cost-of-living/city_result.jsp?country=Singapore&city=Singapore

I have found that a good general source for salary information in Glassdoor.com: everything on it should be taken with a grain of salt, but it's a good starting point for getting a general sense.  Searching there at the moment, postdocs in Singapore seem to be reporting around $5K/month.
Combining that with the cost of living estimator recommended by Fabio Dias, it seems to be survivable, though you'll likely not be saving much.


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Humanities - taking a year off between PhD completion and academic job
I am a PhD candidate in literature, finishing my degree in August. Due to a combination of factors, I did not line anything (academic) up for the coming academic year. However, I will be spending that year on the job market. I had planned to simply teach a couple of courses if possible, and to work on getting some publications out, and attending conferences where possible. This would make me a bit of a drifter for one academic year, and I am wondering how that would reflect upon my qualifications while applying and (hopefully) interviewing for academic jobs. Essentially, I want to stay active in my research, but I won't have the banner of a university name under my own...
The reason I'm crowdsourcing this is because I'm getting conflicting information. One of my committee members tells me that it's better to have the PhD in hand while applying, so I should finish up ASAP. He also assures me that a PhD still looks "fresh" up to two years after completion, so I shouldn't have a problem. Another member, however (who is perhaps more familiar with the current job market climate) has informed me that a gap year will ruin all chances of employment, and that any period of wandering institutionless - no post-doc, no fellowship, no teaching - would be fatal. He suggests that I hold off graduation, so that I have no in-between time.
Do any of you out there have any thoughts? Or similar experiences?
Thanks for any responses you have.

How do you know the gap will only be a year?

I'm happy to contribute an answer to this if you address my comment.

Sure, I honestly wasn't quite sure what you meant, and answering to the best of my ability took a bit more thought than I had at the time, but since I have a moment now I'll go for it. A year is the length of time for which I have not scheduled any post-docs, fellowships or teaching gigs, and since I did not go on the job market this year, I certainly will not have a professional academic position - tenure track or not - by the fall of 2015. Of course, the break could end up being more than a year if my job search for 2016 goes bust, but that would be a misfortune, rather than a plan.

Did you apply for an academic position and fail to receive one? Second-time applications are different from first-time applications.

No, as I said, I have not applied to anything yet.

As you said? "Did not line .. up" does not mean "did not apply".

I'm in the humanistic social sciences. If you were my doctoral student, I would suggest that you delay depositing your dissertation. This is even though there is considerable pressure from my institution to hurry students out (part of the NRC university rankings is time-to-completion so the provost puts pressure on faculty in this regard).
If you can afford the continuous registration fee and the university does not put onerous rules to make life difficult, then there are many more pros to cons.
Pros:

You can work on your publications as if you are a post-doc.
Applying for jobs is a full-time job
You still get to use your university letterhead
If you don't get any jobs this year it isn't as apparent that you're "stale" next year

Cons:

Your advisor may be under pressure not to allow this.  It could impact her/his ability to recruit new doctoral students until the old ones graduate.
Your university may not allow this
Your university may charge continuous registration fees

Notes:

Your advisor will have to write in his/her letters that your dissertation is essentially finished. Everyone is familiar with this strategy so it's not a red flag.

Another pro is that some fellowships require you to be within N years of graduating. By delaying graduation these clocks would not start counting yet. Another con is the  psychological factor of not having graduated.

That may be in an ideal world, @shane, but in reality once people graduate they may find it's difficult to access the library system, they start to lose focus as they work (or seek work) outside academia, etc, -- and as a result, stop publishing.

If you decide to graduate, you should get some sort of affiliation with a university, even if it is teaching a course or two as an adjunct, or getting a visiting scholar or some such other non-paid position. Besides other, more noble things mentioned above, you need university letterhead for your letters of application. They look terrible on personal letterhead.
Considering how the job market is, you will most likely spend a year or four without an academic post, even if you deposit a year after you've actually written. Unless you're a rock star from the best program, etc.
And last, but not least: Being on the job market (this is my second year, PhD in literature), takes up most of your time, if you do it right. You will have little time to focus on real work, unfortunately. So, don't think this is going to be like the time spent on the dissertation. Instead, you will be writing and rewriting dozens of rather formulaic documents, researching programs and their needs, and writing dozens of potential syllabi to submit with your apps.
Hope that helps.

