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Can anyone write a paper and then publish it in a journal?
I know nothing about the bureaucracy of the academic world when writing papers but I sometimes need or enjoy to read academic papers.
Usually all the papers I've read were written either by professors or by reasearchers (I'm guessing PhDs). Some papers were written by people working at Google and they were PhDs too.
My question is: can anyone write a paper or is some minimum level of education (say a PhD for instance) required? Of course I'm not asking if a persone can wake up tomorrow and write a paper on quantum physics without knowing anything at all of physics.
EDIT: when I said "write", what I meant was having the paper published. Sorry!

In principle: Yes, of course!
No journal I know has a rule that requires a minimum level of education or a specific affiliation. But in order to be accepted for a journal with reasonable reputation, there are several requirements:

Contribution: With more education (not necessarily a higher degree) it gets easier to provide a better contribution. As you said, just waking up with a great idea without even knowing the fundamentals of the field of research before is unlikely.
Novelty: For an external person it is hard to decide if he has really found something new or he was just reinventing the wheel. That is much easier if you are part of the research community. That does not necessarily require any affiliation, but for example the regular participation at conferences and workshops.
Experience: You need experience in many areas to write a good paper. A lot of (if not most) papers are rejected not because of bad ideas, but because of wrong experimental setups, wrong application of statistical methods, ugly looking plots that do not provide confidence intervals ... and most importantly because the paper was not written in a convincing way. You can not learn these things by just reading a book at home.
Time: Research requires a lot of time! If the university pays at least part of your bills you have more time to do research.
Money: Depending on the journal, publishing might be very expensive. With an affiliation at a university it is easier to find someone who pays for your publication.
Reputation: Last but not least, there are things, such as reputation of the author, that should not influence a reviewers decision, but they do at least sometimes.

Journals set their own criteria for determining which papers to publish, but anything that's original and advances the knowledge of the subject is generally publishable somewhere. The catch is that it's very difficult to do research outside the academic world. That difficulty varies with the field. As you mentioned, companies like Google and Microsoft regularly publish computer science papers; on the other hand, there really isn't alternative to academia for pure math research. Doing research at a company requires it to be willing to support your work, and very few companies are interested in supporting pure research. More applied research still requires companies to invest in their reseachers, and that generally requires a PhD, academic experimence, or some other bona fides.
If you're specifically interested in doing research yourself without a PhD, your best bet is probably to get involved with one of the few companies like Google or Microsoft that does publish large quantities of papers, put your name on its published papers even if it's just doing background or logistical work, and try to build up enough clout and experience to persuade the company to start letting you run research projects yourself. It's a hard sell, even with all the bona fides in place; companies are about making money, not doing research, and it's hard to spin publications as being profitable. You might have more luck at government labs, although their friendliness towards research and publications vary.

In theory, yes. There are no requirements that an author needs to have an academic title or education. Neither does one have to be affiliated to a university or other form or research institute.
Practically, there are a lot of things that would make it unlikely, such as a lack of support (financial - you need to have some clue of the existing literature, which is usually obtained via university subscriptions to journals) to qualification.
The person might also have to invest some of his own money, since it is unlikely to get a research grant as a privateer.


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Heard of Chamber of Chartered Java Professionals International?
I'm Java course which they said to me that they can arrange a Bachelor's degree from "The Chamber of Chartered Java Professionals International."
I did a little research my own, and from what I can see, they don't really have any verifiable information to confirm their existence.

Is there such chamber that can give people a degree?
If they can, is it a reputable degree?

My course is covers regular software engineering, including generic languages and sometimes specific languages. I also submitted a few assignments, and projects to the institute that I'm following the course with. From what I understand, they can make them equivalent to their degree requirements. However, their reputation and existence remain mysterious and I chose not to rely on what the institute says, which of course, technically, is a business.

Looks bogus to me. according to Google Maps, their "USA Coordinating Office" seems to be an apartment building.

If it sounds like bogus and looks like bogus, it is bogus. Stay clear as soon as possible to not lose any more money. The only reliable Java certifications are from Oracle and even Oracle does not claim to give BSc degrees.

Consider coding bootcamps instead if you prefer a non-conventional (non physical college) route - many are free these days; and to have to show something, coursera and such.

Any class in which the instructors/organizer offer you this must itself be considered suspect. I know, you didn't want to hear that...

In general, degrees are given by universities, technological institutes, and other similar accredited institutes of higher learning. A degree without such an accreditation in place offers extremely limited value.
While this does appear to be a "real" organization, it does not appear to have any accreditation, which would make its degrees worthless junk.

Heard of Chamber of Chartered Java Professionals International?

No.

2. If they can [offer a degree], is it a reputable degree?

No.

According to my knowledge, this chamber is owned by IJTS (a private sole owner company provides Java courses) in Sri Lanka.
Not reputed.

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Who evaluates Marie Curie Intra-European Fellowship proposals?
Who are the evaluators of the Marie Curie Intra-European Fellowship proposals? Other academics ? How are they selected ?

You will find details on the evaluation process in the Guide for Applicants. The evaluators are experts (=researchers) in the field. They will be matched to the proposal according to their profile and to the abstract and keywords. They will for sure be in the general research area, but might not be in the exact same field of the proposal. It is (at least, officially) not possible to find out who evaluated the proposal afterwards, but you can find a list of former evaluators here:
http://cordis.europa.eu/fp7/experts_en.html

Who are the evaluators...? I am. Along with a few hundred other people, of course! The evaluators ("experts" in EU jargon) are mostly academics from across Europe, with a decent number of scientists from industry, government, etc.
How are they selected? There is an open application process to become an EU H2020 expert. You fill out a form on the H2020 website, where you detail your scientific expertise, list your publications, grants etc. Then there is some selection process where, if your profile matches a vacancy on one of the evaluation panels, you get invited to be a panel member.

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Should a journal ever reveal the name of an anonymous reviewer?
Recently, the single-blind peer-review process failed to appropriately deal with highly sexist comments. An anonymous reviewer provided a sexist review and the Academic Editor forwarded it on. They have since blacklisted the reviewer and asked the Academic Editor to step down. While I think that blind peer review provides useful protection for reviewers, are Academic Editors generally provided anonymity? Further, is there any precedence for when a journal should reveal the name of a reviewer?

Do you really want to ask about the academic editor in the penultimate sentence? This makes the question somewhat overly broad.

Well, for instance if it was found that the reviewer plagiarized and/or stole from the work he reviewed, I think protecting his anonymity would be entirely inappropriate.

The review process of PLOS One did not fail. One reviewer made sexist comments, and the editor failed to take appropriate action. How can you blame that on PLOS One's process?

FWIW I'd lay some of the 'blame' here on the widely-used process of anonymous peer-review. Would the reviewer dare write what s/he did if s/he knew their comments were definitely going to be published for all the world to see?

@rmounce: At the end of the day, it all comes down to definitions, but for some interpretation of these words, the review process did indeed utterly fail – in the sense of not producing the desired outcome at all. However, there is no economically reasonable way to design the process in a way that such failures are completely avoided or at least neglibly unlikely. Therefore the process is arguably not the one to blame.

@rmounce and then the authors filed a complaint and the publisher ignored it until they were publicly called out. That seems like an utter failure to me.

@Wrzlprmft potentially it is too broad if we include editors, but I have never heard of anonymous editors before this.

@PeteL.Clark I think I agree, but I am not sure if I have ever read about it happening.

@StrongBad many journals, including PNAS and the whole PLOS family, keep the handling editor anonymous when a paper is rejected.

@StrongBad "the publisher ignored it" I disagree. According to Fiona herself, they took about 3 weeks to respond to the appeal. Being slow isn't the same as completely ignoring it. PLOS have very publicly acknowledged this both on their blog and on Twitter.

