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Things to focus on in a model lesson
A model lesson is a usual element in interviews for the faculty level positions. Normally this is not a full lesson but a 15-minute version which is performed in absence of actual students for just a few professors from a hiring committee. It is supposed to demonstrate "your teaching style", but by design this is clearly a different enterprise: you should "act normal" doing "the same" things

in a different time-frame,
for a different audience,
with completely different motivation and
under exorbitant cost of failure.

Having said this, I also acknowledge the model lesson as indeed a much needed element of the interview, which helps to assess a candidate's set of relevant skills.
The question is how one can ideally prepare to give such a model lesson. Putting aside obvious things like "structure of the talk," "clear slides," "projection of the voice," and "body language", which normally should be already trained by experience, are there specific things that should be taken into account for the model lesson only? What about techniques like jokes, questions to the audience (e.g. how many of you are familiar with the definition of the derivative), work in pairs, which you probably use in a real classroom — is it a good idea to demonstrate them in a room full of senior professors? I am a little confused.

May I ask: is this a common scenario in Europe?  In my experience, in the US: (i) if you are applying for a job at a research university you will give a research talk only; (ii) if you are applying for a job at a teaching/liberal arts college, you may still give a research talk, and you will probably also teach a class, but a real class: i.e., of full length, and to actual students.  The format that you describe seems so artificial so as to select primarily for people who can get past its weirdness.

It is quite common in the UK, afaik, since they are very much in the "teaching & research" mode. I can not say for the rest of the EU.

@Ben: That's interesting.  I have little direct experience with CC's except that both my parents taught in that system (in English departments).  My father's department was enormously large (over 100 faculty, I believe), so I can imagine that the hiring process needs to be streamlined compared to what I am used to.  Do your 15-minute teaching segments involve actual students?

I did this in Sweden, and student representatives from various levels were in the room. They were primed to ask common student questions.

I have also experienced this in Switzerland, the audience consisted of the hiring committee, but student representatives were present also (and/or were part of the hiring committee).

Having done this, I'd advise:

Take it really seriously. In places where candidates are judged equally on teaching and research, the model lesson could really make the difference. Strong researchers may neglect it, relying on their publication/citation record.
Make sure you prepare for the expected audience (in my case, 1st year students), not the actual audience (academics).
Feel free to use techniques you would use in a classroom, but then use "time jumps" to indicate that the activity has taken place. The problem with this is that if you have follow up questions, there may be no answers and the lecture may fall flat.
Don't forget "learning objectives" and "lecture structure" up front, and other guidelines for students throughout (though you probably can only show one such thing).
Practice more than you would practice for an actual lecture.
No corny jokes. If you cannot tell whether a joke is corny, then assume it is. In fact, beware of jokes. Relying on natural humour is probably better.

@PeteL.Clark ...just like real teaching, no?

@JeffE: Maybe.  Remind me to end my next lecture with "and.... scene."

I participated to this kind of interviews, as an applicant as well as a committe member. For the exemple, I will assume that you are applying to a position as a maths teacher.

As Dave Clarke mentioned, prepare for the expected audience. If your are expected to teach to maths major in a very good institution, it is not a big problem to show off your skills by lecturing at a level a little bit above the expected audience's level. But avoid this if your expected audience is notoriously weak or non maths majors. I got rejected once because I was "too good" for the position.
To prepare the lecture, you should study the curriculum of the institution you will be teaching. You usually can find it on the institution's website. It is important since it helps you to do the lecture at right level, but also helps you to connect your lecture to other topics (especially when your expected students are not maths major) studied by your future students. It will make you more comfortable for the questions that usually follow the interview.
Only do things you usually do in class. An interview is definitely not the place to experiment a new teaching method. Last month, a candidate with an impressive CV failed an interview in my institution by trying to use a computer and videoprojector, thing he obviously never did before. The result was pityful.
Make sure your connect the lecture to the lectures sequence of a real course. So, take time to tell what students should have studied in the previous lectures, and which problems (related to the current lecture) they will solve in future lectures. This is something you probably already do in a normal lecture, but it is especially important here since the committee wants to know if you can organize a complete course.
But putting your lecture in context does not mean reviewing the (expected) previous lecture, you have no time for being off-topic.
I would not prepare a joke, as if it was a stand-up comedy. But, if an opportunity to make a joke, I would take it in order to make a more decontracted atmosphere. Beside hiring the best teacher, the committee wants to hire someone who they feel comfortable to work with. To sum up, your goal is to appear as a reliable, professional, open-minded and with team spirit person.
Even if I do it in class, I would not prepare any activity where the audience participates -or only a very short one-, since it takes too much time (except for a foreign language teacher interview). But I would try to interact as much as I can with the audience through questions.


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Should I apply for a PhD position with required programming skills which I do not have?
I did my master's thesis last month and have seen one excellent PhD position in my field. The title and the project description was very close to my master's thesis. My master's thesis relates to one of those standards which is very new, and I can guess the number of peoples which work on it are few -- especially those persons which did or are doing a master thesis in that field.
On the other side I got my degrees with honours -- both bachelors and masters. So I have good situation for that PhD position.
One of the requirements is strong programming ability, which I do not have. I am not so good in programming. (By the way in just 6 months, I can improve that). Also the place is top five (or maybe one) rank with high salary. I do not know whether I should apply for that position or not? I afraid my bad programming skill have a bad effect on advisor's decision about me.
What I should do?
A part of requirements is

... very good programming skills and experience....

which I do not have.
Also the professor is number one person in that field and kind person. So that is one of the most important opportunities in my life. I do not have those skills which are required to apply to the programme. But by that time, I will improve my weak points.

I do a PhD where 95% of the work is Matlab programming. In the lab, we are around 10. Almost nobody knew Matlab when they got accepted, even if practically all the work is done in Matlab. Try.

@AnderBiguri thanks for sharing that experience.

@AnderBiguri perhaps the requirements are to prevent bad software quality. If the OP applies, he should make a big effort to upgrade his skills before starting the position.

@TemplateRex Definitely if he applies he should work very hard into getting those skills upgraded, however he should try.

The answer depends on the position. I disagree with a lot of the answers below. I don't agree that it's boilerplate. If I advertise for something that specific, I want that thing. I don't agree that requirements are lower than industry. I do numerical modeling. I want someone who can code like a champ and understand the science for some projects. If that's the case, maybe move on. If not, apply. If unsure, maybe ask the professor.

I am not sure I agree with Enthusiastic Student. There are two points to consider here:

Do they really need a strong programmer, or is this just something that they traditionally write into their position announcements without giving it much thought? Frankly, in industry like in academia, job descriptions are often given much less thought than people seem to assume. In my old group, we basically had one boilerplate job requirements text which was used for all kinds of positions. This included pretty much the cited text, but we certainly had PhD students that were not good programmers and they still (sometimes) did ok.
Can you learn to program sufficiently, either before starting or at least within acceptable time frame after starting? This largely depends on how good a programmer they really need, how much you currently suck at programming, and whether you learn to program quickly or not (programming, specifically, seems to be one of those skills that comes much more easily to some than to others).

To figure both things out, you should get in touch with the professor or one of his students to get a feel for what their stance on these issues is. For some position, you really need to be an excellent programmer, and for those, there is indeed no point in applying. For others, being able to hack together a workable prototype in reasonable time is sufficient, and most people should be able to learn that. When contacting them, be diplomatic and don't tell them outright that you are bad at programming. Get a feel for what you are really supposed to do, and decide for yourself whether you will be able to do it or learn to do it quickly. Then decide whether to apply.

I would highly disagree with this answer. I'm currently an undergraduate at a top tier research lab that consists of mostly graduate students. Unless there is something spectacular about a candidate in our field (hardware, FPGAs, etc.), if they can't program, we don't want them. If the requirement is to be able to program, then there is probably some computational aspect and therefore you must be able to program.

@SnakesandCoffee: sure, it sounds like your group is a place where strong programming is a non-negotiable requirement, and maybe that’s what OP will be told if they get in touch with the place.  But as this answer says, it could also turn out that the programming was desired but not absolutely required — an applicant’s strengths in other areas could make up for their programming weakness.  So it is certainly worth asking.

@SnakesandCoffee I am sure there are positions where they really need a good programmer (my lab would be one of those), but that does not mean that a student should give up just because of a line in the job posting.

@SnakesandCoffee There are tons of websites like Code Academy that dole out basic programming skills to complete newbies, free of charge, in a manner that is designed for people with no programming knowledge. I firmly believe that if my English major roommate was able to write a GPA calculator in Ruby in a day to win a $20 bet, that someone with a master's degree can do it too. High-performance computing, distributing computing, stuff like that sure, you need the skills. But if OP were doing anything like that, he would likely already have programming knowledge.

