How to search for institutions/universities that have good contributions on a certain physics research topic? For example, I am interested in the research related with "Quantum Hall Effects", and want to have a list of institutions/universities that have good contributions in this topic, with number of publications during the recent years. Any idea how? Is there any website provide such searching service? Google scholar, arXiv?

I tried APS search by searching "Quantum Hall Effects" in Abstract/Title. It shows all related papers. But now I just want to know the statistics of the institutional contributions.

Any idea how?

Statistics on institutions should be taken with 14,000,000 grains of salt: some institutions have changed name over time (including many recently, e.g. in France many institutions were forking twenty years ago and are now merging back), and affiliation rules vary widely between authors (you'll see below huge contributions from state-wide agencies like “Russian academy of science” or “CNRS”, they are not the same as universities or labs). But, you can do it with many bibliographic search tools.

Here's how to do with Web of Science:

Make a regular search (here I chose “title”, but you can do something more complicated)

On the results page, click on the “Analyze Results” link

Choose your field of interest (here, organizations)

Enjoy!


How include contributions to a manuscript of a paper in CV I'm an undergraduate submitting my Resume for a variety of internships and need advice about how (if?) I should include my contributions to a manuscript that my group intends to publish. This would be my first publication so I leave it off I feel that I would really be cutting myself short. I mention my position and the work I did, but I feel it won't carry nearly as much weight if I don't mention that it was in support of a paper.

As a student, it is entirely appropriate for you to list manuscripts "in progress." However, I would make sure that the manuscript is actually progressing before listing it on your CV.

If it's in preparation, you then list it as you would any other publication, except where it's published (journal, volume, page, year), you instead list where you plan to submit it (if you know that):

  Author List (including you). Title of manuscript. To be submitted to Journal X.

or, if you don't know where it's going to be submitted:

  Author List. Title of Manuscript. In preparation.


How to handle possibly subtly flirtatious emails from students? I got a series of emails from a student. At first, I thought she was being over-polite. But now things are making me very uncomfortable. For instance, at every email she thanks me for giving her good grades; it gave her motivation, encouragement etc. (this makes me very uncomfortable since it might imply I'm giving her preferential treatment) and I am the best TA she has ever seen. Her emails bear a tone which can be interpreted as either overly polite or very subtly flirtatious e.g. using emoticons, signing emails with only "Yours", "have a good night", "lovely day".

I am willing to give the student the benefit of doubt. English may not be her first language, so she may not know some phrases in emails are only appropriate with your closed ones. I want to tell her that she should avoid these phrases in formal emails not so directly. How can I convey this to the student?

You should keep your replies short, polite and professional. Do not respond to what you see as flirtatious. Try also to interpret what you see as flirtatious in a different light, as you say, it could be due to language issues. It would be bad if you started to respond in a manner that assumed something that was not intended.

In the end it is very important to not fuel any behaviour that you think is "suspect" but at the same time you cannot avoid responding altogether. Acknowledge praise briefly but do not return praise since that could appear as favouring a student before others. Turn the focus of a response quickly from any polite exchange to focus on the course material. You may also take opportunities to point out that information given is also given to others to at least subtly impress the fact that there is no "special treatment".

In short, act as if nothing special is going on, be brief to the point and professional in your response. Do not try to be anything other than yourself or treat any student differently from others. Keep records of your mail or other exchanges.


How to reference a technical document (like an RFC) in APA style? Like, this document, for instance:
https://tools.ietf.org/html/rfc791

It's an official Internet Engineering Taskforce document that defines things like network protocols, etc. Often times there's really no specific individual(s) credited as the author(s), and even the official title can seem ambiguous.

The information on the title page is:

INTERNET PROTOCOL
DARPA INTERNET PROGRAM
PROTOCOL SPECIFICATION
September 1981

prepared for
Defense Advanced Research Projects Agency
Information Processing Techniques
Office
1400 Wilson Boulevard
Arlington, Virginia 22209

by
Information Sciences Institute
University of Southern California
4676 Admiralty Way
Marina del Rey, California 90291

So what's the official title and who get's the credit; DARPA, IPTO, ISI, USC, or IETF? I was going to do something like below, but I thought I should check with you guys.

DARPA. (1981, September). Internet Protocol Specification. RFC 791. Retrieved from https://tools.ietf.org/html/rfc791

The APA Style blog walks you through citations with missing info. There is also how to cite a book with no author or editor. You seem to be using DARPA as the author, but from the title page, it seems mote likely that ISI/USC is the institutional author. If you dig deeper, the linked document lists Postel as the editor. In that case you just do a book without an author, but with an editor: https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_books.html

Edited Book, No Author
Duncan, G. J., & Brooks-Gunn, J. (Eds.). (1997). Consequences of growing up poor. New York, NY: Russell Sage Foundation.