While I think that blind peer review provides useful protection for reviewers, are Academic Editors generally provided anonymity?

In my experience this is rare but not unheard of.  For example, the PNAS submission guidelines specify that the editor handling the paper will remain anonymous until the paper is accepted.  Presumably this is meant to protect editors from retribution over a rejected paper.  I'm not convinced this is necessary, but the existence of these policies indicates that someone must care.

Further, is there any precedence for when a journal should reveal the name of a reviewer?

I'm not aware of any policy that allows journals to reveal the name of a reviewer without the reviewer's consent.  It could be reasonable in a case like this, but I wouldn't want to be in charge of writing a policy delineating when it is or isn't allowed.

In addition to the difficulties in writing such a policy, I am not sure I would review for a journal that had such a policy.

@StrongBad Knowing this would be a deterrent, but I actually have no idea what the policies are for any journal I've reviewed for.

Anonymity, when used for any scientific role, is intended to make it easier for people to conduct honest scientific assessments.  It is not intended to be a shield from which to attack with impunity.
In business, there is a concept of "piercing the corporate veil," in which the shielding of corporate liability limits is removed in cases of gross misconduct.  Likewise, I think that it is reasonable to pierce the veil of scientific anonymity in cases of gross misconduct.  This recent case of "please add a male author" is one such; others could include abusive personal attacks or plagiarism.
I'm not sure that exact boundaries of such a policy would need to be spelled out in advance: simply saying "anonymity may be breached in cases of gross misconduct" may be sufficient.

What I find tricky is that I'd like to be able to assure referees that being wrong can't constitute misconduct.  (You are entitled to your own scientific judgment, even if it looks foolish or negligent to the authors/editors.  It might make you a bad referee whose opinion shouldn't be trusted or sought again, but it wouldn't mean you were guilty of gross misconduct.)  I see "please add a male author" as gratuitously abusive, not a scientific judgment at all, but I'm sure the referee would complain loudly that their honest scientific opinion was being oppressed thanks to political correctness.

@AnonymousMathematician I think that certain types of misbehavior mean that people need to be called out and shamed.  I'd be fine to have that referee complaining loudly: bigots generally do.  It's not for the benefit of the bigot that we name and shame, but for the rest of society.

I agree that there's no need to feel sympathy for this particular referee, and I'd be happy to see them shamed, but I'm worried about making it clear where such a policy would be applied.  I've never seen a genuinely offensive/abusive referee report, but I've seen some lazy or foolish ones and some harsh ones, and I've seen authors who were offended by what seem to me to be legitimate differences of opinion.  I hope I'll never have to deal with a referee who deserves public shaming, but I expect that a shaming policy would cause some authors to ask whether it could be applied in their case.

For example, suppose an author submits a short, readable paper but the refereeing takes an extraordinarily long time.  Meanwhile, the author's tenure case is submitted or their eligibility for a prize for young researchers expires.  Has the referee committed gross misconduct by being so slow?  I'd say no, but some people might disagree.  Or what if a referee says something clearly negligent, such as "this method is well known, as the authors could easily have discovered by consulting an expert or even using Google" when in fact no other expert knows it and there are no references online?

@AnonymousMathematician In the first case, I would say we're definitely dealing with something within the normal standards of the community.  In the second case, we're starting to push into active negligence or hostility if the reviewer is making blatantly untrue statements---I think a reviewer should be expected to show their work.  I may have a fairly extreme view here, but I do think that such behavior is a form of professional malpractice and needs to be dealt with by a community, though likely not with "name and shame" as a first recourse.

Yeah, I think both (hypothetical) referees I mentioned are bad referees.  Currently, the punishment for doing a bad job is having the editors think less of you, which may or may not be a deterrent.  If the editors recognize a bad report, they will ignore or replace it (I can't believe that didn't happen at PLOS ONE).  Adding a further possibility of public shaming is not necessarily a bad idea, but it would lead to a lot of debate on how to apply it, and I'm not convinced it would end up being applied as sparingly as I think it should.

@AnonymousMathematician For the negligent example you give, a couple of other considerations are: It may not be clear to the editor that this is blatantly untrue without a back-and-forth with the author & reviewer (and so far I personally not bothered to tell the editor when a referee has based a negative opinion on a blatantly wrong statement, though this has only happened once or twice to me), whereas a diatribe or sexist remark should be.  Also, it could turn out that this was due to an honest misunderstanding on the part of the referee, for which public shaming is inappropriate.

@AnonymousMathematician But I think if one were to try to make an clarify a policy of "public shaming," it would be better to spell out a conservative list of things one could public shamed for (e.g., sexist reviews or a history of vitriolic reviews against certain researchers), possibly require warnings for a first offence, and have an appeals process for someone slated to be shamed.


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What's more important in choosing a PhD program, advisor or institution?
In terms of judging a doctoral program--and possibly also relevant for postdoc-ships(?)--which is the more important consideration, who your advisor is or the institution at which you study?
Obviously both are important, but when it comes down to it, which should weigh more heavily?
For example:
Professor Alpha is a premiere name in the field, but he's set up at Southern State University, an otherwise middling school. Perhaps he's there because he's a big fish in a small pond and gets carte blanche and limitless resources to do what he wants. His graduate students are thus treated similarly.
On the other hand, Professor Beta is a new, unproven professor at Top University, a world-renowned, leading institution. He personally may not have the resources and freedom as Professor Alpha, but he's at an institution whose name carries weight. Therefore the school certainly has the capacity for the same, if not more, resources, but access for Professor Beta's grad students will be more limited as they must be shared with other professors' groups.
Assuming all else is equally appealing (funding, location, research topics, etc), which offer do you choose, or which program would you hold in higher regard?
(The situation doesn't have to be so stark as like Harvard vs. Middle-Of-Nowhere University, but it makes the point clearer.)

I assume you're asking mainly about the experimental sciences, but let me point out anyway that in mathematics many students enter a Ph.D. program without yet having a clear idea of what subfield of mathematics they will specialize in.  In such a case, the weight obviously shifts toward the institution.

Another important consideration is, even within the same university, whether you want an older, more-established, advisor or a younger, more-to-prove one. Both have their pros and cons.

I think the answer to this question varies a lot between the US and most European countries.  In Europe, the distance between top and bottom universities is not so steep (in particular when compared within the same country) and it is possible for a middle tier university to have a top-class group in a particular (sub)field. I would say that in (most of) Europe the group (or PI) should carry more weight. Possible not-so-clear-cut cases can be Cambridge, Oxford, ETH Zurich, etc.

Obviously one needs a competent advisor with whom one is compatible. But assuming that both professors qualify, I think what matters most is the quality of the students who will be your peers. You need to surround yourself with students who, from day 1, expect nothing less of themselves than to produce novel scientific research of the highest caliber, present it at top meetings, publish it in top journals, and forth. Ultimately you will learn more from your peers than from your advisor. A sufficiently talented and ambitious cohort will hold the bar high for you and push you to excel whereas a sufficiently talentless and unambitious cohort will help you make excuses for your own failures to reach your potential.
In my experience, top schools with top graduate programs have the sorts of students you want to surround yourself with. Second tier regional programs may, but I have yet to see it.

How can one asses the quality of PhD students?. Check their publication record?

In many STEM fields in the US, prospective PhD students visit as part of the admissions process. This is the best opportunity to assess the quality of the PhD students. Meet them. Talk with them. Get a sense of departmental culture. Figure out whether they are publishing, and where. Etc.

As the OP almost 2 years later, I can confirm that this was easily the best advice. Good advisers are important, but you heavily rely on and collaborate with your peers. High quality and collaborative students is a big thing

Delighted to hear that, @marcman!