@ChrisCirefice there is a big difference between monkey programming, where all you need is to add few numbers or iterate the list and a good programmer. The sites you provided are targeting people who want to impress their grandmother with "look grandma, I can add 3 numbers". To be a good programmer and you need way more than that and this transition does not happen over night (in fact a lot of people who are doing programming for a living for the last 5 years are not able to make a switch)

@SalvadorDali Not all areas of research need anything more than 'monkey programming'. Sure, if you're trying to build a software suite to model performance of the calculation of pi to 1 trillion digits over a distributed system, you might need some more programming experience. From what I've seen of graduate research at my own university, a lot of research involves number crunching ("adding 3 numbers"), statistical calculations or some implementation of Algorithm X on a particular data set. Since OP was very ambiguous about the desired program, we can only speculate...

@ChrisCirefice agree that not all areas need more than monkey programming, but based on my experience for such positions they do not write: very good programming skills and experience. Why would you need very good programming skills to calculate the average and what experience would you need to write a while loop?

@xLeitix Judging by OP's prior post (http://academia.stackexchange.com/questions/29434/how-to-make-a-papers-author-willing-to-help-me-with-his-source-code-like-a-semi), He's working on wireless sensor networks. Unless he's amazing at algorithms with little to no programming experience, I don't know what he'd be looking at in terms of work.

You should definitely apply. Because it doesn't hurt to try.

If you are accepted, it's fantastic.
If you are rejected, the biggest lost is a possible application fee of less than $100 (in EU, the application is often free).

If you do not try, since you like this position that much, you may regret forever.
Note that the level of programming skills to be considered "good" in academia is very different, i.e. much lower, from that in industry. Any CS graduate student should be able to learn a new programming language and do some basic programming with it within 1 week. That may already be "good" enough.

"should be able to learn a new programming language and do some basic programming with it within 1 week." Not if you are not a decent programmer (in some language) to begin with. The OP's post sounds like he is not.

I wouldn't call being accepted into such a program "fantastic". You relocate to a new city only to be stuck in a position you're not qualified for, where you waste everyone's time and likely won't be able to successfully finish your PhD.

I'm assuming from the OP's question that he/she is not a CS grad student. I do agree that a CS grad student should be able to do at least basic programming in a week in any language, but that's precisely because they do (or at least should) have strong programming skills.

And then professors are surprised when they see hundreds of unqualified candidates. Surely it does not hurt to try. But it does not hurt him to try, because it definitely hurts professor and hiring committee. The reasons of spammers is similar: it does not hurt them to send a few thousand viagra emails and you know what, that test@gmail.com has never told that he does not want to get such email (if he told, may be he was not sure).

Do not worry that much about the exact requirements. The process of creating a job/position offer is the following:

the job: screwing screws with a screwdriver
the actual requirements: ability to twist your wrist

This does not sound cool/expanded enough so we add some more requirements:

experience with a screwdriver
business acumen to understand the implications of the strategy of the company
fluent English, German and Swahili - in case the purchase order for the screwdriver was from there
ability to convey an idea, in case one would need to do a PowerPoint on the usage of screwdrivers

Then come the candidates, usually interested in Liberal Arts or Musicology. None has seen a screw.
Then come you, and say that you are very good in production lines and have seen videos on how to use a screwdriver, and that it honestly does not look hard and you are willing to work hard to understand the subtleties of the job. Heck, you have even purchased a screwdriver to get some experience ahead of time.
The jury has not even seen the job offer, they know what they need and except if the experience with a screwdriver is an absolute must -- you look like a reasonable candidate.
There is of course the chance of the screwdriver maniac who has been doing this for the last 10 years, enthusiastic about the business consequences and having published a paper on that in Swahili (and then presented in with PowerPoint on a conference). Bad luck, he is a better fit but at least you tried.

+1 In my limited experience with (academic and industry) hiring, this is exactly what happens most of the time.

Apply! That's how I got my first TA position (in another field though). I didn't have the required level of knowledge of certain areas but still applied. They trusted my abilities to read up on such stuff on my own (I had proven to be able at other occasions during my studies), so they gave me the chance. I caught up what I was still lacking and they were very happy with the result.
You seem to have a lot of potential since you graduated with honours. Mention this as well in your application. Show them that you are willing and able to catch up anything you still lack of.
They do not need you to fit perfectly but to be willing and able to work hard for the good of the institution and scientific progress.

I see two issues:

You are concerned about not being perfect for the position. Nobody is perfect for any position. Put your name out there and let the lab manager or PI weigh your strengths and weaknesses against other candidates. A PhD program is for training scientists. If you already had the skills, you'd be applying for faculty positions. This is perfectly fine.
You mention this is nearly identical to your masters work. This is probably OK for a PhD position, but you would typically be applying for PhD and post-doc positions based on seeking training in a new skill rather than just using what you already know. This, I think, strengthens my first point, but I hope changes the way you perceive a "perfect" position.

Best of luck.

Personally I would apply for both and be completely drop dead honest with your experience (how much time, what languages, etc.).  That's the best policy.  If they want a really experienced developer, honestly, a PhD or candidate is probably not the best place to find that.  If they need someone that can code to some degree to implement some particular structures that you have a good understanding of based on your experience, then it may be a good fit.
My expectation is that something like this would be proto-typed by people with specialized knowledge, but refactored by developers specifically before any actual production release/use.  Again, I would clarify exactly what you know and don't, the interviewer will know that you can learn based on your education, and as long as you're honest about what you've done should not have any unrealistic expectations on how quickly you can come up to speed on things you don't know.
You can learn the basics of a language in a few weeks or months generally, and the real question is what level of complexity does the actual code rise to?
I would expect that you would be writing either sample code for a new architecture/design or a library to be used by others.  Both are much simpler than production code so you don't need the entire skill set that an experienced (5-10 years experience) developer brings to the job. Not that either is without its pitfalls, especially the latter!  But generally you will not be using as much of the language's API for these as a developer at that level of experience would have direct experience with.

The originally selected answer simply says not to apply. The fact that you chose this as the answer is sad, since it looks like you're giving up. Few people exactly match a CV's prerequisites (or if they do they are probably overqualified). Skill are not inate but are acquired.
If the only deficiency is that you do not think your programming is as good as the professor expects, then spend some time coding and convince yourself otherwise. I'd bet there are probably other candidates who think they are good programmers and are actually worse than you.
T'is better to have tried and failed than never to have tried at all.

This does not provide an answer to the question. To critique or request clarification from an author, leave a comment below their post.

@jakebeal It is an answer, actually. It says he should apply, and justifies this on the basis that programming experience is subjective, and that people are accepted for positions despite not meeting ask the criteria. The critique of the other answer was just a bonus.

@beldaz Then perhaps you would care to remove the first paragraph, which would have been better as a comment?

One of the requirements is strong programming ability which I do not
  have that. I am not too good programmer.

Simply do not apply for the programme.

but I do not like miss the opportunity of working with him . Do you have any suggestion. Can I say him I want to work with you with out applying? I want to make connection with him. I want he know me. any suggestion please?

How do I make connection with him for any thing even not applying for phd?

@alex Here there are two different stories. Whether you are eligible for the programme or not and whether that professor wants to work with such unskilled applicant or not. At your current state, you say that you do not have required programming skills, so why should you put yourself and that research project in trouble and accept programming duties as part of your PhD programme when you do not have required skills? Of course you can send email to the professor and clearly state that you are not a good programmer but have strong CV. He then can decide whether he wants such student or not.

@alex Also, I have the feeling that if in the requirements it is clearly stated that they need a student with good programming knowledge and experience, you need very good programming knowledge and need to be so skilled to accept their research project.

I disagree. People state all kinds of things that they often don't really need in job listings. No reason to get immediately discouraged.

All job postings should describe the perfect candidate. There is no such thing as the perfect candidate. It's the person doing the hiring who must weigh the strengths and weaknesses of each candidate against each other, along with personality issues and things that come up in interviews.

@alex It is your question and you may change its accepted answer at any time you like.

+1 for being one of the few realistic answers. Sure, job descriptions often contain unnecessary noise but those generally aren't prefixed with the qualifier "very good". To me that doesn't seem like a minor or flexible requirement but indicates a core job requirement.

If they want PhD level for a programming related job, this could be development in a physics level? I would speak with a recruiter about this opportunity to gauge where you stand, what your comfortable with and if you think your current major isn't sufficient, it would not take very long to fill the gaps in learning how to code. The problem is for that type of role they may also be seeking senior level developer skills and methodologies. They could be looking for CMMI, Scrum, Agile, or other frameworks that you may or may not have studied.
Are you qualified to answer programming related questions when it comes to the interview..... maybe... how good are you with formulas? Programming isn't difficult, programming to make intelligent decisions is the tricky part. If you are GREAT with psychology and physics, you could be a great developer. If you can prove that you are qualified to systematically respond to an intelligent user response with a an action based on pivotal logic statements, for loops, and combine this with several datasets... you might be qualified.

