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How to avoid disrupting the narrative in a scientific paper when you have done too much work
I have been working on a project for almost a year now. This project involves the implementation of a computational method to calculate material properties and the application to different material systems. I have also done original modifications to the method during the course of the implementation.
At the moment I am in the process of writing down the details of the implementation and the results of my calculations. I have envisioned that the best way to break down the large amount of work that has been done is to write three papers. Chronologically: 1) one with the improved methodology with pertinent application results, 2) another one with the implementation details and 3) a final one focusing only on application of the code to a very interesting set of systems.
I think that writing papers 2) and 3) will become easier as I can simply refer the reader for details to 1) and 1) & 2), respectively, but I am having quite a bit of trouble finding the right narrative for the first paper, since I want to focus on the big picture of the theory and methodology but the little details of the implementation seem to constantly get in the way. This comes in the way of "we are trying to achieve this big objective A but in the actual implementation we did things a little different by changing B1, B2, B3, ...". This would distract the reader from the main point and becomes extremely disruptive from the point of view of the narrative flow. But somehow, it feels wrong to leave these details out since readers would otherwise assume we use the previous approach, or would simply not know how exactly we carried out the work.
I am wondering what are useful and effective strategies to write papers that can be read smoothly when there is a lot of fine detail involved that has not been previously published.

Not an answer to the question, but a general rule that seems relevant: Do not devote space in proportion to effort invested.

Is this for a journal or for a paper in a class or for a thesis or comprehensive project or what?  What level - bachelors, masters or doctorate?

@MikeP Does it matter?

Does it matter (to the reader) what you were initially trying to accomplish? Such information might be best presented as a footnote or a separate part "other uses" or "alternative approaches" (if at all), not in chronological order before the actual interesting results.

My field is biomedical so comments may or may not work for you. In our works, sometimes protocols did change along the way and occasionally I need to explain that in the paper. Hopefully these comments are general enough to be useful to you.
The primary goal is to think from the gain of the reader and maximize the gain:pain ratio. You want the ratio to be high: transferring the most to them with them going through the least amount of effort to understand your work. With that reason in mind, here are some suggestions:

Really, very few people reading scientific journals are interested in the step by step saga in how we reach there. I know it may come off harsh but what matters to the researchers during the development process can be drastically different from what matters to the readers. So, cast a critical look and weed out details that are not bringing any gain.
Minimize the "we wanted to do this, but then we ended up with that..." frequency. Try not to start every single sentence with this kind of structure because they sound trivial and never-ending. Instead, I'd suggest setting up a section called "original plan" (to hint that something was changed) and give it a good introduction. Then, you can have a section called "Modifications" to briefly but sufficiently explain major design changes.
One device I found very effective is a graphical schematic. You can consider a graph of the original scheme. Then in the Modification section, use the first graph as blueprint, slightly grey out the contents, and then insert modified components in 100% black. Consider indexing the changes on the graph, and then in the text you can simply explain them sequentially.

I think 1) bears emphasizing. If not accompanied by solid "this is why you should care that our original plan didn't work", you probably should just drop the "we wanted to do this" altogether. So unless it's the most obvious approach ("Reviewer: why didn't you just do X?"), or there's some new and interesting fact about the system which was learned from the failure, just omit details about the original plan altogether. Knowledgeable readers understand that the "story" presented by the paper wasn't necessarily the way things played out in reality.

Separating papers into a "here's a new method" methods development paper and "here's where we apply a new method" application paper is somewhat common. Neither paper may go to as good a journal as a combined paper would, but it's an excellent choice if the audience for the two sub-parts is different.
For example, the people who care about computational modeling and the fine details about computational modeling protocols are normally quite different than the people who care about specific applications to which the methodology can be put. Therefore, if you develop a new computational method for a particular application, it's often helpful to have one paper aimed at the computational modeling people, which goes into the nitty-gritty of the protocol but perhaps only demonstrates it with toy systems, which is sent to a computational modeling-focused journal, and then have a separate paper, which may gloss over the protocol details but focuses on the real-world application, which is sent to an applications-focused journal.
Key here, though, is that you're not really splitting up the paper arbitrarily because it's too long, you're splitting it up because the focus of each sub-paper is different.
In that sense, I don't think your proposed split is ideal. Paper 3 sounds decent as your application paper, but it sounds like Papers 1&2 might really be the same methods development paper, salami sliced for convenience. That's probably why you can't find a separate story for Paper 1 - it doesn't stand alone as a methods development paper.
That's not to say you can't split up your methods development paper, you just need to do it on a topics basis, rather than an overview/details basis. For example, can your methodology be split into solving two independent sub-problems, each of which can stand alone as its own method development paper? Or perhaps there's a problem which is a simpler general case (where you can present a simple solution), and then a more-specific instance of the general problem which permits optimization or where the general case doesn't work, which can be presented as a second paper.
Finally, there might not be a good place to split the methods paper or you may decide against it. In that case, Supplemental Information (or Supporting Material) can be your friend. Write up your methods paper (e.g. Paper 1), but put the distracting details (e.g. Paper 2) into Supplemental Information. That way you can refer to the details briefly in the text, but still have a paper that's a self-coherent unit, as you expand upon it in the SI.


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Duration of courses: hours to weeks and self-study time
I'm trying to apply for a Master's program and on the application form I have to list all subjects I have taken for my Bachelor's degree. For each one, they are asking for the duration in weeks and then Lectures (hrs./week), Tutorials (hrs./week) and Practical courses (hrs./week).
In the documents I have from my university, the duration is only given in hours and the number of weeks taken for a single subject can vary greatly. Some may have been in the form of a block within two weeks, some have been spread over 10 weeks.
Is there any common conversion from hours to weeks? I'm sure they are only interested in the total time spent on this subject, not in the number of weeks in which I actually had lectures on it.
Secondly, my current university lists lecture time and self-study time, which added together make up the total course time (workload). As far as I can see, this self-study time does not match any of the three categories given. Should I just leave it out / substract it?

Regarding your first question for a "common conversion":
In Germany, workload for a course is measured in "hours per week in a semester" (abbr. "SWS" for Semesterwochenstunden), which would be what you are looking for. For singular events without a weekly schedule or for events where you need to calculate from a fixed number of hours, you can use the average (14 weeks / semester) or the real (12w / summer semester, 16w / winter semester [in Germany]) number of weeks and if needed the "academic hour" (which officially lasts only 45 minutes here) to calculate back.
As an example: A short practical course in the winter semester goes over 4 days with a daily workload of 6 full hours (breaks etc. already substracted).
This corresponds to 6 * 4 / 0.75 = 32 academic hours. As the semester has 16 weeks, the 32 hours correspond to 2 "SWS" or hours/week.
Formula: full hours [/ 0.75 if needed] / #weeks = hours per week
Covering your second question:
If your current university includes "self-study" time in the total course time, I would also stick to that in calculating the final "hours/week" for the course. Although it might be confusing if some course include self-study in the total course time and others don't, you should not alter the official course time given by your university.

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What exactly does an "unstructured research problem" mean?
I have often read articles describing graduate education talk of "unstructured research problems". What exactly does an "unstructured research problem" mean?
Some context: All that I've read is in the context of computer science and electrical engineering. And I recently graduated with a undergraduate EE degree.

Example, please?

Well they don't mention the exact term I use but here are a few examples which refer to unstructured work: one, two. Others mention graduate school as being very unstructured; I think I understand that better.

An unstructured problem is one that does not have a direct solution already established: that is, it's not immediately obvious how one gets from the problem statement to a working solution, or even if there is a solution.
This is the standard for most doctoral-level research problems in STEM fields: if the problem is so well-defined that the strategy for solving it is immediately obvious, it is likely unsuitable for doctoral work, and a new (usually more challenging) problem should be selected.

A concise definition indeed, Dr. (+1); your answer differentiates between unstructured research problems and structured problems. May I know what might be a structured research problem? Could you provide some examples?

Thanks for the examples.  I think I understand what you are asking now.

I have often read articles describing graduate education talk of "unstructured research problems". What exactly does an "unstructured research problem" mean?

In much of one's undergraduate work, one is assigned problems where the person doing the assigning has at least one solution, and solution method, in mind.  The assigner has structured your work for you.  Also, the assigner has given you a due date!
But the thesis is the thing that will prepare you to be an independent researcher, finding problems of interest to others, solving them, and presenting the solution in a compelling way.
Although there are exceptions to this, for a PhD, no one is going to hand you your assignment and say, solve this, and hand it in to me in three months.  Your advisor might say, read this paper, tell me what you think; then you might say, the authors suggested applying their technique to such-and-so other problems, and I'm curious to see if that would give useful results; and the advisor says, a collaborator of mine actually tried that once, and didn't get anywhere, but I've been thinking about the experimental set-up he used, could you take a look at it and see if you can come up with a way to....  And then you're off and running.  Only you don't know whether the improvements that you spend three months designing and building are actually going to get you anywhere.