Trailing spouses often have this problem.  Here's how I've seen them address it:

continue working as though they were doing a postdoc, building up the publication list
get an office in some institution, as a courtesy -- this is a great way of staying fresh because you attend seminars, participate in stimulating discussions, stay connected and fresh

I also like your idea of doing some teaching -- for the income, for the experience, and as a CV builder.

Thanks specifically for this comment - I actually am a trailing spouse - and my husband has a wonderful job in a wonderful city in his field, so that is largely why I did not scramble to find a position immediately after completing my dissertation. This is also why I'm hurrying to finish up - because I am no longer at my home institution and writing a PhD from afar is actually quite a bit more difficult (I have found) than doing it in the context of a nurturing and dynamic department. Quite a bit is lost without that network of support.

When you are accompanying a spouse or an advisor on sabbatical, it is much easier to get an office somewhere than if you are completely on your own.  It is nice to have an office to go to every day, and have somewhere to leave your coat, lunch, boots, etc., when you want to attend a seminar.  And it's nice to have people to talk to about your work and their work.  Also keep in mind that it can be stressful to finish a dissertation while working or job hunting.  There's nothing wrong with doing things step by step.

I can't speak to the general predicament that is the dismal academic job market. I completed my PhD (in history) and was underemployed for several years until a very good research university offered me a temporary appointment. By that time I had amassed a solid, if unspectacular, publication record. Since then, however, I have found nothing and so split my time between writing and cutting grass. Good luck.

The only context in Humanities where I can imagine that a year or three of employment gap is noticeable would be if you graduate from The Best Program Ever where absolutely everybody -- except you -- gets multiple offers. If the dissertation is defended, revised and ready to go, and you can afford to pay tuition in some future term in order to deposit, then it might be harmless to delay depositing, though there are risks associated with getting "scooped" if someone else is working on a similar topic.


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More co-authored than solo papers in the Humanities
I am halfway through a PhD in History in the UK, in a highly unusual subfield. As my competences are quite rare, I have already been asked to help out with, and be a co-author of, two different papers with postdocs/professors in other areas of the Humanities. The results are interdisciplinary articles that I am quite happy with. I am also writing an additional article with a fellow PhD student (I will be the first author there).
As I am only now finishing up my first solo paper, I am concerned that having more co-authored papers (3) than solo ones (1) will hurt my CV when I apply for postdocs/jobs. Will institutions look down on me for co-authoring more papers than the norm in the Humanities?

I am not in the humanities (rather, in math where solo papers are still the norm), but in my opinion it is not the percentage of coauthored papers that could be problematic but rather whether all of your papers are coauthored, and (worse) coauthored with the same senior people.  If you have one strong solo publication, then at least in my neck of the woods that would allay people's worries.

Thank you for your comment. The three papers have only one other author each; these are three different people and none is my advisor. So hopefully that is not problematic!

Do the articles specify the author's contributions? If so, it would be clear what you did, and how your unique skills are a good asset for whomever wants to hire you. (But I am not in humanities, so I don't know if they will be seen like that by most people).

In the UK, up until last year, hiring for lectureships was all about the Research Excellence Framework (REF). Going forward, hiring will likely be all about the REF. We just made two hires in my department and the keys questions were what did the applicants look like for the last REF and what might they look like for the next REF.
Co-authorship in my field is the norm and for the last REF where on the authorship list you were did not matter. I am pretty sure this was true across all assessment units, but you should check with someone in your department. For REF 2014, the same paper could be returned multiple times if the authors were spread across multiple universities (and possibly even multiple units of assessment). For REF 2020, we do not know what the rules will be. Potentially, they will attempt to assign partial credit to publications or only allow a paper to be returned once, but this would be hugely messy.
If REF 2020 devalues co-authored papers in History, and by 2020 you won't have N (last time N was 4, but could be reduced for new lecturers) single authored publications, then the joint publications will be looked at unfavourably.