What the title of the position is, can usually give some relativity to the role you might be considering applying for...
All things considered, try to dig up more info about the company, the role, and it never hurts to reach out and inquire. :)

I would also go with the "apply" people
Be honest about your lack of programming skills and whether or not you are willing and able to upgrade them (may ask for tips from them).
Then let them decide how hard the requirements are.

If you really want to do something, then apply for it. This is my advice for jobs, scholarships, PhD positions, community service programs--whatever. You might not be accepted, but applying is the only way you stand a chance. Also, you probably stand a better chance than you think. Lots of positions have stringent requirements in theory, but that doesn't mean candidates meeting those requirements are easy to find. Not everyone has "very good programming skills" (or a fluent second language, or 5 years of experience, or whatever the "requirements" are). They will take the best candidate, even if the best candidate isn't perfect.
In your case, you seem to be highly qualified overall. Let them know about your master's thesis. Let them know about other experiences that seem relevant. Make sure they see you as a unique opportunity. Don't lie about your skills, though--if you say you're a great programmer, you'll be screwed when they find out you aren't. Maybe you can turn a negative into a positive. (E.g., "I don't have a lot of programming experience yet, but I have other computer skills, and I'd be willing to learn whatever you need me to do.")
The fact is, if you think you have what it takes, and you can explain why you think that, other people will tend to agree.

What do you mean when you say that you are 'not so good in programming'? Does this mean you have no experience with programming or that you have experience but simply aren't very good? I will assume the former, as it is a bit worrying if you have programming experience and still feel it will take 6 months to become proficient.
I would apply and be very honest about your programming skills or lack thereof in this case. Then it's a case of convincing them that you have the ability, and are motivated, to pick up those programming skills. Do you have any examples where you quickly picked up something technical in your previous degrees?
Ultimately, if they want a hot-shot programmer then you have no chance. In this case, they won't take your word that you are a good programmer; rather, they will expect to see evidence of programs, etc. you have built. Given how generally they have written the programming requirement, however, it wouldn't surprise me if they are just looking for somebody who will have no problem with the programming requirement of the project. It sounds like you are a good candidate in other respects so they might be willing to take you on if you can convince them you can develop the programming skills in due course.
It might not take long to pick up programming expertise once you start your PhD. I (a PhD student in mathematical biology) had never coded a line before I started my PhD and am now proficient in several languages - it only took me about a month of coding before I started building a numerical simulation that I used in the first publication from my PhD. So it definitely can be done but it is dependent on 1. how quickly you pick it up, and 2. (possibly more importantly) your motivation to learn/enjoyment of programming, as the only way to get good at programming is to spend a lot of time programming.

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What is the difference between a teaching assistant and an instructor?
It seems to me that the terms "Teaching Assistant" and "Instructor" refer to a variety of positions. At some places, a teaching assistant is responsible for things like helping the actual lecturer by handing out papers, grading homework, etc., and instructors hold recitation sessions.
At other places, I saw the term "instructor" referring to the lecturer giving the course, while a teaching assistant is the person doing anything else (recitations, grading etc.).
Is there some widely accepted definition of the two positions?
For context: The question arose because I wasn't sure whether I'm using the correct terms in my CV -- I am a math graduate student, and I would like to make a distinction between jobs in which I only graded course assignments/final exams, and courses in which I held recitation classes* (and also participated in grading the final exams). Is it OK to use "Instructor" for the latter? What should the former be referred to as?
*In the course I'm currently teaching, the recitations are planned and written by the ones giving them (without the professors' supervision). Also, the people giving the recitations are not necessarily grad students (some already hold a PhD). I'm elaborating on that because from what I've seen, some of it could be relevant for the definition of the job.

Most of what you said is sad but true, @BenCrowe.  Except that "gets no benefits" is fortunately not always true -- some universities' TAs have unionized!

No, there really is no universal definition of the terms; I have been a "teaching assistant" and an "instructor" at the same school for basically the same position.
The only thing that I would say is that the term "teaching assistant" tends to imply a position that does not have significant lecturing responsibilities, although she may be responsible for nearly everything else in the course (creating and grading homework and exam problems, interacting with students, conducting recitations sections, and so on). Note that this does not mean that the TA might not carry out a "spot lecture" or two; but this is not an expectation of the position overall.
In general, I would avoid this problem by doing two things:

Listing on my CV the "job title" that the school assigns to the role you carried out.
Provide a short list of the duties your position entailed.

In this way, there is no ambiguity or misconception that can result, since you're providing all the information needed to understand the breadth of your teaching experience.

Yes, avoid problems by using the school's language (for example, some schools use GSI - graduate student instructors) and giving a textual explanation.

To me, "teaching assistant" strongly suggests working under some other specific person who has more primary teaching duties and/or more control of the course content, procedures and grading, while "instructor" suggests (though less strongly) the person who does have those primary responsibilities.  When my colleagues and I want to hit that last point more strongly, we often say "instructor of record".  This means that when you look up the course in various academic records, someone is listed as "the instructor", and that person [or persons, sometimes] is the one who has the power to admit, forbid or withdraw students from the course, assign grades and so forth.
But in truth the terms are not used so unambiguously, even within one university.  In my department (mathematics, UGA) we have an "outstanding TA award".  This award is given for students for teaching responsibilities which are identical to my own as a tenure-track faculty member -- i.e., they write a syllabus, give all the lectures, choose all the homework, write and grade all the exams and assign the grades.  (The only difference between what happens when I teach these courses and when a graduate student does it is that the graduate student gets more oversight than I do, in various ways: e.g. they should in principle be showing all of their exams to a faculty mentor beforehand.)  I would be happier if this were called an "outstanding instructor award".  In fact the issue of how much power and autonomy graduate student instructors should have is an active one in my department, and a minority of faculty members call graduate students "TAs" rather than instructors and use this as an argument for less autonomy in their teaching.  So it's complicated!
Let me end by saying that many universities feel pressured to call graduate students "TAs": the extent to which graduate students serve as "instructors of record" varies a lot from one department to another.  Moreover, in some cases it seems like it would be inappropriate to have all but the most senior grad students as instructors of record whereas in other cases it could even improve the teaching experience.  (I regularly teach the same second semester calculus class that I taught as a graduate student.  My understanding of freshman calculus is deeper now than it was as a PhD student.  This is accompanied by less empathy for the students than I had when I was only a few years away from having learned this material myself, with the effect that I think it is likely that a majority of students would have been happier to have the graduate-student-me as an instructor than the present-day-me.)
I fear that at least in some cases universities call their graduate student instructors "TAs" so as to be able to report a larger percentage of courses taught by tenure-track faculty.  Of course this is pure skullduggery, of which the graduate students are not the intended victims but rather collateral damage.

Having read a lot of CV's this year, I can say that there's huge variation in what teaching assistants in mathematics do.  I saw everything from TA's who just graded papers and held office hours all the way through a PhD program to students who had sole responsibility for teaching sophomore/junior level classes while they were in the PhD program.
You should definitely use your official title ("Teaching Assistant", "Graduate Teaching Assistant", "Graduate Teaching Fellow", etc.)  You should also explain exactly what you did for each course that you were involved in (grading, office hours, led recitation sections, lectured when the prof was out of town, ..., all the way up to "sole responsibility for the course.")

In my experience a teaching assistant is a student who is paid for services that may include teaching, grading, one-to-one tutoring, proctoring tests, and perhaps other things.  "Instructor" can mean anyone who has the primary responsibility for teaching a course, and in some cases such an instructor is a teaching assistant.  Teaching by teaching assistants is often done in a role subordinate to that of the "instructor", who may be a professor.  Sometimes the "instructor" lectures before a classroom in which 100 or more students sit, and the students in the course also meet in smaller groups with teaching assistants.
However, at many institutions the word "instructor" also denotes an academic rank, lower than "assistant professor", sometimes only given to persons who have completed a Ph.D., and may be given in disregard of whether actual teaching is required of the person bearing the title.

In the departments that I'm familiar with, "teaching assistant" has always meant a student, usually a graduate student. The meaning of "instructor", however, varies a lot. At one time it was a job title for what would nowadays be a postdoctoral position. My first job at Michigan, as a new Ph.D., was "T.H. Hildebrandt Instructor"; other math departments had similar "named" instructorships, like the Gibbs Instructorship at Yale and the Peirce Instructorships at Harvard.  Not long afterward, though, many universities tried to make the meanings of titles uniform across departments. The new, centrally mandated definitions of titles didn't always match what actually happened in the departments; I believe Harvard used (and perhaps still uses?) the title "Benjamin Peirce assistant professor of and lecturer in mathematics" to indicate that the job is something like an assistant professorship and something like a lecturership.  Michigan has "T.H. Hildebrandt assistant professor of mathematics" as the official title for certain postdoc positions (with less teaching duties than some other postdoc positions).
Having been removed from its previous faculty meaning, "instructor" became available for graduate students. Shortly after Michigan's teaching assistants unionized, their official title became "graduate student instructor". Apparently the union thought this title was more respectful, and the university administration was presumably happy to accept at least one union demand without any new costs. (Well, there was a small cost in the time of admissions officers like me having to explain to prospective graduate students that the graduate student instructorship we were offering them was essentially the same as what others called a teaching assistantship.)
All of the preceding refers to "instructor" as part of someone's job title.  The word is also used in the context of "instructor of record" for a class, which Pete Clark explained, so I won't write more about that.
Another use of the word "instructor" is just as a general term for anyone teaching in the university, regardless of rank. For example, our end-of-semester teaching evaluation questionnaires ask students about their agreement or disagreement with statements like "the instructor is an excellent teacher." This terminology is the same whether the instructor in question is a graduate student or the provost.