Having spent some time now doing some work of this kind I understand now what you meant! Thanks for your answer!

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Is it a good idea to put equations in a research proposal?
I am preparing a grant application for personal funding to carry out a 3-year project. The topic is in the field of computational condensed matter, and the work will focus on i) method development, ii) computational implementation, and iii) application of method/code to interesting systems.
I think it's easier to bring across some points by (light) use of equations, but I'm not sure if the reviewers will frown upon it. The committee members should be either experts in the particular subfield or at least fairly familiar with it (i.e., it's not a multidisciplinary committee).
This website for instance states that

[...] the best proposals contain no equations at all!

So, is it a good idea to include equations in a research proposal or should I strive to avoid them?

While I am not a physicist (I'm a mathematician, but this doesn't particularly make me any more partial to equations), the point behind the quote on that website is that you want your proposals to be easy to understand, and not make the reviewer wade through a sea of technicalities.  Since you're writing for experts, if equations make the proposal easier to read and understand, please use them.  Everything should be made as simple as possible...

I agree with you, but just to be more specific about my question, as you probably know, for every reviewer's opinion there's another reviewer that will disagree. Quoting from my last proposal report: "... could hardly be described as high risk/high gain" (reviewer #1); "... is clearly high risk/high gain" (reviewer #3). So while some reviewer will complain about the technicalities, some other will complain about lack of technicalities. My question aims at finding the "sweet spot" that would (partially) satisfy both types, and how equations play a role there.

@Miguel Your question as stated reads "should I include equations or not", not how should I include them or how many to include.  You'll never be able to satisfy all reviewers, nor do you have to.  Just write as clearly as you can, try to get feedback, and incorporate it.  Hopefully you'll improve over time.


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Reusing material from paper on website
I have been working extensively on a project for which I have written a couple of papers which still haven't been submitted for publication. I am also preparing a website where I want these materials to be freely available. I would like to avoid having to rewrite everything again for the website, so I was wondering what is the best solution to be able to reuse literal sentences from the papers (once they're published).
As far as I know, Open Access solutions sometimes allow the author to retain copyright, but I'm not sure if always. What kind of publishing licenses would allow me to copy-paste literal material from my paper onto my website?
Overall, is this a good idea or should I strive to rephrase content even if not legally bound to do so?

It likely depends on the journals to which you are looking to submit your papers. Different journals have different copyright options, some allow you to publish a "draft" (i.e., identical to the final paper), as long as your don't post the actual article .pdf, and you provide a link to the published journals. Others might have an embargo period, after which you are free to publish on your website.
SHERPA/RoMEO provides information on copyright policies for various journals:
http://www.sherpa.ac.uk/romeo/index.php
If you are at an institution, it might be worthwhile to talk  with a trusted librarian, as they will sometimes be able to assist you with negotiating copyright contracts with the journal editor, so that you are able to publish copies of the articles on your website. Authors will sometimes use publishing 'hacks', such as copyrighting or even publishing an article themselves before submitting to journals, so that the author owns the copyright instead of the journal.
Open access journals are another option, although some may be predatory or require a fee to publish your articles. For example, Elsevier charges up to $5,000 if you want to avoid an embargo period.
So,

Overall, is this a good idea or should I strive to rephrase content even if not legally bound to do so?

In my experience this is a relatively common practice, just be careful to follow the copyright restrictions negotiated between yourself and the journals. Rephrasing content is not always a good solution, as some fields consider it unethical to publish the same work in multiple forms/venues.
Elsevier Gold Open Access Price List: http://cdn.elsevier.com/promis_misc/j.custom97.pdf


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How often should an editor ask for reviews from the same referee?
There is a journal editor who keeps sending me review requests. He sends a new one shortly (a couple of weeks) after I return the previous one. I tend to accept because they align quite well with my expertise and I want to stay in good terms with this editor, who is a prominent figure in the field. I am a slow reviewer, but tend to give quite detailed and comprehensive reviews (compared with what I usually get for my own papers), and I guess the editor is happy with the quality of my reports, otherwise he wouldn't keep asking. However, I wouldn't mind if he asked less often. After all, this is only one journal and I also get review requests from other journals.
I have no experience as editor, and I am wondering if there are any best practices from that side. Is it common for an editor to keep "milking" that reliable reviewer? For those of you who have editorial duties, do you have any limit on how often to ask? Once a month, once every two months?
My intuition tells me there's a risk the reviewer gets tired of getting so many review requests from the same editor and the editor may end up losing that valuable resource.

Tell them you are happy to review every 6 months/1 year/2 years?

I am looking more for an answer about the editor's perspective.

I try not to ask for a review more often than once every 2 years. But YMMV.

Do you work in math or another field where it takes a long time to get reviews? In my field we get reviews in 1-2 months for the average paper. Once every two years is a lot less frequently than I was expecting. Thanks for this data point.

It's not math, although papers can be mathematical. But it is a matter of respect for the reviewer's time not to ask more.

https://academia.stackexchange.com/questions/29079/how-many-papers-should-i-be-reviewing-as-a-referee

Just tell the editor how many reviews you would like to do.

IMO, the bigger limit is how many papers you're publishing in their journal. If you've only published one paper in their journal, I'd stop at 3, 4 at the most, unless you really love the area.

From my experience as an editor, it is not unusual for referees to ask for "time off" from being assigned reviews and give bounds for the frequency of requests.  As Buffy suggested, some editorial systems allow referees to enter this information and the editor sees it before sending out review invitations.  I was glad to honor such requests from reviewers---I wanted them to feel satisfied & respected so that they would write more helpful reports in the future.
Similar to Fred Douglis, I tried not to ask anyone (other than editorial board members!) to review more than twice a year.  However, we aren't mind readers.  If your pattern is to submit a helpful report and then say yes to another request soon afterwards, then maybe you have the time, really enjoy reviewing, etc.  What editor wouldn't follow up on such enthusiasm?  My advice is that it's up to you to speak up about what you have time for, how often you're comfortable reviewing, etc.  I think there's very little risk of getting on the editor's bad side by setting up those kind of parameters.

I'm not an editor, so I don't have the first-hand perspective you're asking for. Anyway, according to Publon's Global State of Peer Review 2018 report, ~10% of reviewers are responsible for ~50% of peer reviews (Nature News summary, full report), so some reviewers probably do get "milked". The report also discusses if there's a rising "reviewer fatigue", where review invitation acceptance rates are going down. That might make an editor more likely to repeatedly invite their more reliable referees.
Since your profile mentions you have a physics background, I'll mention something I've heard from APS editors. They try (across the journal family) to limit review requests a bit. First, they try to avoid asking a reviewer review multiple manuscripts at the same time, but do make exceptions for e.g. resubmissions. Second, they have a stated aim to give reviewers a two-week break between submission of the last report and the next invitation to review.

I suspect Publon's data are very skewed, and I would not trust them.

@FedericoPoloni Fair enough, but I don't doubt the qualitative result that some review a lot more than others.

Even for reviewers I know well (and probably have worked with), I will try not to ask the same person to review journal submissions more often than every 4-6 months.  I certainly wouldn't say "good job on that last one, here's the next one for you!"
But it all comes down to how people respond.  If someone declines, I'm more likely to wait a long while before asking again, but if they agree whenever I ask, I can imagine that window narrowing.  Especially when it often takes asking 8-10 people just to get 3 reviewers.

An editor should and normally does keep a database of reviewers. It contains more than just their email addresses. There is no particular reason why it can't contain preferences for frequency as well as the other information. So, an editor can and should ask, and try (hard) to honor those requests. Then the frequency is determined individually and need not be the same for all.
It would be fairly easy to write an application that will move potential reviewers forward or backward in a queue so that the process is automated, more or less.
Another system is to provide a list of papers to a set of reviewers and let them bid on them. This is harder to automate since editor judgement is probably needed to match papers with reviewing skills, history, and preferences. But a fairly large subset of the needed reviews can be handled purely via reviewer requests. Some CS conferences use this method. Then, fewer specific requests need to be made.
You are getting a lot of requests because (a) you accept them and (b) you do a good job apparently. You will keep getting them unless you ask for a pause or a slower or faster request rate. Accepting one two weeks after completing the previous one feels like service above and beyond the call of duty to me, actually. If it is burdensome in any way, or interferes with your own work, speak up.

The last time I handled a journal which had a standard review deadline of ~28 days, I had a personal limit of once every two months. It's not a strict rule, and if e.g. a paper is revised within two months I will still invite the same reviewer. This limit is also not based on any statistics or data - it's simply something I intuited. It was also rather rare for me to actually run into the limit since we don't usually get that many papers in only that single reviewer's expertise.
If you are getting too many reviewer invitations, absolutely feel free to decline. Editors see so many declined invitations that they are probably not going to bat their eye at yet another declined invitation. Just say you don't have time (which is true as well). There's a good chance you can also indicate in the journal's editorial management system periods for which you aren't available.
You don't have to feel bad about declining - there are thousands upon thousands of researchers in the world, and there is always someone else who can review the paper. If you can suggest someone else, it's not even that inconvenient for the journal to invite them.