Courses to take in Machine Learning for applying for PhD in ML? I just finished my BSc Hons. in Mathematics and CS from one of the leading research institutes in India (Not IITs). Now I'm going to continue my masters in CS. I like ML. But I haven't done any proper course. I wish to apply for PhD in this area. Can anybody tell me a detailed idea about the courses that I need to take so that I can apply for PhD in US or Europe?

Can anybody tell me a detailed idea about the courses that I need to take so that I can apply for PhD in US or Europe ?

PhD programmes in the US and Europe are significantly different. While a PhD in Europe expects you to have a fair idea of what you intend to research, the US universities allow you to take courses to learn - quite similar to what the IITs follow.

What courses to take largely depends on where you are studying, right? You cannot take a course if it is not offered.

An example Data Analytics course is at https://volgenau.gmu.edu/program/view/20521

Basically, you want to learn a couple of programming languages - Python (with scikit-learn) is good, take a course on statistics (and learn R programming). A core course in Machine Learning (teaching decision trees, neural networks, clustering etc.) and few courses on database systems. You need to know SQL and also NoSQL systems. Try MySQL and MongoDB, for example. These should generally give you the pre-requisites.

Also, just learning theory is not enough - one needs to also do practical work. For that, I would suggest learning Linux and having the ability to spin up VMs and setup a system with Hadoop etc. Cloudera provides a VM to get started, and so does MapR. Virtualbox is a good free virtualisation software.

You also need to decide what field of ML you want to go in further. This would depend on whay you want to learn ML - the reasons would be your own. Of teh sub-fields one could look at pattern recognition, audio recognition, predictive analytics, classification systems etc. You should then do your Masters work on that. IMHO, it would make sense to look at small, real world problems and try to solve them with ML to build a portfolio, then tackling something huge. If you are able to solve small but significant real-world issues, you would have a much better chance of landing the paid scholarship.

To get an idea about opportunities available in the UK, you can join the BIG-DATA@jiscmail.ac.uk mailing list. Social media researchers can join mailing lists of the  Association of Internet Researchers at http://aoir.org

Note: Before or after down-voting this answer please leave some rationale as to why you do not think this is appropriate advice.


Will my age affect my chances of finding a funded PhD position? I just finished my masters studies. My question is, will my age (29) affect my chances of getting a funded PhD position? I finished Bachelor of Engineering when I was 24 (took 6 years to graduate, normally my program was 5 years). I worked as a Lab course assistant (teaching the practical part of the course at a local university) for 2 years before I started my MSc a bit late due to financial reasons. I started working in industry a year ago (for same financial reasons) in a computer science field but irrelevant to the research area. I know that most of PhD scholarship positions officially require the applicant's age to be under 35, but do not they prefer someone who is 25 rather than 34?

I have two conference publications, one in IEEE, and about to send the third for journal publication. My field is computer engineering with a focus on the software side and I am trying to apply in Europe mainly.

The short answer is: no. Quite the contrary, many universities value the experience (preferably from industry) so it is beneficial. Also, your conference papers will be the most important factors in getting the PhD position and/or funding. I'd also emphasize that you should highlight the fact that you have a journal article (preferably A or A*) in progress.

I have not seen any such requirement which is restricting PhD or any academic degree to a specific age. In fact, doing so is illegal in most (read: all) European countries as it comes under age discrimination.

To narrow it down further, different funding bodies could impose their own restrictions per project, for instance DAAD's grant that you mentioned is "to promote and fund young artists" according to them, that is why it is restricted to a certain age group. A similar example could be feminist studies where it could be restricted to a single gender. Again, this has nothing to do with general conditions of admission.


What to do when the claims in a paper are proven to be wrong? What can be done to correct an error that might be hiding a certain author's sole purpose of publishing a paper, no matter the soundness of their method?

In a nutshell, the particular case that spawned this question can be summarized in a few sentences:

a paper presents a mathematical construction and proposes a numerical solution for the resulting nonlinear optimization problem
the problem has many local solutions that are not numerically distinguishable
it is impossible to ensure convergence to the real solution without actually starting near it
there are too many local solutions (an infinite set in some cases) to simply test the best sample
the authors claim unconditional convergence to the true solution, regardless the parameters
their results are consistent with their goal, but the mathematical formulation is in contradiction with the conclusions simply judging by the properties of the objective equations.
Hence, such results are, at best, a stroke of luck, if not part of a probably much different approach.

After spending almost one month trying to understand not one, but a series of three inter-linked articles on a scientific subject, I have mathematically proven that the central assumptions and claims in that series of papers were wrong and/or incomplete. As the papers were peer reviewed and even published in reputed journals or conferences, I feel there is a need of saving other people the trouble of wasting valuable time trying to reproduce a falsely advertised behaviour. What is the proper action to take in this situation (for example, writing to the editors of the journal)?

Write a paper explaining what the errors are and how they invalidate the results of the papers in question, then submit it to a journal with good visibility and get it published. Writing directly to the journal editors is appropriate only if you have good evidence that the errors in question are deliberate (e.g., the authors have fabricated data in order to obtain the results they wanted).