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text:
How to prove that a student is plagiarizing with paraphrasing software like Spinbot?
Plagiarism software will not detect assignments that use Spinbot or other paraphrasing software. How do you prove a student is doing so?

I know the word "spinbot" only in the sense that a character in a game keeps executing a spinning movement. Is the word used in a wider sense now, as well?

@O.R.Mapper there are sites (for example spinbot.com) provide this "service" as a way to find different word choices for your text. They spin it many different ways such as useful for brainstorming or for "revitalizing" old articles/blog posts for reposting. It's a smarttext application that can generate human readable content.

Short of actually catching the student on the site during class, depending on how "smart" the generator is, you probably can't prove it.

As long as the spinbot isn't very good, it doesn't seem like it should be terribly difficult to spot. Of course, plagiarism is notoriously difficult to prove, but I would imagine the people using a spinbot aren't pulling from terribly obscure sources, so its not all that different than a student lazily paraphrasing.

So the spin bot only acts as a thesaurus and you still have to choose the actual wording yourself? In that case, I don't see why you would even want or need to prove that the student used a spinbot, since the plagiarism is in taking the idea without credit, not the wording. (Unless it's too similar still, but even then it's not the spinbot that's the problem.)

@sgr You can it yourself at https://spinbot.com/ . I don't see any thesaurus functionality, or any possibility of manual choice: there's one box to type in your source text, and another box where it spits out a paraphrase of whatever you gave it. For instance, it turned my previous sentence into: "I don't perceive any thesaurus usefulness, or any probability of manual decision: there's one box to sort in your source content, and another case where it releases a summary of whatever you gave it."

@Tyberius: It might be easy to spot manually in a singular case, if you're looking at one paper and the original source side-by-side. But the whole point of the question is that it successfully defeats automated software that does a literal text-search of hundreds of student papers to direct the instructor's attention in the first place.

@Pont: I wouldn't worry about that one. "In likelihood hypothesis, the typical (or Gaussian) conveyance is an extremely normal nonstop likelihood circulation. Ordinary appropriations are critical in insights and are regularly utilized as a part of the normal and sociologies to speak to genuine esteemed arbitrary factors whose dispersions are not known." Pfft.  (Original text: first paragraph of the wikipedia article on normal distribution.)

@InquisitiveLurker One more nice criterion to distinguish real science from blah-blah-blah... :-)

Looks like Spinbot's an API that's being used not just on its own website, but also through others and in software that licenses it.

+1, because even if this isn't a huge problem yet, it'll likely become one in the near-future as this sort of software rapidly becomes more effective.  Seems like there'll probably be a near-term arms race between plagiarism obfuscation and plagiarism detection, though long-term I'd imagine that plagiarism obfuscation'll tend to win out since it's a much easier problem.  Sorta like how encryption tends to win out against encryption-cracking; there's just a basic computational asymmetry to the situation.

Are you trying to automatically detect papers that are likely to have been plagiarized, or are you trying to prove that a specific paper was plagiarized once you already have the (candidate source, paper) pair?  Because those are really two separate problems.

I think you would need to know the particular source text that you believe it was modified from. In that case, demonstrating identical structure ought to be sufficient: a sentence-by-sentence comparison ought to show convincingly that the exact same ideas have been used in the same order. This absolutely falls under the definition of plagiarism (whether or not it was done in an automated way by a spinbot), and provided the text is of a decent length, it would be unreasonable for the student to claim that they happened upon the same structure by coincidence.
If you don't have the original text, I'm not aware of any tools you could use to search for it - that would seem to be a very complex (though maybe not insurmountable) AI problem. But if you don't know the source text, how would you suspect it in the first place (unless you'd caught the student in the act)?

This answer seems to boil down to "The given website does successfully and completely defeat existing tools to search for plagiarism".

You don't need to prove it.  A mechanical paraphrase is no different from a paraphrase written by the student.  What makes plagiarism is the absence of a citation.  I've found that it is generally luminously clear when (undergraduate) students have copied without citation, whether paraphrased or not.
If you can recognize the original source, then paraphrase without citation is clear.  If not, asking the student for more detail about the idea that the student claims as his own will generally demonstrate the misconduct.  Whether you can take formal action in the latter case depends on the rules and culture of your institution.

In many universities, a coursework assessment does not allow for a viva, so there is no option of "asking" a student unless a misconduct case is filed.

@DmitrySavostyanov  I can only comment on U.S. universities, and then only on a subset, but my experience is that an allegation of academic misconduct starts with a meeting between student and professor in which the professor questions the student about the suspect material.

Rules are more strict in the UK regarding the number of assessments, so if the module descriptor says it is a coursework, a professor is not supposed to make it "a coursework and a viva", particularly for only a subset of students.

@DmitrySavostyanov There is a difference between it being "coursework and a viva" and an interview as the first step in an academic misconduct investigation.

Well, a good clue would be sentences that don't actually make sense, like the classic:
“I could hear the charlatan of the ducks in the distance,” and other examples stolen from:
http://www.slate.com/articles/life/education/2014/08/writing_clearly_in_student_papers_the_right_click_thesaurus_and_rogeting.html
Unfortunately, the only way I can think of to identify this automatically would require custom-written software, and a decent amount of work. Essentially, you could take chunks of text, throw it into a spinbot repeatedly, and then see if you turn up matches. This seems like a computationally difficult problem, since you have to test (number of synonyms)^(sentence length) options - you could only do this for short sentences. Maybe it's possible to cut that down by going to more-common synonyms first. Sounds a little like a problem where testing a proposed match is a lot faster than actually finding the match. Maybe you could get some interest from folks on https://cs.stackexchange.com/ to see if defeating spinbot plagiarism is NP-Complete!

Nope, build a syntax tree of each sentence and do a look-up based on that tree. Requires that your corpus also be similarly processed but it's possible (and to horribly hard)

Ah, not bad, wasn't thinking too hard in my original answer. (But it requires you to have the corpus to match, which you generally don't for turnitin, etc.)

A method that might be useful is contextual analysis. A statement that used jargon that seems out of place, or whose meaning doesn’t tie into the larger narrative lends weight to the possibility that the words were not the authors own.
If you ever do in person reviews of papers, you can cross examine the author on his or her knowledge and intent of including the statements.
If they are able to defend themselves, then the possibility shifts from suspected plagiarism to authentic knowledge.
If not, then you’ll know.
Nevertheless, it will be up to you to determine how much time resources you want to devote to authenticating the work of your students.

Could you tell us more about your assignments, your suspicions, your students, and your grading scheme?  For my answer, I'll make a simple assumption but please straighten me out if this is wrong.
I'll assume that the plagiarism problem comes up primarily because you are assigning some standard homework problems for which other students have posted solutions online.  Example: http://www.amandalscott.com/wp-content/uploads/2016/02/Amanda-Scott-PRL-102-Final-Fall-2015.pdf.  This is a homework assignment that a student submitted for a class two years ago and then uploaded to the web.  Who knows why!
The assignment comes from a standard textbook.  This very same assignment is given to large numbers of students across the country every semester.
If this is the type of situation you're facing, as an instructor... I think the solution lies in modifying the assignment.  Then if the work submitted doesn't hang together, you grade it accordingly.  Let's suppose your student tried to cobble something together based on a homework submission someone else turned in and posted on the web, for the homework problem as it appears in the textbook, which is a slightly different assignment than the one you gave.  If your student learned something from the submission s/he found on the web, and then did a good job of cobbling; OR if your student did not do a very good job of cobbling -- in both cases, just grade the work the way you would normally do.  Does the prose have good structure and readability?  Do the ideas flow with good logic?  Does the document hit the important points?  Not too short, not too wordy?  Etc.

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text:
How to write a good PhD literature review?
I am in the early stages of my PhD and I am trying to put together a literature review of my topic. My intention is that this review will eventually be included in my thesis, something like "the chapter that describes the state of the art in the domain."
My subject is soft matter physics and a large number of theses have already been written this topic. When looking at the literature reviews included in these other works I've noticed that:

The sequence of ideas is often the same (this makes sense, so why not?)
Cited papers are always the same, even though 20 years elapsed between the first and last thesis. Moreover, papers from the 30's are cited but no one in my lab seems to have a copy available?