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What should you do if you don't hear anything back from editor after a whole year from first submission?
I have submitted a paper more than a year ago, but still I haven't heard anything back from the editor. As of today I have no idea whether my paper has been accepted/rejected or is in a review stage. Only thing I know is that it has been received, for a got a confirmation of this soon after the submission. Needless to say that I've tried several times to get in contact with the editor to find out about my paper's fate, but I got not a single reply to my status update requests. What should you do in a case like this? I was thinking of writing to the editor again to let him know that I'm withdrawing the paper from him and submitting to someone else? Is this a good idea? Are there other paths one might walk down to?

Happened to me during my postdoc. Produced one paper; got a one-paragraph rejection letter after 18 months in review; bye bye academic career.

This is very bad publishing practice. I understand that you don't want to reveal yourself by telling us which one it is, but I think this sort of behavior should be reported to colleagues. I would stay away from such a journal.

If the editor isn't responding, it's time to escalate. The journal's web page should give contact info for an editor-in-chief and/or a managing editor. Contact one or both of them and let them know that you would like an update on the status of your paper, but cannot get a response from the handling editor (include dates of submission, dates you sent emails, etc). They should    take care of the situation.

"They should take care of the situation." they should, but they don't always. Some journals are just awful and managed so poorly.

The only contact I had so far is indeed with the Editor-in-chief. The story goes like this: I submit the paper before Christmas; for some reasons I get no reply to that. I then rewrite after a few weeks into the new year (2013) and finally the Editor-in-chief tells me that he has received and filed to the appropriate branch said paper. After several months of absolute silence I decide to write to the Editor-in-chief to get an update, but I get no reply. I wrote him again after a couple of months, but with the same result. Meanwhile a year has passed.

So have you tried contacting the handling editor at all, or have you always gone straight to the editor-in-chief?

So far I've been trying to reach the Editor-in-chief of the appropriate section. Just to be clear, what do you mean by handling/managing editor? Is he/she the person in charge of the publisher company?

No, the person in charge of handling your paper specifically (e.g. finding a referee for it).  You should hopefully have been told who this is (when I submitted papers, I was asked to nominate an editor from the journal's editorial board, and my paper was always handled by the person I nominated).

Unfortunately I've only been told that my paper was filed under this particular review, with no mention to who would've been in charge of the paper itself. The only thing I could do is then to write to the general editorial board of the publisher company and let them know about this situation I'm in with the Editor-in-chief of this one review.

Can you get hold of the editor's phone number?  I've sometimes found it very effective to call someone when they haven't been replying to emails.  However, I've only done this with academics I knew personally.  But it still might be worth trying, before you take the fairly major step of withdrawing your paper after more than a year (the advantage of eventually having the paper accepted by the journal you currently have it submitted to is that the date of submission will be on the published paper, and of course this date will be much later if you submit it somewhere else now).

Thanks for the advice. Since I'm still fresh about this process, I don't really know how to address the editor. I mean, of course it is in my own interest to have the paper published, but maybe mentioning my intention of withdrawal to him wouldn't constitute a leverage of any kind in my favour? What would the best thing to say/write be in this case? Cheers.

"I submitted my paper on X date. It's been Y months now since I first submitted it and I have not heard back from the journal. Would you be able to let me know where in the process it is?" Depending on the discussion you might mention that if you don't get feedback in a certain amount of time that you might consider withdrawing it.

The content of my many emails to the Editor-in-chief has been so far along the lines of the above comment, except for the part where I should be mentioning my intention of withdrawing the paper. So perhaps my next email will definitely include a hint to my intentions of withdrawal then.

(It's an old question yes but would like to give another answer) I would seek to withdraw the paper from the journal with a letter to the editor stating the reasons so. I think there needs to be a time where you've 'waited enough'. For me 1 year is too much but for others, perhaps they have more patience and I think for you to be so patient with your to-and-fro to the journal speaks volumes about your character but it may not be so good for your manuscript.
P.S. What was the final outcome of this?

Eventually I got sick of all this publishing pressure nonsense and left academia for good. I know of another paper that my co-authors are still chasing after after 2 years from submission (afaik we don't know if it has been rejected of not). I leave this joy to them.

Oh my gosh. Thanks for the update and I hope you're happier in another field!

Thanks. I'm quite enjoy life at the minute, exploring and learning tons of new and useful things. I definitely don't miss the pressure of publishing and the anxiety caused by waiting to hear back from grant panels and alike.


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Is there an online directory listing upcoming scientific conferences?
I am looking at organizing a small conference next summer and I would like by all means to avoid concurrent dates with any major or highly-overlapping conference on the same or related topics. I thought that it would be really useful if there was an online directory where I can check a calendar of upcoming scientific conferences and workshops (maybe sorted by field) and plan mine on a week in which it does not coincide with an already planned event. That way I would not be "competing" for speakers and attendants against the organizer of a different event. I would prefer to avoid "manually" browsing the internet to find this information out, so a centralized online service would be perfect for my needs.
Does such an online resource exist? If the answer depends on the discipline, I am mostly interested in physics, chemistry and materials science conferences and workshops.

https://www.conference-service.com/conferences/index.html

The first resource that springs to mind is the COMS directory, which lists conferences in the scientific disciplines (physics, chemistry, maths, life sciences etc). I don't know how comprehensive the listings are, but I think most major conferences should be listed there. You can filter the search by subject area (down to subfield level, such as astronomy or condensed matter) and country.
More specific resources exist which only list conferences in a certain country or subfield, for example the IOP (UK physics only), APS (mostly US physics only) or Inspire-HEP (international, but mostly high energy physics only).
Another resource used in my field (cosmology) is the UK Cosmo mailing list, maintained by the University of Sussex. Organisers can mail conference and summer/ winter school details to the list, and it's not limited to UK meetings either. A similar mailing list for your field may exist, although the benefit of such a list is its narrow scope-- after all, people don't want their inboxes spammed with emails about conferences in other fields, so I would use one with caution. Another drawback is that not everyone may be on such a list in the first place.

This COMS directory looks quite interesting. They could improve the layout with a calendar view rather than the list they have, but it's a good place to start. The COMS software also looks interesting.

PaperCrowd is a new research conference directory that may help.
 - Researchers can search for conferences based on research interests, topics, keywords location. They can follow events of interest.
 - Organizers can add their events in a couple of minutes.
 - It's limited to academic research conferences to reduce clutter.
 - It's free.
Disclosure: PaperCrowd is Ex Ordo’s contribution to the research community. We’ve committed to keep it free. We’ll continue to develop and support the platform as a side project to offset the development costs. Making it light-touch to use and to support will minimise the on-going costs.  We need the research community to embrace and populate PaperCrowd with conference data to make it a really useful resource. Please spread the word.
Read more about PaperCrowd here.


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Listing an offered (but not taken up) position on CV
I was offered a lecturer (assistant professor) position which I decided for personal/professional reasons not to take up. I therefore remain currently a postdoc. I have seen people listing such offers on their CV, with the addendum "not taken up". I guess the rationale is to convey the message to future prospective employers that "someone already deemed me good enough for this kind of job".
I was wondering if while I am a postdoc it is a good idea to list said lecturer offer on my CV, and if so, whether I should drop it once I manage to secure a lecturer (or equivalent) position elsewhere.

I am personally not a fan of this, but I have no idea how common it is. A more reasonable circumstance is when there is some award offered, but the award must be declined due to a conflict. In this case, you are noting the award, which is an achievement in itself. Although being offered a lecturer position is also a sort of achievement, it seems different to me.

similar to https://academia.stackexchange.com/questions/91383/is-it-appropriate-to-include-declined-post-doc-offers-on-your-cv (where it was about a postdoc position. Frankly, depending on what else is on the CV it might look a lot like a puffed up addition to me (i.e., and might lead to a slightly red flag feeling - do I have to figure out who I know to call at that institution so find out whether this is real or exaggerated). (but perhaps I am running across more CV's where there are red flags (talks called plenary  that were not, invited talks that were actually someone elses invitation)

Listing the offer is not something I've seen on a CV, but I have seen CVs which list job talks in a section entitled "invited talks" (similar to what is discussed in this question and, specifically, this answer by user JeffE).

Personally, I wouldn't list jobs I hadn't taken up on my CV. Whilst it could give a prospective future employer confidence that you would be up to the job, I feel for me I would rather discuss this face to face in an interview where they can hear you out rather than let them make unnecessary and potentially false assumptions about you based on your CV alone.