@marcman One might call the core of academia a social constructivist approach to building knowledge. Peers are who you co-construct with; you bring your own unique perspective, and they their own. Together, you build entirely new ideas, processes, etc. If you consider your advisor just another peer (but perhaps with more experience), you may just find that your plural peers provide more room for growth, and thus to be more important :)

Caveat here: "high quality and collaborative students" doesn't correlate one-to-one with, e.g. USNWR ranking. I turned down a top school in part because other incoming students seemed like arrogant jerks.

I personally think that your rapport with your supervisor is of primary importance, and I personally didn't care to choose my PhD by university when I got the opportunity. (Assuming that both your options are offering what you want from a PhD in terms of subject and skill sets.)
As a final year student in biomedical sciences, what I have mostly found is the following:
Money
Your supervisor should be able to fund you, and your experiments fully. You should not come to a situation where you are choosing the second best option (especially in biology) because of the lack of funds. This will ruin the quality of your thesis.
Go-to guy
You should have a supervisor or a post doc in the lab who will be able to help you when you initially start out to answer your stupid questions. There will be many, and you'll need to find some one in the lab who is friendly enough, and patient enough to answer them. You'll know them when you see them. And of course, the other members of the lab do make a difference. See what they are like.
Higher up or lower down?
You should need to ask yourself, how high up the totem pole you want your supervisor. Remember, the higher up they are (especially professors) the lesser you are likely to meet them on a regular basis, and most probably have lost touch with bench experience. On the other hand, profs have better connections and their recommendation carry weight.
The argument for university preference goes like this:
If your prof doesn't have his own lab, and relies on community equipment, then you must go to a university which has the money to spend. Otherwise the choice of university is mostly trivial.

A very small answer, in addition to other good observations: I do claim that a particular analogy is relevant. Namely, would you want to have good parents but live in an unpleasant town, or bad parents but live in a nice town (if one imagines that "nice town" can truly make sense if one has bad parents).
Yes, if your penchant is for complete commodification of the whole process, then the parental/familial thing can be scoffed-at. But I'd recommend against going too far in that attitude.

Here are some additions to the other answers.
First, since I don't know how you've made your assessments of A & B, a couple of things you should look into if you haven't already:

Look up what kinds of jobs the former students of Professor Alpha got.  If almost all of them got truly great jobs, then working with him seems like a safe (though not necessarily the better) choice.  If not, maybe you should reconsider his pull in the field.  (But if not, one factor is that his students may not be as strong on average as those at a better university--still this is bad for you as in Corvus's answer.)
Check to see if Professor Beta was hired as an assistant professor or associate professor.  At many top departments, it's really hard to get tenure, but they hire more established people they are sure of at the associate leve.  So if Beta was highered as an associate professor, then it's safe to say Beta is "proven."
If you have professors in this field, ask them for their opinion.

In addition, the other answers don't seem to address your job prospects after getting your degree at one of these universities.  For your question, "which university would you hold in higher regard?", if I were reviewing an application for a job application without specific knowledge of the professors, I would hold the higher ranked university in higher regard.  If you're looking for a research job, and you have a positive answer to point 1 above, then it shouldn't be a problem as enough people in your area will know how good Professor Alpha and his students are.  But if you're applying for more teaching-oriented positions, or positions in industry, then graduating from Better Name University can help you.  (It's not just the name, but other factors as well: more contact with more talented people, etc.  See this related question.)

The most important thing is your adviser. Obviously you're not looking for a label, you want to do some valuable stuff in your PhD period.
The professor in middle-of-nowhere university has the vision that's needed and can make you the researcher you need to be.


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Can I still pursue a research career after a possibly lengthy break?
I've been offered a PhD position, but I'm forced to decline it due to family reasons. However, once the situation becomes more stable, I will re-apply again. What concerns me most is whether it's still possible for me to pursue a research career after a long (2-4 year) break?
I hope that perhaps once the crisis is overcome, I could look for part-time assistant/technician jobs in labs, which would allow me to still stay close in research before I would submit my applications for a PhD.

Some universities allow you to defer admission to a PhD program by a year (I don't know if more than a year is acceptable). If you have that option, you need not re-apply.

Please contact the dean of graduate studies at the department that accepted you and describe your situation.  Various creative approaches to this problem may be possible.  For example, if the first stage of your degree program involves coursework to prepare for some qualifying exams, it may be possible for you to take some of these courses at a university closer to home, with careful planning, and direct communication between the two departments.
If you are not already working with a counselor or therapist, I suggest that you find someone you like to get started with.  When going through a family upheaval this can be helpful.  Also, in the safety of the counseling relationship, you may gradually become comfortable about exploring different ways of balancing supporting your family and pursuing your own personal growth.  Sometimes the stress of the situation one is living through at the moment makes it difficult to see all possible options.

There is no need to think you cannot pursuing a research career after a long break. You can (re-)apply for a PhD or research position whenever you want. You will always have your existing research history listed on your resume.
It is also not uncommon for people to first work in industry (after a Bachelor or Masters), and then return to research again.
A PhD research can be a posted research project, but also a research suggested by yourself. As such, your current offer might still be a valid research in a couple of years, if it was your own suggestion. If it is a posted project, often funding and time limitations exist, which means that someone else will perform this research. In that case, your future application will have to be your own suggested research, or an application to another posted project.
Of course, in your future application it is certainly useful to mention the reason of your gap in your research/working career (you mention 2-4 years).

I'm not sure what your background is so this is very general. One way to go about it is to test the waters before committing to a major project. I'd say start with a smaller project (e.g. 3 months) and see how it goes. Once you've gathered some momentum, you will be in a better position to take on a PhD project. Alternatively, a part time Phd might be more suitable for you.

My background is in Molecular Biology. This PhD requires me to move to a different city, very far away. Unfortunately my family suffered a major accident and I need to step in and take charge of the running business which is our sole source of income and is essential to cover medical treatments. With that, no matter how much I want, I cannot relocate.

I'm sorry to hear about the difficulties in the family-I'm guessing your phd would involve a lot of lab work-not something you can do from home. Perhaps you should explore other options? Are you planning to go into academia after the PhD?

You're correct, my PhD is very lab work-based, which is something I really want to do. I hope to then progress to a Post-Doc position and set up own lab group. I don't know how long it will be before I can resume my further studies, let's assume 1-2 years, things are more stable, I can start with part-time lab positions to start building up the work expression again and then re-apply for PhD programmes. Or if not, take a Master research degree if that would help. I don't want to give up a research career.


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Can I lie about my GRE score to get a better letter of recommendation?
I have a situation. I have got GRE score of 324. My academics are pretty strong as well (5.1/6.0). I am applying for MS to US universities. In the process of gaining letters of recommendations, I do not have too many options. One of the professor at our department has pre-written letters, because he is busy most of the times. He makes rudimentary changes to it to make it suitable for each candidate, but the gist remains the same. From the experience of past students, he asks the GRE score and he somehow thinks that it is the only "good" metric of evaluation. So he has some 3-4 versions of these letters and based on a GRE score he selects a theme. I also came to know that if student is under 320, letter is excellent, that is, it is more balanced. And over 320, there is more of a high pitching.
I am not targeting many 1st class universities. I am more selective and I really do not want this bluffing. Obviously, I cannot reveal to him that I know his procedure of writing the letters and I need one for below 320. My question is, may I lie about my GRE score to him? When he gets emails from universities, can he see my GRE score? I definitely do not want him to know that I lied, at any point in time, even after admission. Are there any other options?

The GRE score range is 130 to 170, and a higher score is better. You refer to a score of 324, and apparently lower is better in your scenario. Please [edit] your post to clarify.