My hypothesis is that these theses are derived from some sort of a Mother of All Thesis, and that paraphrasing the work of the previous student is OK.
So, what makes a good literature review?
How do you notice that a literature review is sloppy?
PS: I posted this question because I assume many of you have experience with this process either in your own PhD work, or as a supervisor where you have had to deal with paraphrasing of your students.
PS2: I am not asking about making proper citations, LaTeX+BibTeX handles that like a charm.

The purpose and expectations of a PhD literature review is likely to vary from field to field. My PhD was in Physics, but my views might be taken to apply generally.
There is likely to be some repetition or paraphrasing between students in the same research group, when it comes to the literature review. However, perhaps the comments below might help.
A literature review should be an enjoyable to read (!) introduction, survey and guide to the state of the art. You want to introduce your reader to the field (assuming a clever, but non-expert reader), setting out what has gone before, and perhaps to some extent showing where the gaps are in the research - raising the opportunity for you to present your research as that which fills a gap (Next chapter: "Aims and Objectives", or similar).
My primary hallmarks of a poor, or sloppy literature review is that papers are listed without any helpful context.  A dreary literature review, to me, is a listing of papers that we all already know about, without any guide to the reader why the trail leads me to hold the present thesis. No-one much likes reading a dry chronology of papers. I personally, want to be told the story of the research and the literature review plays an important part of that story.
The opportunity exists here to review the field - what are the general trends in the literature? For example,  Paper A was the first to introduce the theory that drove the authors of Paper B to perform experiment Z which is now the standard technique. However, Paper C suggests that an alternative method may be more effective, etc.
Note that your review shouldn't attempt to be a complete review of the field - whole standalone papers are written on this, usually by invitation. Your PhD literature review should be more focused, but still a recounting of the Story So Far.
Since your literature review is to be a nice, focused review of the path to your contribution, it is likely that you will read far more papers than you will need to cite in your literature review. Those papers that do not contribute to the Story So Far can be excluded from your literature review. Going off on a tangent, like in any story, can lose and confuse your readers. If you feel a need to refer to these papers, perhaps you can refer to a decent review article which discusses them in detail, for the interested reader.

I think Nikolas' answer is already pretty great. I'm not doing physics, but I'll try and stay as general as I can. Here's some specific advice I got from my supervisor and things I realized while doing my own lit review:

It is normal for a big section of referenced papers to be the same across a lot of survey / literature review papers. Those would be the papers that first introduced a problem, a concept, an approach.
In addition to the seminal papers from your (sub)field, you usually want to describe the current state-of-the art. This would be based on current papers based on the original problem, concept or approach that adopt the problem for a different environment, apply a concept for a different purpose or represent an improvement to the approach.
For example, in Computer Science, it would be okay to talk about a structure or a problem (seminal paper) and then talk about the current best algorithm(s) to solving the problem (state-of-the-art) without mentioning every single "evolution step" of the algorithm.
 Basically, to sum up and dump up these two points: you cite the "first" and the "last" paper dealing with the same thing.
Of course, there's exceptions to this: if there's any groundbreaking papers between the "first" and the "last" paper, sometimes intermediate papers can also be viewed as "seminal papers" for the subject/field.
This might depend slightly on the type of document you want to produce, but usually it is okay for you to explain the technique / method in detail, while for practical uses of the technique, you just mention (and cite) several successful applications of the technique without going in to detail about how exactly the method was adopted.
Finally, if  your goal is to publish your literature review as a survey paper (which is usually worth a shot), you should think about how to "get a new spin on things".
Every paper, including survey papers, is supposed to be a scientific contribution. That means that you have to find something that makes your survey useful, or in some context better, then all the existing surveys. This might be a change of context in which the methods are examined, it might cover more material, offer new classifications of the methods or new links between them.
I would say you have to think of at least one type of reader (a reader with one type of goal) who will take your review and say: "That's it!", while he can not say that any of the current surveys out there are exactly "it" for him.

There are couple of points i like to make from my perspective.

Bibliography is something which evolves during your PhD. I would recommend not to write it at the first place. As you read more and more, relevant to your area in Soft matter, you can keep adding it to your bibliography
Soft matter is a really huge area. One who works on Molecular dynamics may not even touch crystal defects while writing his bibliography. In that way it is really topic specific and not the entire area.
You said, you saw some say 30 papers in every thesis. This is not because of magic, this is only because they are path breaking. If you are in MD area (which is mine), and you are using a thermostat, it is 99.9999 % sure that you cite Nose-Hoover paper. It is no magic.
There is no point in saying none from my lab is cited. It depends on how many groups are working in that "specific" area and what impact had the papers published from your lab made in their research.

This all points out to the fact that one does not simply write a bibliography of an entire area :)

I'm sorry for the downvote but I do not feel like this answers the right question at all. It is all useful advice, just not the answer to "How do I write a lit review?" but rather "How do I organize/keep my bibliography collection?".

References and bibliography are to be read and digested in a progressive manner. References that might have been not so intuitive become useful over time as we gain more experience.
One needs to document them in any suitable way and:

Add new references and connections with current work.
Track these references and revisit them when and where you touch base again with them.
Revise the entry with new information or clearer understanding of the subject.
Remove any parasite or related paper that you think is no more directly related to your work - clear clutter up - this is important to stop accumulating lots of bibliography which can become non specific!
All of the references you might accumulate may not be useful for the final bibiliography. There is need to sort or classify these references as biblio, self learning references, state of art, related (first order, second order) and so on and so forth.

Doing this using a wiki would be advisable - and if there is a team involved group updates would be preferable! Basically one needs a good sense of organization while writing the thesis.

Sorting the refs into specific usage is a great help !

While it is all great advice, somewhat similarly to Vaidyanathan's answer, I feel like it's more focused on how to organize the bibliography during one's PhD and not how to do a lit review. It does mention using this for the final bibliography, but I would say putting this in the more specific context of the question would make for a much better answer.


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What is the meaning of signs and numbers appearing in scoring system of AAAI?
I've received the reviewer reports for a paper I submitted to AAAI (the Association for the Advancement of Artificial Intelligence).
I found their scoring method a bit confusing and I would like some help understanding their review of my work.
Each aspect is followed by a number and some plus and minus signs. For instance:

8(+++)

Can any experienced reviewers/authors explain the meaning of these signs and the range of scores?

Clarified slightly, including focus on AAAI (EasyChair allows many ranking systems)

So each reviewer gave a score and couple of signs for each aspect? I would guess 8(+++) means three reviewers evaluate this aspect to 8

I dug up my AAAI reviews from two years ago, and it looks like they've been tinkering with their scoring system, so I can't tell you a precise answer.  I can give the general principle, however:
EasyChair allows the chairs of a conference to configure a set of "attributes" for scoring.  Each attribute gets both a numerical value and a descriptor.  Some examples from AAAI two years ago:
Individual attributes:

5: (ground-breaking (top 15%), a sufficient basis for accepting the paper)
4: (positive, a factor in accepting the paper)
2: (problematic, a factor in rejecting the paper)

Overall ratings:

2: (Strong acceptance.  A 5 or 6 in some category, no 1 in any category.)
-2: (Strong rejection.  A 1 in some category, no 5 or 6 in any category.)

So as you can see, then they were using a 1-6 scale and a -2 to 2 scale.
From the sample you gave, my guess is that they're currently using a 1-10 scale, with 5 being neutral.  Thus

8 (+++)

Would translate approximately to "8 out of 10 (a very good score, three positive steps above neutral)."

This is outdated. For AAAI'24 the scores are new: https://academia.stackexchange.com/a/203574/119679

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text:
When am I supposed to get an acknowledgement for a paper submitted via e-mail (CS conference)?
I have submitted a paper to a CS conference. Am I supposed to get an acknowledgement email, so I know it hasn't ended up in the spam folder by accident, and that it will be considered for the conference? If so, how long after submission? Is it OK to contact the conference organizers and ask if my submission has been received?

Is there an online submission system? At every conference I ever submitted to, I could inspect the data of my submitted paper after submission.

@lighthousekeeper: As far as I can discern, there's only an email address.

So you submitted the paper via e-mail? That sounds really untypical for me for a CS conference. But yes, in this case, I would absolutely ask for a confirmation that your submission has been received.

@Buffy Sure, just waiting for confirmation that the paper was submitted via e-mail. In my area in computer science, that would be super unusual.

@lighthousekeeper: I submitted by email, as per the "Submission Process" instructions on the conference's website.

@lighthousekeeper, and it might be a low quality conference, or even one (in cs) that runs a bit differently from others. Patterns conferences are quite a bit different, though high quality.

Thanks EvanAad and @Buffy, I now added an answer.

In computer science, paper submission by e-mail is non-standard. Therefore, there is no default answer to your question.
However, it's in the interest of the conference organizers to show good professional communication that does not leave authors "in the dark". I would expect them to confirm your submission immediately after submission, within 24 hours. If you have not heard back from them after 24 hours, it's absolutely OK to contact them.