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Is a faster implementation of an existing algorithm publishable?
So a paper exists, it was published 3 years ago and had a novel algorithm (more or less, it's in the area of finite-difference time-domain simulations).
I've taken the algorithm and accelerated it by a factor of 100x (example, I don't have the true number), producing the same results in the end, but providing an opportunity to essentially simulate more (iterations/objects) in the same amount of time.
The methods used to accelerate it aren't particularly novel, though some aspects might very well be a bit different from mainstream ideas. All in all, a person set out to do the same thing would probably be able to do it, but I would not call it trivial. However, I know that this has not been done before.
Is this something worth publishing? I am going to ask my supervisor, but he's been very busy lately ( >.< ), I haven't been able to catch him for ~4 days. I would like some of your opinions.

Did you make an algorithmic improvement that improved the asymptotic complexity (from e.g. O(n^2) to O(n*log(n)), or simply write a highly tuned implementation of the same algorithm?

@BrianBorchers, it depends if you consider parallel implementations a change in complexity (I think of it that way, but I don't know if that's an accepted view). I think the time complexity has changed because it scales differently with n now.

Also I should mention, the algorithm is implemented in simulation software, so I think there are people who would like having my version, but I don't know if it should be published.

@Alexandros, first of all, GPU. Secondly, examples. I'm not looking for technical criticism here, just publication advice.

@Mewa Such papers are publishable, and that's from personal experience. My very first paper used high-school math (Gaussian Elimination) within a context (homography estimation in computer vision) where the use of the expensive SVD decomposition was all but standard and we got a massive 70x speedup over the state of the art in OpenCV (the popular computer vision library) while not damaging accuracy too much, making it possible to run real-time on mobile phones and embedded platforms. The paper was published in CVPR Workshops 2014 this past summer!

From personal experience, such results are absolutely publishable.

If I understand the question correctly, the dilemma is whether to just distribute the code or whether to also make a scientific publication out of it.  The way that I typically think about this type of problem is to see whether it passes any of the following tests:

Does the improvement enable a significant scientific or technical work that was not previously possible?  For example, if faster simulation allows a control loop to be done in realtime that couldn't before, that advance may be scientifically valuable even if the methods are not interesting in and of themselves, but you have to demonstrate that value.
Does the improvement make a qualitative change in the operation of the algorithm which is interesting, e.g., changing a scaling property that was previously a limit?
Is the mechanism of the improvement interesting in and of itself, e.g., such that it teaching something about the nature of the algorithm or such that it might be applied to other algorithms or problems as well?

Any of these is a good reason to publish an improvement on an algorithm.

Thanks Jake! That makes sense. I think it fits (1) and (2) fairly well. Not sure about (3) so much, but I'll definitely take a closer look. Maybe it can be useful for other FDTD simulations.

@jakebeal answer is spot-on, but I will add my extra two cents. As you said you parallelized the algorithm, which is good but how did this happen?

Was the algorithm already parallel and just has not been implemented that way? If yes, simply parallelizing the implementation might not be good enough.
Did you used other additional optimizations to make it efficient? For example did you use SIMD (SSE, AVX) instructions or GPUs for your implementation?
As jakebeal said, did you alter the scope of the algorithm? If the algorithm could handle e.g. only small graphs up to a size, with your implementation it might scale to much larger graphs.
If, for example you worked on an indexing method, did your method improved the building of the index or also improved the index's query performance?