@ff524 GRE score range is 340, 170 for Quant and 170 for verbal. FYI - https://www.ets.org/gre/revised_general/scores/

I haven't heard people refer to a sum score like that before.

I would be concerned about asking that professor for a recommendation anyway. If you have noticed his system, it is quite likely other professors in his field have noticed as well, especially if they have seen two or more practically identical letters from him.

On a practical side, what happens if your professor writes "... and so-and-so's GRE score of XXX etc etc etc ..."?

thank you everyone, i got my thinking straight. i'll talk with him this weekend, and will update what happens next.

I am tempted to say: "Never ever lie on an issue like that." Actually, I say: Never ever lie on an issue like that. First of all, it's wrong, plain and simple. Second, from a more practical point of view, you never know how it's going to bite you back.
It can taint you forever, even if here you are downplaying your achievement. It will be difficult for people to believe that you actually did that, and they will start believing that you are untruthful in other aspects, too. Frankly, it will raise more than a few question marks if it should come out.
You'll have to live with the exaggerating letters, or else to find someone else to write you a sensible one.

Disclaimer: I do not know about GRE scores, but understood from the gist of the question that a too high score would cause the recommendation to be ridiculously exaggerated which OP wants to prevent. Since I am aware of analogous cases in other contexts, I think the question is legitimate. Perhaps the GRE information should be corrected/adapted, as the score range of the OP seems double the official one.

No, you may not lie about your GRE score. Because:

ACADEMIA IS A VERY SMALL PLACE

Seriously, let me say it again (in normal letters this time):
Academia is a very small place.
Really, you have no idea how small of a place academia is. Trust me, this will come back to bite you, as Captain Emacs said. People talk, and one way or another, because of some unexpected set of circumstances that you cannot control or predict, your lie will be discovered and you will pay dearly for your mistake, possibly with irreparable damage to your career. So remember this: lying is in general a bad idea, but lying in such a small place as academia about a crucial thing like your GRE score is just inexcusably foolish and risky.

And even if it were big, it's still too small for such a "trumped"-down story. +1

The best thing to do is just talk to the professor about this.
If you're worried that the recommendation letter might be too strong or too weak or too generic, just talk to him. Express your concerns and see what he says.
If you don't think his letter will benefit you then try to find an alternative letter writer, but don't lie.
Side note: I find it odd that you know this information considering recommendation letters are usually never made available to students.

I was tempted to write Marquis de LaGrange's "When we ask advice, we are usually looking for an accomplice." but your case is actually quite interesting as you are ostensibly lying "not in your favor". I agree with the others that lying will come back to haunt you, perhaps immediately if the prof asks to see proof of your score. Personally I'd be pissed about being lied to, no matter in which direction the lie goes.
So perhaps two other options:

You write that you do not have too many options, but you also write "One of the professor at our department has pre-written letters" -- so there are others? Is this prof really the right one, both in the sense that you had to lie to get the letter you want (now), and in the sense that his practice is apparently known? If he is busy and these are his practices, then how much value does this letter have? And are other profs not a better choice?
If you really want a letter from this prof, can you talk to him about the letters, not his process of selecting them? Can you, for example, say that you have seen both letters "low" and "high" and that you'd much prefer the "low" one? It's walking a tightrope here, as you cannot tell him what to write and he might be convinced you deserve the "better" one (and avoid "low" and "high"). But if it does not blow up in your face, it might work.

There are also two other aspects:

If this prof is known and his procedure (or letter of recommendation) as well, perhaps the issue isn't as large as it appears to be. You might be shooting yourself in the leg here when you go for the one you consider to be "better" here. It also reminds me of the practice to exaggerate a little in applications. It's a practice I abhor, so I understand the concerns, but truth is, if everyone exaggerates and everyone knows about it, being honest is actually lying in that situation. Yep, sounds strange but true. You might be going against social conventions without others knowing, so they get a wrong picture of you and your qualities. In being "formally" honest you might provide a wrong picture of yourself and undersell yourself.
It appears as if you want to match the quality of the recommendation to the level of the university you want to apply to. It seems like a fear of being "overqualified". But if these universities have two applicants and one spot, which one will they chose? Do they really go for the one that is on their level (that would be brutally honest) or will they go for the one that can best improve their research? I don't know the answer but perhaps it's something to think about.

thank you. I was on similar lines that speaking truth is actually lying in this case. But your answer helped me to look at it from a different perspective.


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Examples of research resources for which Wikipedia is known as being amongst top referrers?
Wikimedia sites – and Wikipedias in particular – direct a lot of traffic to many web resources, including research-related ones.
Click stream data is not recorded on the Wikimedia end, so the alternative approach to finding out how important Wikimedia sites are in terms of traffic to research resources is analyzing the latter's referral logs.
One such analysis that was made public is from CrossRef. I am looking for other cases where such analyses have been made public.
Interesting questions to ask about such datasets:

Is wikipedia.org or one of its sister or subdomains (e.g. wikimedia.org or en.wikipedia.org) amongst the top referrers?
Is that pattern stable?
Since when has this been the case?
What are/might be the main drivers of that traffic (in the case of CrossRef, it's Wikipedia readers clicking on references cited by their respective DOIs)?

I bet if you ask on Stack Overflow you're quite a bit more likely to get an answer.

I agree, but am not sure the question would be in scope there.

I agree.  Wish SE would see the value of these kinds of cross-population posts.  But that's a topic for Meta, innit?

I asked on Meta, you might be interested in the one answer I got: http://meta.academia.stackexchange.com/questions/1759/is-the-a-better-way-to-cross-purpose-technical-academic-questions/1760#1760

I'm voting to close this question as off-topic because it appears to be a research proposal, not a question about academia.

This doesn't directly answer your question, but in 2012, the Biodiversity Heritage Library's then-technical director published a presentation reporting on how users from Wikipedia stayed longer and browsed deeper than others, which included some analytics information. You could drop the the BHL an e-mail and see if they'd be interested in sharing any more recent details.

Some BHL members attended Wikimania 2012; I haven't seen them on the Commons, but they might be worth approaching! http://blog.library.si.edu/2012/08/wikimania-2012-bhl/


text:
How does a professor know when a research project will get expected results?
I read that "One difficulty with research problems is that it is hard/impossible to know if the problem is easy or not" or when it can be solved. So how a graduate-research student (i.e., PhD or MRe) knows what to pick as his/her work, and/or how can his/her professor 'predict' it? Because if one knows if it is possible or easy to solve then he/she likely knows also how to solve the problem, hence it is no longer an open question.
If professors can't decide the period of time a project to be finished, how they risk tuition paid by students or scholarships granted?
EDIT - My intention is mostly on Pure Mathematics.

Who says that they do?

@Nate Eldredge - TravisJ in http://math.stackexchange.com/questions/1323577/small-open-problems-in-real-analysis-as-graduate-research-project . the last sentence is also from him (changed literally).

As TravisJ says, it is hard/impossible to know!  So that means that professors often do not know when, or if, a research project will get results; they just have to guess, and often are wrong.

"Because if one knows if it is possible or easy to solve then he/she likely knows also how to solve the problem, hence it is no longer an open question."
There is still the issue of collecting data. Are you talking about a purely theoretical field of research?

In my own (recently completed!) PhD journey, my thesis was a moving goalpost.  First I thought I would do work on generalizing the Ohsawa-Takegoshi theorem.  I learned a lot of technology to digest the original proof, and poked and prodded to see if I could get any improvements out.  None of my ideas ever panned out in this direction, but throughout the process I developed enough mastery of the underlying technology that I could prove some nice related theorems which were only tangentially related.  Basically, follow your nose, but be open to new opportunities when they present themselves.