Actually, they should have an auto-reply in place on the submission email, but probably don't. But maybe they are just new at this.

@Buffy Alternatively, they might do a manual sanity check of some sorts. But then, they should at least announce the communication protocol (including confirmation e-mails) in the call for papers.

I browsed the website of the previous time this conference was held, and they did use an online submission system. Strange.

@EvanAad Maybe the license expired or they didn't like the system. But strange indeed.

The more I think about it, the more I get the feeling that the conference organizers simply haven't set up the online submission system yet, but that they plan on doing so in the future. I think maybe I'm being overly enthusiastic by trying to submit my paper too early, and I should wait for the right time when the paper submission system has been set up. On the other hand, the official conference website is already up, so one could expect the paper submission system to be up as well, and, if not, that there will be a clear notification on the website stating when the system will be available.

@EvanAad That would still be rather unusual on the conference organizer's side, as this would create some extra effort for adding the e-mailed papers (and meta-data) to the system. Your best bet is to just ask.

I asked, and, as I suspected, the answer was: "Thé EasyChair will be open soon."


text:
PhD supervisor is extremely "hands-off": How can I get better feedback for my research projects and cope with this situation?
I'm currently a PhD student at a US University. The relationship between my advisor and me is extremely hands off, and she only contacts me to help write grants and to review papers. While she does try her best to fund her students (including me), she doesn't respond to my emails, doesn't give me any feedback on my research updates, doesn't give any feedback on my papers, and doesn't appear to care about my career. I've had to strike it on my own on everything I do, and it's honestly getting exhausting.
I want to switch advisors but am approaching the end of my third year without any major conference papers and feel that it's too late to change my advisor. All of my paper submissions have so far gotten rejected, and getting any feedback from her is impossible. That, plus the fact that the coronavirus fried up the job market in tech just makes me feel completely powerless and desolate. What do I do?

How many years is your PhD expected to take? If you're in the third year of three, it might be tricky to switch. Third year of five or six, it's worth doing. Do you have a second supervisor you could talk to? Department head? It seems very unfair that she contacts you only when she wants something from you (grant writing and reviews). How does she act towards her other students?

Her students usually take around 6-6.5 years to graduate, but she's kept some students around for 8 years. I currently don't have a second supervisor I could talk to. A department head would be worth talking to. Her behavior with other students is the same as with me.

Does she help other students? Is she tenured?

Do you have access to other more experienced researchers, such as late stage PhD students or postdocs, that can provide you with mentorship and feedback?

@Buffy she's tenured

Are there general guidelines or something like this at your university for what level of supervision to expect? A general PhD tutor? If it's a good university, I'd expect them to have some written down standards and procedures (particularly points of contact) in case they fall short of their standards.

I'm not quite sure. I'm at a well known university and my advisor is pretty famous, and from what I've heard this is common practice across research groups with famous advisors.


text:
second on campus interview for TT faculty position (3rd interview total)
I have a question for anyone who might be a department chair or on a search committee. What does it mean if you get invited for a second on-campus interview? I have already been there once for a standard on campus interview. For context, this is for a tenure track assistant professor position in the sciences.

Was the first interview on campus?

An interview invitation doesn't have a hidden meaning.

no. it is the second on campus interview.

Oh, the edit makes sense.

I don't think anyone will be able to answer this question, so please go to the interview and tell us what the answer turns out to be.

Agree with @AnonymousPhysicist, an update to the question regarding what ended up happening might be useful to others who may experience similar things in the future.

What country is this in?

It's in the US.

I have been a department chair (math department, large US university) and nonetheless find your situation completely baffling. I have literally never heard of a TT job candidate being invited to a second on-campus interview. This is so unusual that I can’t really come up with a plausible guess for why the department that invited you thinks they need you to visit again; moreover, I think this may potentially bring the competence of the people who came up with this plan into question.
Please don’t rely on idle speculation by strangers online. My advice is to email the people who invited you and ask them to clarify what their plan is for the second visit and why they think it is needed. In my opinion, if you already had one on-campus interview, at least in a normal situation they should have all the information about you that they need in order to make a hiring decision. So I’m guessing their explanation may not be the most logical one. But at least you will have a sense of where they’re coming from.

I agree that this seems unusual.  I have heard of situations where a candidate who has been made a verbal offer is given a chance for a second visit (often with a spouse) to investigate housing, schools, etc., but these visits are after the offer, not before the offer.  If they weren't willing to make an offer after the first interview but are still interested in you then it seems likely that either some important decision maker didn't get to talk to you during the first interview or they have some reservation about hiring you that can only be addressed in interview.

An example of how this situation could arise: My college requires candidates for tenured (not tenure-track) positions to meet with an associate dean. This policy could be altered at very short notice (actually zero notice) to require the same for tenure-track candidates. In that event, we'd have to re-invite any tenure-track candidate whom we wanted to hire, and that re-visit would have to come before we could make an offer. (I don't say that this is a likely situation, just that it's not entirely absurd.)

I can imagine that the search committee forwarded two candidates, the dean rejected both (or they both declined the offer) and the search failed; the department then took the remaining candidates to build another short list and for OEO reasons, that requires inviting everyone who is now on the short list to be invited to an interview, regardless of whether they had interviewed before. Regardless, it's a rather unusual situation.

@AndreasBlass in this day and age, the scenario you are describing is completely ridiculous. Such meetings can be done over video. In any case, I don’t find this sort of speculation helpful. We don’t and can’t know what’s going on and OP should simply ask.

@DanRomik I agree with you about "this day" but not "and age". My university discovered yesterday that what used to be done face-to-face can be done by video (and starting Monday that will apply to all our classes). But until yesterday, meetings between tenure candidates and associate deans had to be in person. Video might have been allowed in extraordinary cases, but "the candidate was already here for an interview" was definitely not extraordinary enough.

@AndreasBlass I didn’t say it couldn’t happen in this day and age, only that it is ridiculous. Ridiculous things do happen unfortunately.

Thank you all. Good to hear perspectives from the other side ;).

Generally it would mean that they are very interested, but not absolutely sold. It may be that some senior professor wants to see more of you or meet you for the first time. They may want some student opinion in some places. It isn't frivolous, since they are spending some money, but you still have to close the deal.
In the long term it is probably a good sign that if you get the job they are treating you as a serious contender for eventual tenure. They are doing more than just filling a temporary slot.
But, close the deal.

Thank you. That is a very helpful answer. Kind of what I thought

Of course, there may be another candidate in the same situation.


text:
Submitting an improved/extended version of a journal article under review
Ten months ago, we submitted an article to a journal, which is still under review. In the meantime, we have made a few extensions/improvements to the submitted article.
Can we submit the extended version to another journal? How can we cite the work presented in the article under review?
Do we need to inform the editors of both journals regarding the submission of the extended version?

In my research area, journals have clearly defined rules that are relevant for this situation. For instance, one particular journal, Software and Systems Modeling (SoSyM), has the following rules:

SoSyM Policy Statement on Plagiarism: Papers submitted to SoSyM must not be simultaneously submitted as is, in an extended form, or in a shortened form to other journals or conferences. Authors can submit extended forms of papers that have previously appeared in conference proceedings. Such submissions must clearly state that the paper has been published elsewhere, must reference the paper in the submission, and must clearly state how the paper significantly extends the published version.
[...]
No Self-Plagiarism. Manuscripts in which at least 75% of the content appears in a non-journal publication or in which at least 40% appears in a journal publication will not be published.

You should check the submission policies of your target journals carefully for such rules.

One should be very careful what does it mean by 40%. Is it the outcomes of the experiments or the text?

@Coder That's indeed a bit vague in this formulation. To shed more light on the rule, one can look at its instances: in all examples of extended versions I have seen, the additional content were additional contributions, such as generalizations of the original work to a more diverse setting, rather than a more detailed presentation of the existing work.

Right. Probably the extended version of the presented conference papers (in comp. sc field).

@dan1111 Thanks, I have added relevant excerpts.


text:
Crippling anxiety when writing grant applications
I find it very difficult to make strong research proposals, where I am trying to convince the audience that my proposal is important (possibly more important than the other applicants'). I write "grant applications" in quotes, because that is the most straightforward example: In these, it is typically expected that you not only describe your idea in a way that the reviewer will easily understand and comprehend, but also convince them that the research is important and worth funding (especially with grants where the majority of applications are rejected). This feature is not limited to only grants: I think fellowship applications, PhD applications (whether they require a research proposal explicitly, or implicitly through statements of purpose with concrete research plans embedded in them being more effective), postdoc job applications and perhaps even junior faculty member applications are very similar in that one must propose a research project, and make it sound important besides merely communicating clearly.
Whenever I need to write such a proposal, I inevitably feel stuck. I immediately become anxious that my research is not all that interesting, I'm not really all that great a scientist, and feel that I must work very hard to make my proposal sound like it is more important than it is if I am to have a fighting chance. This is scary, and I end up procrastinating for many days on the writing. I tell myself that I am "waiting to be in the right sort of creative, inventive, intellectual, scientific mental state", but I secretly know this is nonsense. There are 3 very strong antitheses:

All the creative persons across the spectrum of fields (from artists to writers to inventors and engineers to mathematicians and scientists) appear in unanimous agreement that it is "1% inspiration and 99% perspiration". I have never heard anyone worth mention claim that "waiting for inspiration to come" is an effective strategy.
The inspiration that I supposedly await has an uncanny habit of materializing exactly on the night before the proposal deadline, at 3 AM in the morning, such that if it came just a little later I would not have been able to make it to the deadline.
When I do finish the proposal, I am almost universally satisfied that the result doesn't sound unimportant, and could have been brilliant if only I had started a bit earlier and made more rewrites.