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How to assess the impact of an academic paper in the industry
Assessing the impact of an academic paper on other academics can be done (with its pros and cons) using the number of citations the paper attracts. For more detailed information on how the paper influenced the citing work, one can read the citing paper, visit the authors' webpages and even email them. All of this is made possible by the fact that most (successful) academic works result in the public, searchable, dissemination of that work.
However, how can I assess the impact a paper has on industry? Industrial work, which results in products rather than papers, will usually not leave an easily identifiable trail connecting it to the previous work on which it builds up. But funding agencies put emphasis on reutilisation of academic results for industrial applications. Recently, we got a consulting job because a semiconductors company came by a paper I wrote a couple of years ago and decided to hire us to advise them on how to build their production process. In my next application for research funding I can use this contract to exemplify how my research is useful for industry. But what about all the other companies that are using our results and we don't know about? Is there a way to estimate this impact?

Start by making a list of all the industries that could use your paper...

This answer deals primarily with engineering products, I'm not sure if it applies to say, the software industry. Most research papers will present some results, but not industry-ready solutions. Most industries will not have full fledged research teams to scan scientific literature and work on translating it into products. So there is a gap that an interested industry needs you to bridge. Therefore, when an industry finds something interesting, they will contact you, as has already happened with you. The chances of many companies using your research without your knowledge is slim.
If you are interested in application-oriented research, you can increase the chances of this happening by attending certain conferences which have industry delegates, and proactively interacting with them. This can lead to collaborations, sponsored projects and a general understanding of their requirements. As you said, there is not much of a public paper trail, so human interaction is the only way.
To know what impact other people's research has on industry, you could search for papers sponsored by those particular industries (acknowledgement section for example).

Count of number of times your paper has been downloaded would be a valuable metric.

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


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Should I take undergraduate CS classes if all I do is applied software dev and data science?
I am a PhD student in social science who got interested in programming via data analysis in R and various utility tools in Python, SQL, Java (for web scraping, data querying, etc.).
I am considering whether I should take several undergrad CS classes at my university, including 1) Data Structure & Algorithm, 2) Software Development (both in Java), and 3) Database.
My concern is that I've seen various posters on this site claiming that what's taught in CS program has very little to do with the craft of programming itself. My main goal is to better my data analysis skills (for a data science career) and perhaps learn some machine learning and agent-based modeling. Given that goal, should I those classes? If not, what's the best way to learn programming the applied way?
(A common answer to "how to learn programming by yourself" is to do a project. However, engaging in a project without guidance and quick feedback is a very easy way to get sidetracked, especially since I'm in social science where programming skill is nothing but a tool and not valuable in and of itself. So, if your answer is "to do a project", please provide more details on how to get guidance, e.g. data analysis books)

what's taught in CS program has very little to do with the craft of programming itself — This is exactly correct. What is taught in CS programs is more closely related to the underlying science of programming.

@JeffE So how do I get better at programming for data analysis / machine learning?

In my opinion, the best way to become a better programmer (or a better whatever) is to both learn the science and practice the craft. Neither is sufficient on its own.

Everyone here -- starting with the OP -- is saying something I find strange: that programming skill is "nothing but a tool and not valuable in and of itself".  For whom is programming skill anything other than a tool?  (For whom is any skill anything other than a tool?) Why is developing a skill / acquiring a tool not "valuable in and of itself"?  Most of the point of a PhD is to develop skills for future use: this is more "valuable" than whatever product was created or project completed in the PhD work itself.

Millions of people have developed valuable programming skills: isn't the question rather whether the coursework is a good way of developing these skills?

@PeteL.Clark For people who aim to get a job developing software, programming skill is valuable in and of itself (or at least very close, since it's directly relevant to get a job, etc.) For me, a PhD student in social science, having awesome programming skill is only remotely relevant to producing dissertation, get tenure, etc. The application of programming in my case is not immediately obvious, so the connection between the means and the end is less clear than for a software developer.

@Anh: If you are doing programming in your social science work, then having awesome programming skills will improve your work.  If awesome programming skills are not standard in your area of social science, then that opens the door even wider for someone with these skills.  I also work in a field (pure mathematics) in which programming skills are neither taught nor traditionally valued...and the ones who have them can very often put them to excellent use.  One of my PhD students has superior programming skills: I honestly think these will help him get a good academic job.

Not to mention that you wrote "My main goal is to better my data analysis skills (for a data science career)"  The point is that two people can get PhDs in the same subject and go on to do different things afterwards.  If you were working in cultural anthropology, yes, it would be hard to see how to apply your programming skills directly to your profession.  But a data science career?  How can you do that without strong programming skills??

Everyone here...is saying... programming skill is "nothing but a tool and not valuable in and of itself". — I am certainly not saying that, @PeteL.Clark!

@JeffE: Again, you catch me using a universal quantifier rhetorically.  Not you. :)

If you are considering such classes, then go for it!
You are right that basics of computer science have little to do with direct application (its unlikely that you will need to invent a new sorting algorithm). But:

algorithmic thinking is invaluable,
getting it at level of computer science students (rather than "computer science for liberal arts majors") may be a challenge worth it,
getting contacts and interaction with CS students is invaluable (you may learn a lot about applied programming by immersion),
learning advances CS will pay off (regardless if you stay in academia or not).

Dedicating a year or whole studies to something is a commitment people sometimes regret. Taking a one or two courses someone is interested it is rarely regretted.
@EnergyNumbers warns you against lack of focus. But hey, you are not taking a random subject! It is a thing that will boost skills you need for the things you are doing.
Source: I did take one such class (while majoring in phys/math) and it was great (my only regret is I didn't take more). Now I am doing data science.
Disclaimer: I do like to side-track and I have little respect towards entrenching oneself in one, arbitrarily defined field.

Could you explain with some examples of how algorithmic thinking is "invaluable"? Also, not to be ad hominem, but could you tell me which discipline are you from so I can gauge the level of relevance between CS and yours vs mine?

@Anh As I said, physics and mathematics (and now I am moving to data analysis... often of social data). But my background is less relevant than quality and level of the course you are considering. Algorithmic thinking - each time you write code to solve a problem it is an algorithm. There are some nice ideas and insights from classical algorithms that may be good for programming in general (e.g. computational complexity, recursion, divide and conquer, dynamic programming, functional programming, encapsulation, dealing with edge cases, proving that the code solves the problem etc).

But hey, you are not taking "Arabic Language" — I think this is unnecessarily dismissive of the study of Arabic languages, especially with respect to social sciences (and data science!).

@JeffE It is in the context of the question. If the question started with "I am a PhD student in social science who got interested issues of Middle East..." then "Arabic Language" would be certainly on topic. (And I used it to argue with @EnergyNumbers.) In general, I think that it is not bad even if something is very off-topic as long as one is interested in it (to the point that I stared organizing an unconference series, http://offtopicarium.wikidot.com/ ;)). In any case, I am changing the problematic sentence to something less inflammatory.

I see a couple of places where CS classes would help towards data analysis in the social sciences.

thinking about issues like complexity can help when you're writing scripts to analyze large amounts of data
the "craft of programming" is also useful to learn, because you realize the risks of your code being wrong or faulty in some way (and techniques to guard against that), which in a social science study can simply lead you to draw completely wrong conclusions. Such skills are likely to be taught rather in  computer/software engineering than CS, if that distinction exists wherever you are.

One of my friends, a glaciologist, lost an enormous amount of time during his phd because of limited programming skills and the inability to verify his code, which led him to doubts about his experimental results. The programmer they hired just didn't understand the science and was useless...
Finally about machine learning and agent-based modeling, you won't learn much (if any) of that in undergrad courses. Those are usually graduate courses.
Perhaps an interesting avenue would be to collaborate with a computer scientist on a research project related to your studies, rather than embarking solo on a toy programming project.

Strongly seconding the second bullet point here --  understanding what your code actually shows is really hard. Actual math-research hard, which is what CS departments often do. Getting a good-enough-to-launch-a-rocket trust in your code is the engineering approach. Look for classes in testing and verification or validation.  N.b.; I know of a hotshot professor whose first big paper was demonstrating that famous modeled result "A -> B" was meaningless because all input to the program in question produced result B.

No, you shouldn't take undergraduate courses just because the subject interests you.
You are doing a PhD in Social Sciences. That means that all of your academic effort goes into your PhD. A PhD is a full-time occupation. Not in some weak, 35-hours-a-week sense of "full-time", but in the sense of consuming as much brain work as you are able to put in.
Programming and statistics are merely some of the means to an end for you: to provide you with the tools you need to complete your PhD. So focus. Focus on that. Every time you feel the urge, when feel distracted by machine learning or whatever, ask yourself: how does this directly contribute to me finishing my PhD? Catch yourself as soon as the siren call of "it will help me better understand the bigger picture of machine learning" or whatever starts weaseling its way into your mind. Those are nasty little tricks the mind plays on itself, that will drag you off your true course, and onto the rocks of endless distraction. And then you'll never finish your PhD. Just keep looking at the post-it-note you've attached to the side of your monitor that contains a terse expression of your PhD's research question. That is your beacon: aim at it relentlessly, and don't steer away from your true course.