The most important thing to consider, is that you need to write a full paper to present your improved version. So, if all you can say is "I parallelized the algorithm with OpenMP and is now faster" or "I vectorized this loop" and other technical details, this will not be good enough for a scientific paper. On the other hand, if you worked on advanced techniques (SIMD, GPUs), your work might worth a publication. Still, it might not be good enough for top-algorithm conferences (where new algorithms are usually presented) and might be more suitable for conferences focused in parallel algorithms, implementations, which are more focused on the technical side of things. Also, I would worry about the fact that no one touched this algorithm for 3 years. Are you sure there is not another algorithm that is now the state-of-the-art for this particular problem? You should look into this too.
Update: Since you already have a done a GPU-CUDA version of this algorithm, it would be interesting to actually extend your work on plain multicores with a) OpenMP (that would be trivial) b) OpenMP + SIMD (that would be harder c) or OpenMP + SIMD + partial CUDA. Having several tuned versions of the same algorithm for different architectures and performance benchmarks for the different versions, would make a much stronger paper.

Thanks, Alexandros. I don't want to go into too much detail, but basically:
(1) No, it wasn't. It's a very sequential implementation.
(2) I used a GPU (CUDA).
(3) Technically it can simulate greater number of nodes now. Also I think 3D would be more feasible (it's 2D right now though). I haven't tried 3D yet.
SIMD is an interesting idea (I've done it before on microprocessors), maybe I'll try that too. I'm not sure why it hasn't been moved to GPUs yet, but I talked to the authors in June (in person) and they were still working on it then. It's not that big of a deal if it isn't published.

Continued: It is part of my MSc thesis, so if it just takes up a chapter, that's ok too :) I thought publishing might be nice though. And yeah, I was going to go for some parallel processing group rather than algorithms. Maybe something like IEEE PADS.

You could also try Euro-Par.

@Mewa See my edit

Regarding different platforms, it depends on the target audience. Most computing clusters I have access to have CUDA enabled cards, so that would be enough. If you want users to run it on their computers, OpenCL is better, because it can run on CPU too.

One option that you have is to submit a paper to a demo session of a conference. Such papers usually describe existing systems so they don't have to be new. If you are accepted, your paper is published in the proceedings, and you have the right to present a live demo of your system in the conference. If your improved implementation indeed makes 3D possible, you may have a very impressive demo.

How is your code faster than the state of the art? If it's faster only because you're a good programmer, you're unlikely to be able to publish in a worthwhile venue. If it's faster because you did some computer science, you might be onto something.

Nice, I'm a professional programmer and I just read all the other answers thinking, "what? I optimise code from time to time, never occurred to me I could get a paper out of it!" :-)

@SteveJessop If the scale of improvement is outrageously large enough and the software is relevant to the scientific  community, a paper combined with an opensource implementation can be worth trying. In such a paper, be prepared to explain the design decisions and demonstrate you have not lost something for all that speed. It's fun when your implementation becomes the gold standard.

That's fair. I am going to talk to some CS people (we share the floor, so I don't even have to walk anywhere!) and see what they think. I was thinking this would be more appropriate to publish in the area for which the algorithm is used rather than CS/algorithms/even parallel programming to some extent.

Also, obviously I attribute the fact that I get anything working to the aspect of me not being absolutely awful, but I would have thought migrating to a different hardware (GPU in this case) would go a bit beyond the normal optimization (unrolling loops, inlining, etc).

@Mewa Maybe, maybe not. Porting code from PC to Mac wouldn't be a paper, for example.

I have also published some papers in the same vein.  If you can find something novel about your implementation (significant changes to the algorithm, novel optimizations, new insights about the architecture, etc.) then you have a better chance of getting published.  If you only achieved the speedup by parallelizing the algorithm in a straightforward fashion, it will stand less of a chance at the higher tier conferences.  5 or 6 years ago when GPGPU programming was still very new, people were often publishing papers about GPU parallelized algorithms.  This is becoming less frequent now, because many of the fundamental concepts about this process have already been explored.  Much of the low hanging fruit in that area has been picked, so reviewers will tend to view straightforward parallelization of algorithm "X" as not very novel.

I'd say simply write a paper, submit it at one of the top venues in that area and let the reviewers decide for you. If it was rejected they will suggest the changes that could get it accepted in the following conference.