I think the more realistic explanation is that at some point the fear of missing the deadline becomes so great that it overpowers my anxiety. However, I think it would be better if I could do away with the anxiety, so I could start work way before the deadline, and have time to make many revisions and avoid having to pull all-nighters.
How can I get over this anxiety? By way of showing what I have tried:

Gaming antithesis #2 above: Setting an early deadline, so that it forces me to get started, then obtaining an extension on the deadline in which time I can make revisions, now that I have gotten over the most difficult initial step. Unfortunately, the moment I obtain the extension, the anxiety comes back and saps my motivation. This happens even if the extension happens as a surprise.
"Just start by writing anything, and rewrite later" - this is very hard to force myself to do, because I feel like my ideas are hopelessly irrelevant and there's no point in even trying. Even if I do force myself to jot down a very rough outline, it is just as hard to motivate myself to keep refining it, because I feel that no matter how much I refine it, it will still be irrelevant.
Ask friends and colleagues for feedback - very effective for making a mediocre proposal good, but useless for starting out: I get even more anxious because I worry about embarrassing myself to other people.
Build up tolerance by repeated attempts - I have gone through the proposal writing process quite a few times, but the experience doesn't appear to have made it any easier. I feel like even if I had been awarded a thousand grants, I would still say to myself, "Man, you may have had a good run in your day, but this time you've lost it - this is the stupidest idea you've ever had".
How do I overcome fear of rejection when writing academic papers? - the suggestion to follow the example of good papers is hard to apply, because proposals are often confidential. The remark about "reaching a certain level of maturity" also seems to not apply, because surely a project that is only at the idea stage is anything but mature?
What is expected when "novel" and "innovative" ideas are requested as part of a research grant application? - very related, but there are many grant schemes which emphasize impact and importance (often without defining them) over innovation.

Oddly enough, I don't feel insecure about other aspects of science. I don't hesitate to do research because of self-doubt, I'm not shy about telling other people about my research (so long as the only requirement is that they understand it, and it doesn't matter if they don't think it's important), I think I do a decent job of communicating my ideas clearly and I sincerely believe that given my level of competence I have a good chance of solving the problems I am working on. Obviously, I think my research is worth doing - otherwise I wouldn't be doing it.
It is only when convincing someone else that my research is important that I stumble. I tend to imagine a grant reviewer saying to me, "Okay, this is all very nice and good, but applicant X over there wants the same grant so he can cure cancer and end world hunger. Why should we fund you and not him?" Of course, this is like saying "why should we fund NASA when we could be feeding the poor" - these aren't mutually exclusive pursuits, and just because you aim high doesn't mean you'll go high. But still, there are millions of scientists out there, and just statistically some of them are probably much smarter and more knowledgeable than me. Honestly, it seems very likely that many of them work on more important things than me. Probably some of them apply for the same grant. So how can I sit there and write a proposal, pretending that I seriously think I should be the one to get funded instead of all these other people?
Sorry if this sounds like more of a request for moral support than a question. In my defense, I think that the difficulty of "selling your ideas" is a common problem for at least a non-trivial subset of scientists (captured quite well by "impostor syndrome") and discussing strategies to overcome it would be a good addition to the site.

Unfortunately, I can't help much answering your question, but it's funny to me how we in academia exhibit anxiety similarly.  Mine just happens to be in a different area than yours.

Man, my life would be so much easier if I knew how to answer that. If it helps at all, I envy you that you only have this with grant applications. I need to re-convince myself of the significance of my work for every paper as well as for every grant and job application.

Are you me?????

@JEffE's comment is actually quite a useful one.  One thing that young people who feel real emotional (and maybe even physical) distress in writing (e.g.) grant applications should know is: most senior people do too.  I just spent the better part of two months writing an NSF grant application.  Aside from being a lot of "extra" work (if I don't get the grant the quotation marks can get removed) it is truly harrowing to have to say "my work is so great" so many times in so many different ways (or rather to show it, which is harder and just as stressful).  Hang in there: it's not just you.

My solution is to work with collaborators.
If you're writing a proposal together with others then you can workshop ideas together, pick each others' spirits up when you go down, have somebody who you "owe" progress to as an external motivator, and make writing schedules that you have to keep.  You can also aim for much more interesting and ambitious projects when you combine complementary skills and capabilities.

I suspect any answer will be highly specific to individual psychology.
There have been four things I found useful.  The first was to do a good project plan for a grant and to convince myself that everything needed to be done to a high standard.  Once I have a list of every piece of nigh-meaningless paperwork that needs doing, panic/inspiration tends to flow several months before the due date.  And, in practice, it helps cope with writers block because putting together random patient-related boilerplate and laboratory descriptions lets my mind wander while still progressing towards grant completion.  Anxiety (or even consciousness) is nigh-impossible while working on a human subjects section.
The second was to read a few granted proposals in my field.  There are an awful lot of funded studies that just don't appear at all promising.  And the feeling of 'well, I suck', but less than the people who put together grant XYZ is strangely empowering.
The third was to acquire a book describing recommended formats for grant proposals and approach grant writing in a very formulaic way.  Okay, a paragraph describing prior work....blah blah blah.  Okay, hypothesis... For me, it reduces anxiety by transforming the writing process from promoting my research to filling in the blanks on a long and frustrating form.
The last was to just kind of divorce myself from the whole project and gamify it a bit.  Think of writing the grant as preparing a presentation to convince people that something should be done without worrying about whether or not it is actually worthwhile.  And pretend you're doing it for someone else.  Things also go faster if I reward myself with bathroom breaks upon section completion.  Perhaps this is TMI, but it really works.

TLDR;
In the end, I highly recommend the book, and the following

Be kinder to yourself in your own head - if someone else said to you "they do important work and you do nothing important" you'd probably be inclined to smack them in the mouth. Yet if you say it to yourself, you probably accept it.
Accept that this is a complex and real problem, and instant success is not reasonable - so don't beat yourself up when you run into the problem again.
Try to shift your view of yourself to be based upon your resilience, creativity, and persistence - which are in your control - rather than factors like "grant approved" that are much less in your control.
Realize that you can do better in the future, but only by making adjustments that address your own personal real issue and not merely distract from it.
Your importance, intelligence, and abilities were established and verified a long time ago, and are not up for debate or re-interpretation. Problems you face now aren't because of any of these traits or behaviors.
Like any good experiment, let results dictate whether or not a method is effective for you, not preconceived notions or rapidly changing feelings.

There is no one easy trick that will solve your procrastination - but that doesn't mean it is an insolvable problem. I personally have found that thinking there is some trick actually made the problem worse, because it trivialized the problem.
"This isn't so hard, I just need to do X", I would tell myself. When actually doing X was hard, or didn't solve the problem, then I felt even worse than before - because if I can't even do X, I must an even bigger mess than I thought! This is a terribly cruel thing to do to ourselves - please try not to punish yourself in this way.
Procrastination is not a simple thing, nor is it a sign of stupidity, laziness, moral decline, unfitness, or any other such thing. If this is a problem for you, then I strongly recommend this book: Procrastination: Why You Do It, What To Do About It Now. I owe much of what I have learned to this excellent tome, and to my own struggles with the practice - it is written by two PhDs who've worked specifically in the area of academic and professional procrastination, and there's a vanishingly small amount of pop-nonsense in the book (I have very little tolerance for such things).

You have already hit upon a very important realization, which is that the core of most procrastination activity is fear - fear we aren't good enough, smart enough, worthy enough. But this isn't the only kind of fear a person can have, such as fear of success, fear of being judged, fear of competition, etc. Everyone has their own unique sets of fears.
It is important to understand that procrastination is a sometimes useful, and sometimes mal-adaptive strategy to get what we want. Sometimes we get what we want in the short-term, but not the-long term, and this sort of procrastination is a perfect example - and we need to understand both why it works and why it doesn't work.
One thing that really drew my attention is this phrase:

...could have been brilliant if only I had started a bit earlier...