This is just one example of how success isn't a measure of  how perfectly you attained an initial goal, but a measure of what you did in pursuit of that goal.

The interaction between student and professor should not be a one-shot set-a-problem. Instead, they should be talking frequently, often once a week, and adjusting the nature and direction of the project based on what is being learned during it.
The project starts with some idea, from either the professor or the student, that the professor thinks likely to lead to an appropriate outcome within the available time.
As time goes on, the student should come to learn more about the project than the professor, and be reporting progress or lack of progress. The professor should be continuously evaluating whether the current line will lead to a good result, and encouraging redirection if not.
I am sure my doctoral dissertation was not at all what my advisor would have expected when I started on the project - it was a result of things I learned during it.

The oft-repeated claim that "the student should come to learn more about the project than the professor" is not necessarily relevant, I think, and may set up unrealistic (while un-necessary) expectations/goals...

Actually, apart from technicalities, I've rarely seen a student knowing more about a project than his or her advisor, at least in my field.

It may well depend on the field and on the project.

This depends very much on the student, the professor, and probably the field. I more or less stumbled into my topic on my own as a result of answering a question that my Doktormutter brought back from a conference and realizing that I could do a lot more with the ideas. I never discussed it with her, except to let her know that I was producing results; she was a great cheerleader and got funding for me to present a lot of it at a major topology conference, but she was working on rather different things at the time, and I’m not entirely sure that she ever internalized the definition of ...

... the property that I was studying!  But she was the perfect adviser for me.

@MassimoOrtolano It probably does depend on the field and the project, but the student knowing more than their advisor about his or her own project seems to be the norm in my experience in Computer Science. Honestly, the concept of that not being the case seems a little odd to me, though I can see how that might be more likely to be the case in pure mathematics.

@reirab Actually, it's more the case in those experimental sciences where a group is needed to develop and run a complex experiment which needs knowledge from different areas that can be acquired only after a long path, much longer than that of a typical PhD program.

As alluded to in other comments and answers, I think part of the confusion here (and often in similar inquiries) is due to the notion that there is a well-defined "problem" that is either "solved" or not. Sure, there are "long-standing unresolved" very-specific questions that may admit yes-or-no answers, but, even then, in real life one makes partial progress on things. It's not all-or-nothing.
For that matter, often a very meaningful project can amount to "try to understand X better"... where X is a thing worth understanding better. Very amorphous, really. Such situations are exactly where an experienced person can have good hunches about incremental progress, and also be able to appraise the significance of various incremental advances.
This is why most theses, and most research projects viewed "in the small", do not have an easily-describable, easily-motivated goal. Indeed, in some cases the acquisition of sufficient technical savvy to understand the short-term goal is a project in itself, and it is often the case that "understanding the question" is sufficient to nearly have an answer.
From another angle: it can happen that a project is very plausibly feasible, but the execution of it would require considerable exertion. That is, the thing does not magically do itself. And one never knows with certainty what unexpected intermediate tasks may arise.

A good problem given to a Ph.D. student should split into a series of almost certain, quite certain, difficult, hard, and almost unachievable results. A question of the form "Problem XYZ might be solved using the following new approach. Try it!" is not a good problem, because after a lot of work you will quite likely get "No, this approach cannot work because ...". Such problems are better left for late postdocs or tenured researchers, who can afford to take risks. A good problem is more like "For all finite groups we expect the following. For abelian groups I can immediately sketch a proof, although filling in the details will take a few pages. For nilpotent groups you can probably proceed by induction. For solvable groups I still expect induction to work, although there are some problems with ... . In general you have to understand ... ." Furthermore both the student and the advisor have to be flexible to deviate from the original plan of work whenever there is a reasonable chance that something can be found in the neighbourhood.
However, although the advisor has the duty to minimize the risks involved with doing a Ph.D., he cannot eliminate them. I can only be certain that something works, if someone has done it, and then doing it is not a Ph.D. project anymore.

Professors/senior researchers typically do an educated guess regarding the time needed to solve a problem, based on earlier experiences with similar problems.
Of course, it is still a guess, and they can be wrong.

If a professor's guess is wrong, the PhD student will end with no results to publish. What about the student's money and time and of course degree?

@MKR: That is an inherent risk of doing a PhD.  Anyone who wants to start a PhD should be aware of this risk, and be willing to accept it.  It can be mitigated to some extent: if after some time the student is not making progress on the problem, then as Patricia Shanahan says, they can work on something different.

@MKR I see where you are going. But that is a completely different thing, one doesn't need to fully solve a problem to get a PhD, but you have to show enough progress (for example, solving subproblems that help with the main result). In fact, many PhD projects start with a very vague and open ended description, and as you progress, you will find where it leads to.

@MKR "If a professor's guess is wrong, the PhD student will end with no results to publish." Yes. You will be surprised to learn that in the real world, few things that are worth doing have guaranteed positive outcomes.

@MKR Sometimes, though, in other cases, what the student found in the process of finding that they couldn't solve the problem may itself be worthy of publication. At the very least, you've then saved other researchers the trouble of attempting the same things that didn't work. More likely, you've given them insight into better understanding the problem, allowing them to move closer to a solution (or, sometimes equally useful, proving one doesn't exist.)

As a professor, I act as a scout for every project my students are working on.  I also help students separate the 'wheat from the chaff'.  This ensures students do not bark up the wrong tree, go on a wild goose chase, and more importantly, telling me something is impossible because they lack knowledge or are lazy explorers.  In addition, this allows me to have back-up plans should a direction fails to pan out.   In general, similar to what another reader said, we know what SHOULD work, but the details are left to the student to sort out.


text:
What should I state for "expected salary" in a tenure-track job application?
I am applying to a tenure-track assistant professor job in an applied math department,
for which the job posting states

Applicants should state their current and expected salary in the application.

Questions:

Why does the department ask for "expected salary"?
Is it because they are trying to exploit my naiveté?
What number should I state in my application?
If I state a number that is on the low side,
will they use that to offer me a lower salary?

At the moment, I am thinking of just stating my estimate of the mean salary
for new assistant professors at math departments,
which according to a Tenured/Tenure-Track Faculty Salaries Survey
is $71,412.

If they are unable to pay you a decent salary, you have no big benefit to answer. If they are able to pay a decent salary, asking that question means they are trying to exploit you and pay you less than they should, so answering is a net negative for you. Either way, don't answer.

Tell them to make you an offer, and that you'll compare it to all the other offers you're getting.

You might want to also look at similar questions from TheWorkplace

I feel it's kind of obnoxious to ask for an expected salary, and it does raise issues of whether the answer could be used to lower the initial offer (or decrease the applicant's negotiating power).  I don't see anything wrong with giving a vague answer or just saying you are flexible.  If you specify a number, you should try to choose one that's representative of the type of school you are applying to, as Danny W. suggests.
As for why they do it, one reason is that salaries vary enormously.  A regional liberal arts college may pay less than half as much as a leading research university.  Some U.S. states scandalously underfund their state universities, so there can be dramatic salary differences between what you'd think are comparable institutions.  The net effect is that schools that aren't able to pay a lot worry about attracting candidates who have no idea how little they pay.  They don't want to waste time trying to hire someone who will never accept any amount they could plausibly offer.  One way to get around that is to announce a salary range.  However, some departments are hesitant to do that, perhaps because they don't want to publicly emphasize how little money they get (and thereby humiliate themselves or discourage applicants).  Instead, they ask for an expected salary and filter out anyone who names a figure far out of their range.  I don't like it, but it seems to work well enough that departments keep doing it.

Often the question is inserted simply because the HR people's automatic job-search system is built for staff rather than faculty. If possible, don't answer: I cannot think of a situation in which any answer would benefit you, and I can think of lots in which it might just possibly hurt you.