Strongly disagree. The PhD is not the goal of a PhD program. The goal of a PhD program is to become a productive independent researcher. A PhD is not something you finish; it's merely the first step (or one of the first steps) of a research career. Focusing too narrowly on your thesis is just as dangerous as not focusing at all.

Most of the time, in practical programming you can get away knowing the craft without really needing the science, except for a few details (why is it faster to iterate the matrix by rows than by columns? why can I not run this in parallel?). But a stronger background on the science can help you expand your limits. For example, imagine you have a "weird" dataset, where the standard algorithms don't work, but maybe you can think of your own!
Also, you will be able to understand papers from other disciplines. I personally have "leeched" knowledge from papers in Sociology, Electrical Engineering, Medicine, Mathematics... all of them oriented at the processing of their data, that was by chance, somehow similar to mine.
Yet another reason for it is that it can boost your academic value. I don't think there are many people with a CS background in Social Sciences, and probably even less with a strong knowledge of the science behind your research, which means it can help you stick out and be a valuable asset for your lab.
If this was not enough, never underestimate the value of networking. At some point, you may hit a problem that is too hard for your programming skills. Having connections in CS, you can propose a collaboration.

+1 for the third paragraph, especially as a counterweight to the weird idea that doing a PhD in X means pointedly refraining from thinking about related subject Y.  In the contemporary market we want to hire people who stand out in some way.  Of course being simply the world's best at subject X is a good way to get hired in Dep't X: everyone is trying to do that.  But being as good at X as the other A-list candidates and also having skills in Y is a really good way to get some jobs in the current market.  (I don't think that most social scientists work in "labs"; no biggie.)

@PeteL.Clark regarding labs, I think it is common terminology for research groups in many fields (not all), regardless of the actual "labness". I vaguely remember a TED talk by a social scientist saying "we brought people to our lab".

In my field (pure mathematics), "lab" means only the room where you have to go if you don't have a computer in your office.  For that matter, mathematics departments are usually not organized into research groups in the way I think you mean either.  Anyway, "social sciences" is immensely broad: psychologists certainly have labs, but their labs probably have one-way mirrors.  Sometimes I get a little sensitive to the fact that people on this site tend to use scientific terminology as a synecdoche for academic terminology.  But it's not a big deal.


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What's the most efficient way to schedule a joint meeting with multiple faculties?
I have the find a time slot that all faculties can attend. As everyone is very busy, I want to do it in a most efficient way, i.e. minimizing back and forth emails as much as possible.
One trick I can think of is to ask each of them "What time you CANNOT attend?" instead of the usual "What time you can attend?" That way, I'm more likely to get all the free slots and able to schedule after only 1 round of emails.
Is there any further tips?
A big remaining obstacle is that the faculties still have to look at their calendar and write back to me all the time slots that are not free. I wonder if there's any technology (e.g. sharing a Google calendar?) that makes this process less time consuming for the faculties.

I'm voting to close this question as off-topic because it's not really about academia at all. [workplace.se] might take it.

What @EnergyNumbers writes. This is a boat programming question, where boat = "academia" and programming = "scheduling a meeting".

Why was this question closed?? It is about academia. Specifically how best to set up thesis/dissertation committee meetings. It's not like just setting up any old meeting. Anyone who has done a thesis or dissertation knows this.

From my prior experience scheduling numerous committee meetings (and other multi-person meetings), I've found that the "When Aren't You Available?" approach doesn't always work very well. Providing a proposed list of times can sometimes be more efficient. -- Particularly because it requires the least amount of effort on the part of the people you're asking to attend your meeting:

Pick a few times that you might propose for scheduling the meeting. Start with days/times that you would prefer, based on your own availability and general preferences (e.g. what time of the day you tend to be the most alert. :)
Send each person an e-mail saying something to the effect of:
"Please indicate which of the following times you might be available to meet. If none of those times work for you, please let me know if there are any other time(s) on those days that would fit your schedule."
Include a list of about 4 or 5 different times (or time ranges). This requires a lot less effort on their part to just pick from a list of times. People usually reply more quickly if you make it a simple task. For example, you could list some items in this form:
"Tuesday, September 22, from 11am to 12pm."  or
"Thursday, October 8, any time between 1pm and 4pm (please indicate any preferred time within that range)."

NOTE: ALWAYS, specify the Date AND the Day of the week! This can help to avoid any mix-ups resulting from people misreading their calendar. ( It happens to the best of us! :)

Wait to see what they say. Hopefully, there will be at least one day & time on that list when everyone is available. If one or two people are not available for any of the proposed times/days, you could contact them specifically and ask if/when they are available within your target range of  dates. Then, you can send everyone a new email, with a new list of proposed times.
If "Round 2" of the emails doesn't work, then it might be necessary to resort to that approach of asking, "When Aren't you available?"...

AFTER you figure out the best time for the meeting, don't forget to do the following:

Follow up As Soon As Possible with a final confirmation e-mail, stating the finalized date, day, and time. Politely ask them to reply to your e-mail with a confirmation that the specified time is still good for them. Also, you might want to include the Day/Date/Time in the Subject line as well.
For example:  "Confirming John Smith's committee meeting: Sept 22, 11am"
A few days before the day of the meeting, send them a "reminder" e-mail, politely requesting that they reply to confirm they got your message. (Let's face it, there's a good chance that someone in the group forgot to mark it on their calendar and/or doesn't even know what day it is Today. :)
Don't forget to Reserve the Room for your meeting well in advance! Also, double-check to confirm the room reservation a few days before your meeting. The last thing you want is to think everything is set, only to find out you don't have a freakin' room to hold your meeting!! (Faculty committees don't look favorably on that sort of thing)  :)

Best of Luck!!

Do you usually find that listing 4 or 5 slots work? The chance that 4 faculties with busy schedule are all available for 1 of those slots is quite small I worry.

I guess it depends on the faculty. If most of them are the type of person who is always running around from one meeting or another, then maybe the "when aren't you available" approach would be okay. Although I'd suggest rephrasing it as something more professional like, "Are there any scheduling conflicts that might prevent you from meeting during the week of [or range of dates]... "  (you could even do a Google search for suggested phrases for professional communications like that... ).  Then you could follow up with the 4 to 5 choices approach after that...

I guess my main concern with the "when aren't you available" approach is that it's a pretty open-ended question, if you phrase it exactly like that. People tend to prefer more precise questions (and they're more likely to respond more quickly to something that has an easier answer). On the one hand, people in academics are highly intellectual. On the other hand, many of them are easily annoyed and feel their time is worth more than anyone else's.... in case you haven't figured that out yet... ;-)

Use a polling tool, like Doodle. You create it, they fill in which times they are (not) available, and based on the results you choose a meeting time.

I was actually trying to avoid doodle. The reason is that a doodle form for such busy people needs to list many, many slots. Not only does it make filling it tedious, but people would also tend to not fill it accurately. This often means that no slot is found, and more emails involved.

Add in a threat in the email. Explain that if no time is found during regular business hours, the meeting will be scheduled for 7.30 am. That should encourage them to mark as many hours as possible as free...

@Johanna Then your meeting isn't important enough to your participants. This is likely a problem that cannot be easily fixed using a scheduling "trick". Also note that with "list all times you're unavailable" you are essentially moving the tedious task (iterating a long list of unavailabilities) to each participant rather than you creating a large Doodle poll.

@xLeitix, re: "you are essentially moving the tedious task (iterating a long list of unavailabilities) to each participant"... How does it benefit you to turn anything into a "tedious" task for the people you are asking to attend your meeting?  ... I agree with Heisenberg about avoiding something like Doodle. If for no other reason than that it requires your invitees to figure out something they might have never used before, which carries the possibility of them getting pretty annoyed with you.

@Johanna, re: "Add in a threat in the email. Explain that if no time is found during regular business hours, the meeting will be scheduled for 7.30 am..." -- I'm confused as to how you're coming to the conclusion that any sort of threat would be received well or make a good impression. (Or perhaps you were just joking about that?... I hope so).  I'm assuming that Heisenberg is asking these people to attend the meeting (i.e. that they're not required to just show up at whatever time they're told to be there.). Anything that will annoy them and/or require more of their time should be avoided.


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How exactly do graduate students collaborate on a research project?
My question can be elaborated as follows: When graduate students work together on a research project, are they usually expected to work on the same exact things, at the same exact time, or would it be more reasonable to have a division of labor and divide the work load?

It's hard to see how the collaboration arrangement won't be different with every collaboration.

It's really like any other collaboration. Presumably the (student) researchers are working together because they have a common interest in a problem and possibly have some complementary expertise that's useful for solving the problem. So they'll interact and as the situation merits it will divide up tasks (or work on some aspects together). There really isn't a single rule for this.

I can give you a rule: We should avoid people working on same exact things when the product is knowledge/information. It's very inefficient, because making duplicates is extremely easy and cheap once the product is finished.