This is called "self-handicapping", and ultimately it allows us to protect ourselves from fear. If we wait until the last minute and don't succeed, then we don't need to take that personally- if only we had started sooner, we'd have succeeded! It's not us, it's the delay. On the other hand if we succeed, then we are double great, because we practically phoned that one in and still won - we must really be something! Waiting until the last minute increases the perceived reward AND lowers the perceived risk - no wander it's such a compelling strategy!
But ultimately both reasonings serve to do one thing: protect ourselves from a reality that is frightening. What if we do our absolute best, and still fail?
One way of dealing with this is attacking the fear directly - what if you do your best to write a great grant app, and they still reject you? Go ahead and explain this in a way that is non-threatening - they get a lot of great grant requests, the program directors are morons, they probably just pick grants by throwing darts at a board, budget cutbacks (politicians/administrators/taxpayers are morons)...go ahead and explain the rejection now, in way you believe that doesn't include ripping yourself to shreds.
Or you can accept responsability, but do so in a fair way - you may have failed to communicate the nature of your proposed work in a way they understood, but that doesn't mean you aren't good at your job or smart - you just need to persevere at an inherently difficult task. You can also point out to yourself that you aren't just writing one single grant request (you aren't, right?), and so while the individual chance of each one succeeding might not be great you have a far higher chance of one of your many requests being approved.
In this way you can reduce the fear that this specific grant request is do or die, and so it isn't so bad because it's not scary and you do non-scary things all the time, right? For some people and in some cases, this works nicely, but it's not your only strategy.

Another mutually-helpful approach is hit on in your own realization:

I have never heard anyone worth mention claim that "waiting for
  inspiration to come" is an effective strategy

This is a great observation, and I've heard this called "the motivation fairy". The belief is that we just need to lie in wait for the motivation fairy, and it will appear and grant us the motivation we need to work!
The problem is that, as you noticed, this isn't how motivation really works. It turns out that motivation is not really something that comes before the work - motivation is produced by working! This seemed crazy to me, but the more I thought about it the more it fit my experience. I never feel the most motivated before I start something, but rather it's while I'm in the middle of doing something and making progress and feeling good about the work I'm actually doing! Motivation fundamentally is not forward-looking thing like "hope", but rather it is like the flames of a camp fire - people gather around it to warm up, but it was created initially by working hard in the cold! First comes the work, then come the flames.
The third and most useful tactic I've personally used is this: realize that how you feel about doing something does not particularly control the quality of output of your work, nor whether or not you should do it.
Much like the previous issue with motivation, I thought I should feel a certain way about my work before I started. This is a version of perfectionism - the feeling that everything should be "just so" before you do something. I mean, I've read that brilliant people eat a balanced breakfast and take an afternoon nap, and I ate beef jerky for breakfast and had to work all afternoon - so surely I should just skip this and try to have a better day tomorrow so I can do this work, right? I mean, I don't even want to do it, and surely the work will be terrible with this attitude.
The truth is that work is more like a game of American Football (or Rugby for everyone else in the world) or a broadway show - it doesn't really matter what the weather is or how you feel that day, the game/show must go on regardless.
With much effort I have begun to realize that I really suck at predicting the output of my own work based upon my feelings, desires, and emotions. Sometimes I produce an A+ paper with a fever and a stomach full of Pepto-Bismal, and sometimes everything is going my way and I churn out 10 pages that had nothing to do with what I was actually supposed to be doing. Sometimes I'm super-excited about a subject and just can't "get it", and sometimes I breeze through material I couldn't care less about.
I was amazed to find that some people hear such an explanation and think, "yeah, that's how life works - how did you think it works?" Well, I thought work was something people got all worked up and excited about, looked forward to, then jumped into and made continual progress on up until a conclusion they were terribly satisfied with.
Apparently people laugh at such a fanciful world-view, but that's how many of us still think work is supposed to go, and we get mad at ourselves and feel doomed or like failures when the reality is all messy and we feel grumpy but we are still supposed to work on something we just don't feel like doing today (or this week, month...).
Decoupling "what I feel like doing" from "what I should do" from "what I am going to do now" is really hard, but over the last decade I think I've gotten better at it. But jeeze, I put in a lot of effort and I often flounder around in my chair and say, "gahhh, I don't wannnnaaaaa!" for a while. Sometimes I get over it and get work done, and then I'm amazed at how quickly I forget about the whole episode and my work output seems to have little relation whatsoever to my feelings at the time.

Before wrapping up I want to hit on one more time-honored way we punish ourselves: false disadvantageous comparisons

"Okay, this is all very nice and good, but applicant X over there
  wants the same grant so he can cure cancer and end world hunger. Why
  should we fund you and not him?"

These sorts of comparisons are very common, and notice how incredibly unfair they are? But notice also how they are thrown out there and left unquestioned, as if they are obviously true and we should feel like failures in comparison for our puny efforts.
But that's just it - one of our greatest enemies is unquestioned assumptions, and so we should apply our argumentative skills against these things too.
First, of all, are you in fact competing directly with people who aim to cure cancer and/or end world hunger? If you aren't competing with these people, then that's silly - you're winning doesn't take money away from them, because the grant you want can't possibly take money away from them.
But let's say you are competing with them. Obviously they should win, right? But wait, if a grant request that's competing with you will win, then you have nothing to fear by writing a great request because even an idiot would know they have the better request and they'd get funded anyway. And come to think of it, haven't people been trying to cure cancer and end world hunger for a long time - so why haven't they? Is it because people like me want grants for something else?
It turns out that world hunger is a great example, because without our realizing people did already solve the problem we thought we had. We now have more food in the world than we need, but some people go without - why? Because it turns out that the world is complicated, and things like war, social justice, economic systems, and corruption mean that solving world hunger isn't so clearly solvable. It's going to take a lot of work in more fields than we ever imagined to make more progress, from psychology, sociology, economics, engineering, political science, and probably a lot of more fields than that.
Cancer, too, it turns out is complex and is caused by many things, and we can't cure it because there is a lot about the human body and chemistry we just don't understand. If it was an easy problem, we'd have solved it already. If we spent 100% of our yearly grant money only on cancer research, it's not clear that we could cure any form of it because we might not know enough about basic processes to be able to solve the problem yet.
This is also true of war, social justice, poverty, space exploration/colonization, and any other such major problem. They exist because they are hard problems, and it seems the webs of the world are very twisted indeed. And so we spread out our search for knowledge and advancement over many fields, in the hopes that one day the web will expand far enough to allow us to solve a previously insolvable problem - though we have no idea how long it might take or what field or what person will be responsible for the key insight.
So, with this said, who are you actually competing with - based on successful grant requests - and based on last years winners (when this data is available) surely some will seem amazing to you, and some will seem stupid and unimportant. Grants aren't noble prizes, and some people get money for stuff you couldn't care less about. Some are important, some will turn out to be outright failures, some good things will get funded and some bad ones will too.
And at the end of the day, this might make you feel better or not, but it might not matter because these are often just excuses we tell ourselves to rationalize our aversions to fear and our habits of waiting for the right moment.

The book mentioned previously has about 200-300 pages of very useful and helpful tips and information beyond anything I could possibly summarize here, so please consider making it a part of your daily reading routine if quick-fixes prove ineffective or short-lived (they almost always are). It's a process of developing tools, retraining yourself, and building up psyche-muscles.
Procrastination behaviors, anxiety, and fears all have their appropriate place in life, and can get out of hand and become hurtful to our well-being; they can also be put back into their rightful place, and that requires diligent effort over a significant period of time.
Good luck, and fight the good fight!

Wow, great ideas here.  Here's a small suggestion.  It is sometimes easier for me to get a project off my desk if I use it as a way to procrastinate about some other project.  Perhaps you could harness that idea and cook up some project that you really should be doing, but which does not appeal to you -- and then you might feel tempted to work on the research proposal as a way of avoiding the other thing.
My main contribution has to do with how OCD is treated.  There are two steps:

Name the fear -- preferably something that will help you laugh at it.
Talk back to it.

There is a very nice segment on a This American Life podcast that illustrates #2, done in a novel way, as a DIY project, without a therapist.  If you don't want to listen to it, you can read the transcript here: http://www.thisamericanlife.org/radio-archives/episode/545/transcript
(Scroll down to Act Four. Mailer Demon.)

Purely personal top, from someone who had to break through a near-total writing block: Write one to throw away. If you're stuck for a first paragraph,  scribble a note about what ideas belong there and move on. If you're having trouble with phrasing, just day it however it's easiest and move on. If you can't find the citation you need, leave yourself a (foot)note with a key phrase like "to be determined" or "Fixme!" and move on. Don't worry about making it elegant, just get it down on paper.
After finishing that rough draft, srt it aside for a few days if possible.
Then come back to it, read it through, and decide what needs to be improved. Remember,  the base assumption is that the first pass was just to start organizing your thoughts... bit you may find that very little polishing is needed. On the other hand, even if it's a complete train wreck,  editing it into acceptable form is often less stressful than trying to write a perfect document the first time