Of course, if they did publish the salary range, then it'd save them lots of time & effort as they wouldn't have to consider the people who might make it through the interview process, then reject their salary offer.

If it's a public university, look up the local/regional salary website that covers it (like the Texas Tribune site). Record the names and salaries for all of the Assistant Professors in that department. Estimate via Google search when each of them started at the university in question. Add a year (since the salary sites are usually a year out of date). Assume 2%/year annual raise. Work backwards to their starting salaries. Decide where you think you would rank among the tenure-track professors if you were all starting at the same time, and pick that percentile among the salaries and submit it. If public data isn't available for the university you are applying to, model a similar university in a similar town that does have data available, and then adjust for cost of living.
This is an applied math problem par excellence. You best option is to use your skills to predict a reliable answer.

The applied math problem of "figuring out what you're worth" is not necessarily the same as the strategic problem of "figuring out what to say you're worth" :)

You are worth slightly more than the median starting assistant professor in that department.  Otherwise, they won't hire you.

@JeffE, good thing I didn't suggest picking the median!

I should have said: You are worth slightly more than the median starting assistant professor in that department, after adjusting for inflation.

Yeah, I should have said that you need to push these salaries forward based on inflation (which has been low in the US over the typical tenure clock of anyone that would still be an assistant prof).

If you want to take the safe approach, it may help to choose the mean assistant professor salary for the kind of school you are applying to, and where the school is: a state school in Wyoming will have a lower average assistant professor salary than a private research-level school in Cambridge, MA, for example.
And, although I haven't been on the job market, I know (from discussion with my adviser about this question) that while this may be a factor, others are more important: how much does the department want you and what your other offers are, being two of the biggest.

Taking the numbers from higheredjobs.com, you'll see that there is considerable variation across types of institutions- the number you quoted was for "research universities", while "doctoral universities" was a separate classification with a lower average salary.  The survey also didn't distinguish between private universities and public universities (salaries at top private universities are considerably higher.)
The American Mathematical Society also publishes an annual salary survey that I'd encourage you to examine.  The AMS numbers actually show higher starting salaries at the most prestigious research universities (over $80K), but also show much smaller starting salaries at the bachelors and masters level institutions where most of the jobs are.  I think this AMS survey is more reflective of the variation in salaries than the CUPA survey that higheredjobs.com reports.
I also searched AMS's web site for job ads that featured this requirement.  There were five such ads, Two were for positions outside of the US (where these salary surveys aren't meaningful.)  One position is for a department chair (an administrative job that these salary surveys don't cover.)  One position is for a postdoc.  The last ad is for a named associate professorship (an endowed chair) where the department will be looking to hire talent away from other departments.
Asking candidates for a more senior level position (department chair or the named professorship) what their salary demands are is a reasonable thing to do- you don't want to waste everyone's time interviewing someone who is already much better paid than you can afford.  It makes a lot less sense when you're talking about an entry level tenure track position where most of your candidates are applying from temporary positions (VAP or postdoc.)

Searching SIAM's job advertisements, I didn't see any positions that had this requirement that weren't also on the AMS web site.

One of the advertisements that does include this requirement is looking for someone in computational statistics, an area where new PhD's are pulling down salaries of well over $100K per year in industry.  In a situation like that where any qualified candidate could earn much more in industry, this doesn't seem to be an unreasonable thing to ask of applicants.

Just write negotiable. That's it. Then negotiate when the time comes.
As a rule, I avoid salary discussions before an offer. If asked, I answer that I'm flexible and I'm confident we could come up with a mutually agreeable figure. Then I move on and start asking questions about the job.

It's easy for me to say this, since I'm not applying, but I simply wouldn't list anything.  There's always some risk when leaving out a part of the application that someone is very bureaucratically minded, but I think in this case, the chance is pretty small.  It's very hard for me to imagine the conversation in the hiring meeting going: "This application looks very promising."  "But it doesn't list his/her current salary.  Well, in the trash it goes!"
It'll be trickier if someone directly contacts you, points out that you missed this and asks you to clarify.  At some point, if you decide getting the job is more important than optimizing your salary, you may have to just tell them.  I personally find this a pretty insane request, though.

Q.1: The dept wants to know whether you have realistic expectations about compensation for this position. Trying for >$20k over median for entry level position for institution of this type/location may raise eyebrows.
Yes, they are also trying to exploit an applicant's naiveté (although obviously this should not be taken personally). In particular, a reasonably low figure might suggest to them that salary will be a non-issue. If their resources and room for negotiation for this position are tight, it might tell them which applicant may be worth their time and which might not be worth a significant investment of time if their offer is likely to be out-matched by another institution.
Q.2: If the number was not used at all, it would likely not have been part of the application. So most likely, a very low "self-appraisal" might yield a lower offer.
That said, it does not necessarily mean you should not be modest in your self-appraisal. It is unlikely that your final decision will be solely based on salary. Money only matters when you don't have any. As soon as you have a sufficient amount, other things kick in and shape the quality of life. Friendly colleagues in the department. Overall budget situation at the university and on the state level, and projections for the next 5-10 years. Location, amenities, recreation opportunities, and cost of living in the area. How long you plan to stick around at this institution (keep in mind the likelihood of raises, which over 5 years can lift a salary to a level higher than what you may be shooting for now, risking rejecting offers that might not be quite up there from yr1). Good luck and hope this helps.


text:
Extremely lost and unmotivated in new lab, what am I supposed to do?
I'm currently in a Ph.D program for pharmaceutical sciences. Long story short my background is cell biology and I originally worked in a Cancer lab. My lab relocated and I could not follow. I was placed into a medicinal chemistry lab. This is how things work here, we get little choice. Anyway, I love my PI hes great, and my lab mates also great. However I have no clue what I'm doing. I have a project thats moving along nicely but once again . . . I don't even know why it's moving along.
I don't understand chemistry, I have a mere 8 credit hours from my undergrad in chemistry, and now I am asked to operate under conditions that would require a significant chemistry foundation. In my eyes all I have been doing is mixing what I am told to mix, run it through a column, perform TLC, NMR, and mass spec, and that's it. I don't know why I'm using one solvent over another. I don't know the mechanism behind any of my reactions, and hours and hours of googling has yet to teach me anything about them. No matter how many questions I ask (and I ask a lot) I don't retain anything or understand half of it because it's all upper level concepts to which I have no base to put them on. How am I suppose to defend any thesis like this? How could I ever start a career? I have no motivation in lab because I don't understand anything,at all. I don't have either the time or the drive to teach myself years of chemistry I never learned. Moving labs is 100% NOT an option here. I don't know what to do, any advice is appreciated.

Let's boil it down. You have 3 choices. (1) Learn some chemistry, starting off at the beginning. (2) Accept that you're just a trained monkey/robot (3) Look for another job

Maybe your PI can help?

If you are more than two years from graduating in this, and you are convinced you cannot catch up on your chemistry, quit. Your PI is an idiot to have accepted you, and he's abusing you as a lab monkey. He might not have realised it, don't judge him too badly, but it's just terrible.

@Karl - Agreed that it isn't a great situation, but the OP is working towards a PhD which I assume would get him another job eventually. So maybe working as a lab monkey would be OK until he graduates.

I know an entire chemistry undergrad sounds like a lot to self-study (it is!), but the missing knowledge you describe isn't actually that widely spread. In my undergraduate, it was covered in two semesters: Intro Organic and Advanced Organic. Everything you describe (aside from mass-spec) was covered in those two classes (semester-long). I know students who started doing undergraduate research after finishing that sequence, so you may only need the equivalent of a few classes to get the necessary base knowledge.