@Trylks:  It's not (necessarily) inefficient if they work on the exact same things together.

@TaraB your concept for "exact same things" is not exact. ;)

@Trylks your statement doesn't make sense in my domain, for example, where two students might be collaborating on proving a theorem. They don't necessarily have complementary expertise and are in fact working on the exact same thing: sometimes it's just the give-and-take of an interaction that leads to a new result.

@Suresh it's a matter of definitions, granularity, atomicity and "exact same thing". Several developers may be working on the same software project, several of them may be using the exact same computer (two are recommended in extreme programming) or all of them may be typing at the same time (e.g. w/ screenhero) but I wouldn't say that they are doing the exact same thing. This relates with "The Mythical Man-Month" e.g. if one guy takes 1h to make a hole 1m diameter and 10m deep, and 10h for a hole 1m diameter and 10 meter deep, how long will take 10 men for a hole 1m diameter and 10m deep?

@Suresh in short, if there is give-and-take, they are not doing the exact same thing, because if they were doing the exact same thing then there would be nothing to give and nothing to take.

@Trylks:  If two people work on, say, proving a mathematical theorem together, by talking to each other and bouncing ideas around, it really can often go a lot quicker than either of them working on it alone, and I would find it a bit odd to say they are not working on the exact same thing.

@TaraB I was going to say the same thing but didn't want to go swirling down into a morass of pedant :)

The guy in this picture is not me, because if he was me, this would not be a picture. Call me odd, I would not say that's the exact same thing. In the same theorem, yes, are theorems the atomic level in maths? Are they the maximum granularity? Definitively not. Theorems are sustained by lemmas, propositions, definitions, and each one of them has a formulation, composed of several statements, composed of several symbols, and a proof, composed of several inference steps, that can traverse a path or another, etc.

In short, you can say it's odd to consider a different holistic level than "theorem", IMHO, it's wrong to consider "theorem" as the most basic holistic level in which maths (or work in maths) is divided or composed into and I would say that we are not speaking about maths here as much as we are speaking about information systems and how to model a domain (in this case formal sciences). I'd suggest to leave it here, you seem to be more focused on explaining me your experience (which I've understood from the start) rather than understanding my point. Further comments can only be futile this way.

@Suresh:  Probably a wise decision. =]


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Is citing data from a presentation not trustful?
There is this investment bank specialized in the mining sector. I had access to one of their presentations where they have data regarding the production and end use of some chemical elements. They do not cite the data.
Do you think that is good or bad, trustful or not, to cite these data in my PhD thesis?

Is that presentation publicly available? If not, then the question is how a PhD reviewer would validate that you have correctly reproduced or interpreted the data (or that said data even exists in the first place).

@xLeitix - Not sure I agree with that, from my experience a presentation does not typically contain enough information about the details of the study for the reviewer to either (1) fully assess the validity of the study or (2) replicate the research.

@eykanal I think you misunderstood. I think the presentation being publicly available is a necessary, but not a sufficient condition on it being a useful reference.

@xLeitix - Then we're in agreement.

The presentation can be accessed here: http://superiorprospects.com/data/general-information/Ta%20information.pdf or here http://www.slideshare.net/RareEarthsRareMetals/report-on-tantalum-niobium-by-jacob-securities-july-19-2011

In fact, the information I want to use is for introductory purposes. My main research is on the physical properties of niobium oxides. The data will help me explain why and how is niobium is a less expensive alternative to tantalum.

I don't understand the world trustful here. (Can a native speaker say if the title is correct?) Do you ask  if you should trust data from slides, or the slides should be cited or what?

@PiotrMigdal, a possible alternative word is 'trustworthy'.

@PiotrMigdal Maybe I misused the word... There is nothing wrong in citing what other people said. What I don't know is if in a PhD thesis in my area, citing a presentation of an investment bank may be seen as a doubtful source of information?

If I understood correctly, the quote is about the industrial applicability of your research, not its validity. I think you can relax a bit here.

If the source has been used, it generally must be cited, otherwise you assign yourself results or conclusions obtained by other researchers.
Providing the source is not a question for its reputability. If you think the source is not reputable enough, do not use it in your work. It is not very common but I have even seen "personal communication" as a type of the reference.

It depends on your research topic.
If you are conducting research on the marketing value of a chemical element, the trustfulness of a presentation without citation sources is unknown at best. All you know is that they did the presenation for purposes.
However, if you are conducting research on the investment bank marketing strategies, this presentation can be a research subject. The trustfulness of the presentation can be a research topic by itself. However, you will have the citation issue if the presentation is not publicly available as @xLeitix pointed out in the comment above.

In fact, the information I want to use is for introductory purposes. My main research is on the physical properties of niobium oxides. The data will help me explain why and how is niobium is a less expensive alternative to tantalum.


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Overlap between individual parts of BMBF funding proposals (Germany)?
I'm in the middle of writing a funding proposal for a BMBF programme (BMBF = the German federal ministry of education and research). I'm part of a consortium with a company, a local city government, our university, and another university.
We've already submitted a combined proposal, which got accepted, and are now supposed to submit additional individual proposals from each project partner.
This being Germany, we've been asked to submit forms upon forms within forms, and it seems to me that there is a huge amount of redundancy - the individual proposals don't seem to request any information that wasn't already part of the combined proposal.
Since this is my first time writing a proposal for this particular funding programme, I'm now wondering if I can just copy parts from the joint proposal into my individual one? I honestly don't quite understand why the individual proposals are requested at all, except for adding a bit of details in some parts... any insights welcome :-)

It is normal procedure that you have to submit again individual proposals as every project partner has a different financial account. The 2nd stage and individual proposals are also necessary as you have to show now exact quotes for materials, investments every project partner needs and why you need it. That's the bureaucratic side.
Also, be aware, you still DO NOT HAVE THE MONEY! It looks like you are in a two-stage process, if there are flaws in the 2nd stage, e.g. conflicting working plans and schedules in the individual proposals, you will not get the money! And the BMBF is asking for this to bypass a bad planning of the project by a single person as they often cannot judge if your approach is the best/cheapiest one. Proposals are often written by very few people also much more work for it finally, and they know this very well. You admitted you have done most of the writing.
BMBF projects are very often no pure research projects with a necessary industry partner and funded to have a possible positive outcome for the socienty when project goals are reached. This is not the case for fundamental research. And the scientific scrutinizing of your approach will be more important than for BMBF where they look also on economic measures/outcome.
That you got no new requests for the 2nd stage is a very good sign and the likelihood for funding is now very high, so be sure every project partner reads in the best case the individual proposal of the other ones, especially when there are common work points/collaboration.
But there should not be overlaps in the individual proposals and copy/paste is also not the best idea. I hope it is clear now why...

Thanks, this is very helpful! One more question, though: there are for example sections in both proposal templates such as "Description of the Project Partner" where you're supposed to describe your institution and your previous works. I honestly can't see why I shouldn't use the same text here?

P.S. just to clarify, the combined proposal wasn't just written by me, all project partners did indeed contribute and agree on a joint work plan etc. So I don't think we're in danger of submitting completely disjoint individual proposals.

Description you can copy as normally written by the project partner and send to coordinating/applying partner, but I would make it more detailed also, as in the 2nd stage you have more space (more recent projects, references...). You can also always call the BMBF advisors for this funding note, just be aware that these advisors are also scrutinizing your proposal, so think before what you want to ask and how. They shouldn't get the impression it's a one-man show.

Ask the Projektträger (preferrably via phone). They will help and tell you the rationale behind the approach (which I don't understand either).


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Tracking updates for an individual paper in arXiv
Albeit arXiv offers RSS news feeds for subject areas updates, it is also possible to track an individual paper for updates (such as if it was submitted and/or accepted to a journal)?

This is a pretty silly solution, but you can use a page tracking service to see when the page changes; this should detect both changes in the paper as well as in the journal its submitted to.
Edited as per Jaap Eldering's suggestions in the comments: you can use arXiv's OAI-PMH protocol to programmatically access version history! For example, if you want to look up arXiv #1206.0094, you can look up http://export.arxiv.org/oai2?verb=GetRecord&identifier=oai:arXiv.org:1206.0094&metadataPrefix=arXivRaw for its version history.
Furthermore, arXiv does have an Atom feed for individual articles: you can access it at http://export.arxiv.org/api/query?id_list=1206.0094 -- the link it includes is to the latest version of the article, so I presume it will change if the article is updated.

Dear Gaurav, that is a good idea. Unfortunately, arXiv blocks page tracking services by its robots.txt.

Instead of trying to track the normal webpage for the paper, you could track the page by one of the means listed on http://arxiv.org/help/bulk_data, e.g. the arXivRaw format.

@JaapEldering Those are excellent suggestions -- I've incorporated them into my answer! If you want to add them to your own answer, I'll delete them from mine.

No problem, you can have them ;-)

These updates get announced in the email digest, don't they? So, you could subscribe to the appropriate email digest and filter for messages that contain the URLs of the papers you're interested in.

There is an exception that might be important: after version 5 of a paper, any further updates are not announced in the email digest.  So if the authors are prolific with their updates, this may not help.

@NateEldredge - that's a good point and one I hadn't been aware of. Gaurav and JaapEldering's amended solution might be better, then.


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Is IEEE author's version the same as the accepted version which can be put on arXiv?
When a paper is accepted to be published in an IEEE journal, the publishing system sends by email a PDF file of the author's version
(for an example of what PDF file I'm referring to, see https://arxiv.org/ftp/arxiv/papers/1710/1710.01077.pdf).
(1) Is this PDF file the 'Accepted' version which can be uploaded to arXiv?
(2) Since in this case the authors do not have the source files of this PDF file, it is OK to bypass arXiv LaTeX detection?

How does IEEE define an “accepted” version?
  An accepted article is a version which has been revised by the author to incorporate review suggestions, and which has been accepted by IEEE for publication. If peer review by a journal or a conference requires no changes for publication, the accepted version is identical to the version initially submitted by the author.
  (Source)

From the link you posted, it is unclear if e.g. the copyright statements at the bottom were already present in the submitted version, but it is likely that the "author's version" is slightly different than the "accepted version". To be certain you are uploading the correct version, use the one you have compiled yourself. (That way, you also have the source files, solving question 2.)

Thanks! By the way, do you know the latex commands to generate the copyright statements in the PDF file? From what I've understood of IEEE copyright policy, these statements are necessary to submit to arXiv.

I think it's \IEEEoverridecommandlockouts\IEEEpubid{\makebox[\columnwidth]{ <copyright statement here> \hfill} \hspace{\columnsep}\makebox[\columnwidth]{ }} placed before \begin{document}


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Automatically checking retracted papers in bibliography
Is there a program or online service to automatically check if there is a retracted paper in the bibliography of a pdf file?

First of all, is there any program / service that is able to reliably check whether a given paper is retracted?

RetractionWatch launched a database of retracted papers: http://retractiondatabase.org/

I'm not sure a tool for this exists at the moment, but the open database of retracted papers from Retraction Watch is a great place to search for retracted papers--AFAIK it's the major database of retractions anywhere, and it's free to use.
If anyone is interested in developing tools for interfacing with the database, I bet they would be amenable (I am not affiliated with Retraction Watch, just appreciate the work they do).

If you import the bibliography into Zotero it will automatically do so for any document with a DOI or PMID: https://www.zotero.org/blog/retracted-item-notifications/
as an example:

As of today, nothing for free, and definitely nothing for PDF files. The best approach to developing such a program would be writing a front-end to the database of an organization such as Thomson Reuters or DBLP. However, you are unlikely to get free access to the interface of the database.


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Are professional body certificates any helpful in getting into academia (if I don't have any undergraduate education)?
Sometimes professional bodies issue diplomas and postgraduate diplomas which, for example in the UK, are recognized at a very high training level.
What I am not sure about is whether these, even though not issued by universities, can help enter university at academia or research level?

Usually, these topics are discussed on a case-by-case basis. For example, the professional institute can have some kind of agreement or understanding with some universities, but not with others. The best you can do is to choose a research program that you want to join, prepare your record (including professional diplomas) and ask the faculty that rules the program.
Some universities may accept you without conditions, but I guess the most common case will be that you will have to take some extra courses in their program and get the corresponding credit in order to fit your profile and knowledge to their exact expectation.

In addition to sansuiso's very good answer: In some countries there are legal pre-requisits which are required for a certain position. E.g. if you want to have "Dr." in Germany (~about PhD), you are required to have a masters degree (there are some rare exceptions, but this is the normal process). Therefore you can have as many certificates and be as skilled as you want, you won't get in without taking this step.
So check whether there are formal requiremnts in the country you are interested in.


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How much contribution justifies being a co-author of paper
I am part of a Computer Graphics lab where I got to help a small team already working on a paper, by assimilating/cleaning up some data sets which they required. I was also part of some discussions and shared my views whenever possible trying to help them in analysis phase. I have hardly any other contribution other wise.
Going forward, I am now being offered to be one of the co-authors of the paper. I kind of feel that I haven't really done enough and its almost reaching it's ending stage anyways, so not much chance in future as well.
Other team members are making a point that it won't be just on their part if this work takes up my time even when I don't get to be an author. I am in kind of a moral dilemma as I don't feel my contribution is enough.
Q1. Is just helping out a good enough reason to be a  co-author ?
Q2. How do I justify to myself if I have really contributed enough ? Or should I let the team decide if my work is sufficient ?
Q3. In general, are their any tangible points/guideline I can verify my contribution with ?

@CapeCode I think this is not a duplicate because it asks how a person should evaluate a borderline case of actual technical labor contribution, where the answers of the linked question address primarily strategic "gift authorship" and whether a lab head who merely funds work should be an author.

The standards for co-authorship vary greatly from field to field.  In some fields, you can be a co-author merely by supplying a useful reagent, where in others you need to be much more heavily involved with the actual work.  I don't know what the culture for computer graphics in particular is, but no matter how you draw the line, the general principle is the same everywhere:
The authors of a paper should be precisely the people who meaningfully contributed to the success of the work.
Some advocate for the tighter definition laid out in the Vancouver Protocol, which requires every author to be a significant writer of the paper as well.  That, however, has some serious problems, particularly in tending to unfairly exclude students from authorship.
Applying this to the case of your authorship, the answer is not immediately obvious from your question whether you should be an author or be named in an acknowledgements section, because it depends on the value of the work that you did and that's something that only you and your co-authors are in a position to just.  For example, if your work with the data set was just reformatting it from one format to another, then it's clearly not worth authorship.  If you did some real curation of the data set, e.g., evaluating the information to remove artifacts, and this made a big difference in obtaining the results, then authorship is certainly reasonable.  Note that the amount of work that you did is not actually a good measure: if you whipped up a curation script in a few hours and then let it run, it's no less valuable than spending months inefficiently curating by hand.
Finally, it's fine to err on the side of inclusiveness.  If your contributions are a borderline case, and the primary authors found your work valuable enough to merit a co-authorship, nobody will be hurt by including you in a minor author position in the author list.


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Carry your PhD project with you to post-doc and beyond
Say you develop your own research project during your PhD years and want to carry on the research project with you to post-doctoral and beyond, are there any restriction that you can or cannot carry on the project?

From a career perspective, it's a bad idea to carry your PhD project as your primary work further into your career. It's perfectly normal for people to finish up the publication of papers related to one phase in a later phase of their career, but it's not so good to keep working on basically the same project.
The reason for this is that you don't want to be "pigeonholed" as a researcher who only studies a narrow topic. In most fields, it's not conducive to a successful career, because it makes a researcher look as if uninterested in other research fields (even if that's not the case).
So even if the funding and willingness of the advisors is available to support such a path, it's not one you should follow (absent a very specific reason to do so).

I think switching to a different topic for you post-doc can be a good experience and career move. However, I've seen PhDs around me remain in the same field for their postdoc (e.g. studying sandbar behavior right before the coast), and successfully found professor positions in that field. The advantage of staying in the same field is that you have a good start, you are already familiar with the subject.

There's nothing wrong with staying in the same field. The issue is staying in the same project.

As soon as the article is published, any laboratory can plan experiments described in that article, continuing the research. I see no reason why the original author should not be allowed.
However this is often not as good idea as it may look like. Assuming the PhD student have worked seriously over PhD time, all "low hanging fruits" of the topic may be already picked up and published in journals. And if your parent laboratory continues that project as well, they put up the competition that may be very difficult to win.
The probable exception would be if the continuation of the topic requires to apply methods that are not well developed in the originating laboratory, and you are starting a post-doc in the new laboratory with your current project.

In general, this depends primarily on your supervisors (old and new) and/or funding. If they give you the green light you're good to go.
If you have been working with industry or parts of your research have been patented there may be legal issues if you intend to collaborate with other parties (both companies or universities).


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Competition with your advisor?
My PhD research interest is very aligned with my advisor. However, my concern is that if I want to stay in the academia, will my advisor become my competitor in the future?

i honestly dont know if you are really sincere in this question. Its like asking should i work for my manager because- i may get promoted in future and i may compete with him.

I think it's a sincere question.

I think the point is that the research interests are very close and that would make them competitors for funding, etc. This is unlikely be an issue in industry dealing with one's manager.

In that case your advisor could also be a future collaborator.

It is fairly natural have a similar profile as your advisor. After your PhD you need to develop your own, not just continue in the tracks you started. How close these new ideas end up to your current work is driven by many factors you cannot control. You can, however, start thinking about future directions.

One tidbit of information: some journals forbid advisors from reviewing work submitted by their former students.  So that helps.  (Or hurts, depending.)