OP here.Sorry i'm late to the responses, busy with classes and such. I appreciate everyone's advice. For now I have some books ordered which are introductions into medicinal chemistry(my labs focus). I guess I will try to catch up but if I still feel this way after another semester I may have to jump ship, thank you all.

"I don't have either the time or the drive to teach myself years of chemistry I never learned." -- Usually "no time" is what we say when we actually mean "not that interested, sorry". So my reading is that you're not sufficiently involved in this to pursue at PhD level, thus you have to decide between playing monkey or leaving. Whatever costs you less sanity and peace of mind.

This does seem like a difficult situation but don't lose hope!

Moving labs is 100% NOT an option here.

That means that you will have to adapt to your current environment - i.e. to learn some core chemistry concepts. Without them, it is indeed difficult to find motivation to work on a project you don't understand.

I don't have the time, nor the drive, to teach myself years of chemistry I never learned.

Time: I'd say that catching up on the background is one of your main priorities and is essential for your future as a researcher (given the circumstances). Luckily, you don't have to catch up on "years" of chemistry - start off with the areas that are most essential to your work (not specific questions, however, but rather general topics that are closely related to your experiments).
Drive: As you keep broadening your horizons, keep track of all the things you've learned to stay motivated! There will be a lot of things to catch up on but try to notice all those little moments when the knowledge that you've acquired makes your job easier - there will be a lot of them, and they certainly count.

No matter how many questions I ask (and I ask a lot) I don't retain anything or understand half of it because its all upper level concepts to which I have no base to put them on.

Sounds like you already know what you need. Whether it is auditing a class, reading a textbook, or taking an online course, you need some foundational knowledge to build upon. Googling won't cut it.
Most importantly, be patient. It will take a while to become proficient in a new area, but it's certainly possible. Celebrate small victories and use this as an opportunity for growth. Good luck!

I'm going to assume, as you requested, that you're absolutely stuck where you are, unable to go anywhere else.  I don't know this is true, but for the purposes of my answer, I'll assume that it is.
Well, sure, you could try to play catch-up with a whole lot of chemistry.  But there might be another way out of this.
What if you were to take a step back and look at the various research interests of the PI?  Find something that interests you, where you have something to contribute?  In other words, find some point of interdisciplinary intersection.  And leave the heavy duty chemistry to the people in the lab who trained in chemistry.
If there's nothing that jumps out at you from the PI's publication record or description of current research interests, then try to find at least one paper that uses something he's knowledgeable about, and something you're knowledgeable about.
Or, think in terms of what you want to learn from this guy, that would help you later when you get back to your cell biology.
Hopefully this PI will help you find some intersection with him -- a topic of your own.  If not, find someone else in the department to get you started.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
PhD salary in Germany according to TVöD
I have a PhD acceptance letter from an institute in Germany. They have written that my salary would be according to TVöD (collective salary scheme for the German public service).
I searched about that, but there are different ideas.

You should ask the institute for the details.

Welcome to Academia SE. Can you please [edit] your question to specify what exactly you want to know? Is it the total salary, or how insurances and similar work?

@Thomas: Whatever the question may be, the answer is most likely valid for the vast majority of German PhD students, so it makes sense to have it generally answered here.

Previous appearances of TVöD on this site: Net salary for PhD in German university, Post-doc Salary in Germany.

The following answer applies to all public-service salary schemes (TVöD, TV-L, TV-H, etc.) that apply to PhD students. The information that is most likely missing is:

Your class (Entgeltgruppe): PhD students typically paid according to class 13, which is the lowest class for positions requiring a master’s degree or equivalent. As even postdoc positions with class 14 are extremely rare, it’s safe to assume that this is your class if no further information is given.

Your level (Stufe): You will have the following progression of levels based on experience:

first year: Level 1
second and third year: Level 2
fourth to sixth year: Level 3
after that, you hopefully finished your PhD

You will start on the first level – unless you already worked in the German public service on this level before (or on a job that is acknowledged as comparable), e.g., on another PhD position.

Now, the offer will have to state how much you are officially working. It’s usually somewhere between 50 % and 75 %, but may also be 100 % – this mostly depends on your field.
This should give you all you need to obtain your gross salary (brutto) from the tables or calculators.
Keep in mind that taxes and insurance will be deduced from this, which depends on several aspects such as whether you are married, have children, whether you will use the German public employer's retirement provision (VBL) etc. However, a considerable portion of the taxes will actually be to your direct benefit (health insurance, statutory retirement provision, etc.) and things that you would pay with your salary in many other countries.

In computer science, the standard working time for PhD students is 100% in most places.

@lighthousekeeper Also true for engineering in general.

I can confirm that 75% contracts were the norm in Berlin as of last year, but it was my impression that there was a move away from 50% studentships and that anything under 66% was now frowned upon. Is that impression unfounded?

To the question raised by @E.P.: As far as I remember, 50% were normal around the year 2010 in my field (mathematics) in Nordrhein-Westfalen, but around 2014-2015, new contracts usually were set at 75%.

@E.P.: When I was searching a job a few months ago, I saw a lot of 50 % contracts in various fields. I cannot remember any offers of 75 % contracts or higher – but then I wasn’t searching for a PhD position anyway. Anyway, this is usually given on the offer, so the asker should be able to find out themselves.

@Roland Back in my day (up to 2014), some group leaders in Chemistry reapportioned the money because they wanted to pay all students equally (which, as a pure coincidence, was also less than 65%, namely 50%).

I can confirm that 50% is currently the norm in mathematics in Hamburg.

Since this has just popped up on the start page again, please allow me a brief nitpick on the sentence "class 13, which is the lowest class for people with a master’s degree": More precisely speaking, class 13 is actually the lowest class for positions that require a master's degree. It is possible to hold a master's degree, but to work in public service in a position that does not require that degree; in such a case the salary will typically be lower than class 13.

@JochenGlueck: Corrected, though it should be irrelevant here.

More information is required to answer your question. However, I want to give some basic information.

Where are you employed?
The TVöD consists of several categories, e.g., the TV-L (afaik used by most universities) as well as TVöD-Bund (used by some publicly funded non-university institutes (e.g., Fraunhofer)). Ask your employer for this information if it was not provided to you, yet.
Do you have a 100% contract / full time job? Depending on you employer and region in Germany, this might differ. I know guys who have a 50% contract, thus, there is 50% payment for 50% time. (Please note, that you will still be expected to be at your institute like a full-time employee).
(When are you going to start? The labor unions will negotiate an updated salary in beginning of 2018. So you might finally end up with a few more percent.)

You will most likely start at E13 in Level 1, as this is the standard payment for PhD candidates. There you can find a table for TVöD-Bund:
http://oeffentlicher-dienst.info/c/t/rechner/tvoed/bund?id=tvoed-bund-2017i&matrix=1
So at E13 Level 1 at a 100% employment you will start with 3657.34€/month gross income. (Net income will be somewhere slightly above 2000€, depending on taxes).

I was under the impression that 50% contracts were uncommon and frowned upon. Can you specify where this was (at least geographically), and whether this applies to recent enrollment?

The contracts were quite recent, not more than a few years ago. While I have not encountered them in the south of Germany for engineers, I know guys who are living further in the north of Germany and do not have full time contracts.

I did not get the part about being expected at the work place as a full-time worker though. Is not the worker supposed to fulfill amount of hours written in the contract?

@holmesherlock: Well, PhD positions are weird. The usual justification of this is that you are working for your job half of the time and for your PhD the other half.

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text:
Name spelling problem in recommendation letter
I have applied to several US universities for admission to the PhD program this fall, so I requested my professors to write recommendations for me.
One of the professor wrote my name incorrectly. My full name is: Md Rohan Hossain, but the professor wrote Md. Rahan Hussein. He already submitted the letter with that incorrect spelling. He completed the recommendation process online.
In this circumstances what can I do? Will it cause a big problem?