Well, I don't know. Do you think you can catch up and be on par with your advisor in the number of publications? Do you think your advisor considers this is possible? Do you think that he doesn't have stronger competitors to worry about at this moment (possibly in other institutions, or countries or even areas wrt funding)? How feasible is in your opinion collaborating with your supervisor and competing with the aforementioned competitors?

I too believe it's a sincere question - I've seen it brought up several times in books and articles about choosing an advisor.

You might end up as competitors someday.  I've never felt like I was in competition with any of my former students or my own advisor, but some people are hyper-competitive, and others are unlucky enough to end up in awkward situations, so your mileage may vary.
Even though it could happen, you shouldn't waste time in graduate school worrying about hypothetical future competition.  There are more important things to think about, and you shouldn't let these worries interfere with learning as much as you can from your advisor.
Ultimately, becoming a successful researcher means developing your own research agenda.  Over time, you should drift away from your advisor as you explore your own interests.  (If you don't, it's a bad sign.)  In particular, as you become an established researcher your advisor will no longer play a central role in shaping your scholarly interests, and competition with your advisor will not be much more likely or worrisome than competition with other senior people in your field.

also note that there are many places where you are evaluated where your advisor is expressly forbidden from having a say in the matter. In certain areas of CS, advisors can never (in perpetuity) review their former students' papers. At the NSF, you can never review your advisee's (or advisor's) proposals. and so on...

I think most of the other answers here have missed an important point: following your PhD, you should not be staying in the same narrow subfield as your advisor. If you are directly competing for grants with your advisor, then you've done something very wrong.
The point of doctoral and postdoctoral training is to teach you to be an independent researcher. If you are doing only what your doctoral advisor did, then why do you have your own lab? You should be sufficiently distinct in your research profile that it's clear why "you are your own boss." (And if you can't come up with enough ideas to justify your own group, then you probably aren't ready to be an independent faculty member yet!)

There are really only two places academics "compete": funding and jobs. Since you are only a PhD student now, it is unlikely you will be applying for the same jobs as your advisor in the future since your advisor has such a big head start. By the time you close the gap, you will likely have made a name for yourself. As for funding, this is somewhat field dependent. For example in the US in an NIH funded field you might get a 3 year post doctoral NRSA and a 4 year k99/R00 after your PhD before you would likely be in direct competition with your advisor, and then you would have the "new investigator" benefit. Following this road you would be 12 years out before you are really in direct competition on "equal" footing. In other fields you might be competing for funding from the same pool of money earlier.
The benefit of close ties is that you can collaborate with your advisor after you finish the PhD.

only two places — No, this is simply incorrect. Especially in theoretical fields, several academics often compete/race to solve the same problem and publish first. Otherwise nobody would ever get scooped.

@JeffE fair enough. For some reason I think of that type of competition as being different since there is no obvious head-to-head confrontation. I will have a think about it.

Just for the sake of symmetry: you may also be competing for students...

It is a very nasty situation for the whole science system, when PhD student is already a potential competitor for the supervisor. This often leads to PhD studies lasting forever.
However scientific systems in most countries have more than enough measures to exclude such a competition. Most important, you frequently cannot progress from PhD student to professor inside the same institution, using the benefit that "you are already here, and everyone knows how good you are".
As a result, there is no reason for the supervisor to press down exactly you. Another competitor will come from the side anyway, and the supervisor will be with better chances after having good shared publications on your PhD project.
Competition does may happen if the professor assigns say some quite junior post doc to supervise a PhD student. Such post doc may then want to take over promising project for instance, be the first between authors, etc. However if this goes too far, it is usually possible to ask the actual professor to remove such a "supervisor" out of head.


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Any way to prevent my advisor from destroying my publication?
My advisor said he will edit and submit my manuscript for me but the version he submit to the journal was full of mistakes that was not original in the manuscript that I send to him. Is there anyway that I can also be a corresponding author so I can monitor what he send to the journal? Just to clarify, I'm the first author on this.

My advisor said he will edit and submit my manuscript for me — You should have refused.  It's unethical for anyone, advisor or otherwise, to submit a manuscript that lists you as a coauthor without your approval.  But by letting your advisor submit for you, you've given him that approval.

Also: Don't walk.  Run.

@JeffE it sounds like the OP didn't have willingly let the advisor submit for him. I may misinterpret, but it seems to me that the advisor just submitted and said so afterwards. I certainly agree with your sentiment: run, go, get to the chopper.

I counted three grammatical errors in your first sentence, a fourth one in the question that followed, and a fifth one in a comment below, not counting the lower-case letter starting a sentence. Yesterday, someone had to do quite a bit of work to spruce up one of your other questions. Are you sure that maybe your paper doesn't need a little proofreading and editing?

Sorry, my answer is a bit off-topic, but maybe still a good advice:
When I take a look at your recent postings, I would suggest you either

Talk to your advisor about all your concerns, in an undisturbed setting, maybe together with a third person both of you can trust.
Talk to his/her boss / dean of faculty, ... but be as objective as possible!
Look for an other advisor. When you opt for 3., you should reflect the whole situation and check, where you could have behaved differently in order to avoid similar situations in the future.
Quit academia.

The reason why I'm that off-topic is, under normal circumstances a paper submission by any co-author should be no problem and all authors have to agree on the submitted version of the paper. What you can do is retract the paper by contacting the editor of the journal. I would not do that if you opt for 1. (then your supervisor should contact the editor and tell he sent the wrong version of the paper and send a good one), but if you opt for 2.-3. you could do it.

When I look for other advisor, how should I explain all that's happening to me? Would they just think I'm bad-mouthing my advisor? should I let my advisor know if I look for other advisor? Thanks.

I suppose your advisor will not be surprised - tell him only you are considering it when you want to try option 1. The new advisor will be intersted in knowing why you quit. I'd suggest to tell there were severe problems which you prefer not to describe in detail because you don't want to talk badly about a former supervisor. If he insists, explain it very politely and reluctant. Explain, how you want to avoid such situations in the future.


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Manuscript in prep in PhD thesis
Can I use my manuscripts in prep in my PhD thesis and then publish them later?  I will need to defense my PhD first for an upcoming post doc appointment and plan to publish them later as a post doc.


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How do I choose a lab to rotate in?
Normally, graduate students at my university go through three rotations. I've done two and will need to choose a permanent advisor after this next one. So choosing a rotation is similar to choosing an advisor, yet the philosophy can be slightly different.
1) Funding: Does the PI have funding for at least one year? Having that planning time to find other sources of funding without having to TA is indispensable.
2) Choosing a permanent advisor: The purpose of a rotation is to find an advisor and lab I am comfortable working with, as this will lead to a happier and more productive few years of my life.
3) New skills: Doing rotations in multiple labs will give me perspective. I should be learning different skills from each rotation.
4) Research interests: I should find a lab with research interests that align to mine. I don't want to be stuck working in a field I don't enjoy for the next X years.
5) Prestige: An advisor with strong industry connections can leverage those connections to help me break into industry or finding funding for my startup. A recommendation from a professor famous in your field can be my ticket to a tenure-track position.
How should I reconcile these different points? I'm a bioinformatics grad, if that makes a difference.

I would focus on choosing an advisor and a project as your priorities. These will be the two most important decisions you make as a graduate student. The project you pick will be your preoccupation for the next five or so years, and your advisor will be one of the most important figures in your career. New skills and funding are secondary to these, and the issue of prestige almost shouldn't enter into your decision at all.
In particular, I would actually argue that it's not just choosing an advisor; it's choosing an advisor and a group. You will almost certainly be spending more time with your fellow group members than with your advisor. Therefore, you need to make sure that you can get along with both your advisor as well as your future colleagues. A miserable working environment is not worth the trouble, if another viable option is available.
Also, make sure that the project you want to work on interests you; it'll drive you to accomplish more, and you'll be better motivated to make it your own (which is what you need to do to succeed as a graduate student).

Thanks for your reply! I have been getting feedback from professors that they are unsure of their funding and don't want to take on a grad student (in the student's best interest, since they don't want their students to TA). Follow up question: Should I ignore this and rotate in the lab anyway in hopes that there might be funding, since there are interesting projects?

If they're already signaling concerns, that's a big, shiny red flag. You would do well not to do a rotation in such a group, if at all possible. The likelihood of things working out in such a case is poor.


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How to address a Dr. des.?
How do you address a Dr. des. (Doctor designatus), for example in e-mails?

Dr. John Doe
Dr. des. John Doe
John Doe
…?

possible duplicate of When can you call yourself doctor?

While the formal title is Dr. des., there are good reasons to simply use the form of address you would use to a “final” doctor: the title is only temporary, and the person will eventually have the title or Dr.; moreover, PhD candidates having freshly attained their goal will probably enjoy you using it.

For those who wonder what Dr. des. is, it's a temporary title, like US presidents are “president elect”:

Following a successful defence, the title of Doctor designatus (Dr. des.) may be used until the doctoral degree is gained.