On the list of things to worry about in your life, this should be close to the bottom :-)

Let me add that it could be a problem for non-academic reference letters as it might signal that you are not an important employee if your employer foes not care about writing xour name correctly.

Do not worry about this. Just use the letter and ignore the spelling mistake (which most people will consider very minor).
As long as it is clear that this letter was meant for you (which is the case here), you are fine. People will care about the content of the letter, not about really minor spelling mistakes in your name, address, etc.

I agree with Danny; at the same time I would urge you (Rohan) to double (or triple) check anything that you write; in many fields, attention to detail is considered an important characteristic (and lack of attention, a potential negative mark). For example, your title currently talks about a "recomendation letter"...


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Dealing with the feeling of incompetence and team competition
To preface, I imagine this might come off really immature, given that I am 30 years old. I joined a university as a PostDoc after completing my PhD 6 months ago. I am yet to publish anything after joining here, I have been feeling burnt out and disorganised. I was planning to join the industry within a year of joining (It was initially envisaged as a one-year contract, but it got extended for three more years, due to my professor getting new funding, but that's beside the point). My professor is very understanding, and he is very motivated. His team is getting into theoretical machine learning and the papers he published are already making strides and catching everyone's attention.
I, on the other hand, am just starting in the area of data science. I am an average coder, and my math skills are also pretty average. If I work hard I can crank out some papers ( that is how I finished my PhD), but lately I have been feeling very unmotivated and distracted. I have a few family problems (I am gay from a conservative family), but that is no excuse for not being motivated, I know. I tried out to be a data scientist at an internet advertising firm but was rejected after the on-site interview following a Skype interview, the reason being that my practical skills were not on par (I did a mainly theoretical PhD, and my knowledge of practical algorithms is lacking).
On the other hand, my colleague who is a PhD student under my prof (only 25!) has been publishing and his works on machine learning (also theoretical), have been attracting researchers from companies like Facebook and Google, at a recent conference. As for me, the very idea of going to a conference again gives me shudders.
I am out of ideas and out of steam to be honest, but I really want to create pathbreaking research and join a top company to start my career as a data scientist. But I feel lost.
To have a good CV for an eventual job hunt, I need at least one good publication during this year of my post-doc but all the work I have done have led me nowhere to be honest.
For context: I did my PhD on random graph analysis.
I really need some guidance. I know I should have figured this out already given I am a 30 year old graduate, but unfortunately I haven't. I can blame that on my depression, but how long can I do that for? Anybody who has been in the same situation as me? Any input is welcome.

I don't see a clear question in here, but this seems to be a somewhat similar situation: https://academia.stackexchange.com/questions/89982/phd-and-postdoc-with-no-first-author-publications-realistically-what-are-my-car

It sounds like you are on the verge of burning out. I recommend you take a complete break from work (even just a few days or a week) before you do anything else. Try to completely relax if you can. Hopefully this will help you approach the situation with a clearer frame of mind.

Have you thought about teaching?  Do you find teaching rewarding?

Please, avoid cross-posting questions: https://workplace.stackexchange.com/q/111000

I'm voting to close this question as off-topic because it has been cross-posted and answered on another SE site.


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Software for submitting and testing programming assignments
Can anyone recommend an open source system for students to submit programming assignments? Ideally it would be something that would run on the web, do some level of testing on the server side, and provide feedback to the students based on testing.

This question appears to be off-topic because we don't do shopping questions here. This could be on-topic for [softwarerecs.se], if it was brought up to the standard required there (see their meta for details)

@EnergyNumbers: Perhaps the way it is phrased, it sounds like a shopping question, but the general idea of the question is relevant, I feel. Many academics need to deal with electronically submitted assignments. Some of these are software and software needs to be/can be run automatically.

@DaveClarke the general idea may be relevant, but we don't do list questions here. There is a Stack explicitly for this site of question - and that's [softwarerecs.se]. And this sort of question is explicitly off-topic here: not because of its general idea, but because of its nature as a list (aka shopping) question. Software recommendations are really difficult to ask for, which is why Software Recs has detailed instructions on its meta.

Since I'm interested in this topic as well, let me turn this into a more constructive direction: What would be needed to make this question on-topic? How about asking for practical experiences with automated assessment tools (specific tools or in general), or about specific features which turned out to be useful (or not so useful) in classes?

@EnergyNumbers There are several similar questions that have been accepted. I agree, though, that [softwarerecs.SE] would be appropriate, too.

I've never done this myself, but I think the following system could work using GitHub and Travis CI:

Create a repository for the homework where students can submit pull requests to.
Make scripts to run and test the solution and put them on the repo.
Students would then fork the repo, add their submission, and make a pull request.
Setup Travis CI to run the test scripts on the solutions. This will require some form of standardization for the commands to compile and run the solutions.

The nice thing about this system is that the pull request page on GitHub reports the status of the Travis CI run. You can then leave comments for the students and they can iterate until Travis gives them the green light.

That is a very neat idea (as long as you check they are not touching the tests).

@Davidmh that's the beauty of version control! Just check with a quick  “git diff".

or in the Github's files tab. Just thought it was worth mentioning they may try to trick you!

Can't one rewrite history in the forked clone so that the modifications to the tests don't show up with "git diff" nor in Github's files tab?

They could but that would cause a merge conflict that would show up on the pull request. Rewriting history changes the commit hashes and they would need a forced push for that.

The open-source web program CMS (Contest Management System) was created by people at my university (CS institute, university of Pisa). Screenshots here.
It has been used also in the international informatics Olympiad and several other international programming contests, so it is mature and well tested.
It is in use since a few years in the undergraduate course on Algorithms in our CS degree. It allows students to submit their source code online, where it is executed in a sandboxed environment and scored automatically on the basis of some test cases. It supports out of the box C, C++, Java, Python, Pascal, PHP, and other languages can be added (although I don't know how easy it is).

I can strongly recommend PASS (Programming Assignment Submission System), which was written by Mrs Marsupial to support my teaching on first and second year programming modules (Java and C++).  It formats the code into a .pdf document using LaTeX, but it also compiles and executes the program and adds the compiler messages and output to the .pdf file (and any output files that the program is supposed to produce).  The .pdf file includes an embedded .zip file containing the code in a standardised format in case further inspection/testing is required.  The requirements for each assessment are provided in an XML file for each module that specified expected files, input datafiles etc.  We have done some experimentation with automated testing, the simplest approach would be to include a Makefile and test harness in the metadata and PASS can add the output of the test harness.  However, for the modules I teach I am mostly interested in the structural side of the program design and whether the program is maintainable, so I tend just to have output specifications that show the program basically works and then mark by annotating the .pdf file on my ipad.
We have been using PASS for quite a while at my institution and it has saved a lot of unnecessary admin and hassle.  The major benefit is that there is a well-defined target environment (eliminating the "well it works on my computer" complaint) and the students get to see exactly the output of the program as I see it when it is marked.  Unfortunately students have to formally submit the .pdf file via BlackBoard at my institution, but another useful feature of PASS is that it provides a reliable independent time-stamp that can be used to determine whether an academic advantage has been gained by a late/failed BlackBoard submission.

Github classroom provides a free place to make and submit assignments and you can set up autograding.  One thing is that in github with github actions you can also build tests right into the push process.  However, I have seen some people on the forums for teachers say that they run out of free processing time during busy parts of the semester.

+1 for GitHub classroom. I've used it extensively for database, Java, and C++ classes. My class sizes are relatively small, so I haven't run into the processing time issue much and, when I did, I decided the extra expense was worth it (again, for my class size it was maybe $10).