Can I still publish a paper in an IEEE transaction journal after uploading it to the arXiv? I read often that preprint servers such as arXiv are changing how we publish. However, no one in my area of medical imaging uses them and they are regarded in my lab with suspicion.

I currently have a finished manuscript that I am about to send to an IEEE transaction journal. I would like a preprint of this manuscript to be publicly available for several reasons. However, my supervisors are worried this might invalidate my ability to publish this manuscript. They don't want to take the risk that I do this wrong and can't publish.

So here is the simple question I never seem to see a simple answer to. Here is a finished manuscript, fully formatted for the journal I am going to submit it to, in PDF. Can I submit this  PDF as a pre-print to arXiv right now, or not? Will the publisher still consider publishing it? To play devil's advocate, why wouldn't IEEE say, this has already been published in the arXiv, it is no longer new work?

Edit: Here is what IEEE says: "Does IEEE consider an author posting her paper on preprint servers or on her company's web sites to be a form of prior publication, which may then disqualify the paper from further editorial consideration? No. IEEE policy allows an author to submit previously posted papers to IEEE publications for consideration as long as she is able to transfer copyright to IEEE, i.e., she had not transferred copyright to another party prior to submission."

Yes you can. If/when they accept the paper you need to perform the actions as described in:
From https://www.ieee.org/content/dam/ieee-org/ieee/web/org/pubs/author_version_faq.pdf

Can an author post his manuscript on a preprint server such as ArXiv?
Yes. The IEEE recognizes that many authors share their unpublished
manuscripts on public sites. Once manuscripts have been accepted for
publication by IEEE, an author is required to post an IEEE copyright
notice on his preprint. Upon publication, the author must replace the
preprint with either 1) the full citation to the IEEE work with
Digital Object Identifiers (DOI) or a link to the paper’s abstract in
IEEE Xplore, or 2) the accepted version only (not the IEEEpublished
version), including the IEEE copyright notice and full citation, with
a link to the final, published paper in IEEE Xplore

On the author center of IEEE it's restated here, that prior to publication one can share it on ArXiv
http://ieeeauthorcenter.ieee.org/publish-with-ieee/author-education-resources/guidelines-and-policies/policy-posting-your-article/

Prior to Submission to an IEEE Publication
Authors may post their article anywhere at any time, including on preprint servers such as arXiv.org.

Authors seem to get a lot of leeway from IEEE, including reuse of their previously submitted work in new works. Only thing is that your preprint must match the accepted version by IEEE. Not any rough draft or anything.


Asking for extension in submission of revision I submitted a paper to one of Elsevier journals. It got major revision and the submission time given to me was two months. Now the time is very near (10 days) and I think I cannot complete all changes to be incorporated. I asked for extension in due date of submission through editorial system using my login. Even after 4 days, there is no response. I am confused what should I do?
Is the deadline really hard and if I submit after a week or so, it will be rejected?

Counting the days, you asked for an extension on 24.12. Not everyone has to be around during the holidays so next time ask maybe a little sooner.

It may depend on the field and journal, but this summer I asked for an extension and I got it. Also considering how certain deadlines are handled around the academia (like 3 months taking the referee to review a revision of the paper just to say its OK), you are probably going to be just fine.

Edit: I just remembered that some time before Christmas I was sent a proof to answer the questions from Journal of Mathematical Physics with a deadline of 48 hours. I guess it took maybe even more than 3 days to send it back and nobody did complain.


If/where should I explain the reason of my low BSc GPA in a PhD application? I had serious health problems during my BSc studies and got a very poor GPA of 2.88 to be exact. After that, (I think) I performed much better in MSc, got a 3.75 GPA, and published two peer-review journal articles.
Now, I am looking for Ph.D. positions and worried about my low BSc GPA. In fact, I applied for two positions and got rejected straightaway. I assume that it is because of my low BSc GPA. Should I explain the reason for my low GPA? If yes, should I write it in my SOP, cover letter, personal statement, or in any other separate document?

You need a sentence or less to get this idea across. "While illness affected my undergraduate performance, I overcame the issues as my MS performance demonstrates."
There are a lot of places for such a sentence depending on the application materials requested. Even the SOP might "host" it, provided that you make the SOP more about the future and your goals than about the past. But the personal statement, if required, is probably better. But a separate document might be rejected.
If you are required to provide letters of recommendation, make sure that the writers emphasize your current skills and ability to succeed. They don't need to mention the problems, but their impact should lead to the assumption that poor performance is not expected in future.
But having been rejected twice means little in the abstract. Perhaps they are just the wrong places for you. A broad approach (several institutions with varied reputations) is a better way to assure success than any narrowly focused program.


Creating video recordings of R Studio and R console I am teaching a course of Methods in the Study of Animal Behaviour and, of course, a large part of the course is dedicated to Statistics and R scripting. COVID-19 emergency and lockdowns are pointing the finger to deliver our teaching using video recordings or online streaming of lessons. I've used various popular apps like Zoom, Skype, and Webex, to give lessons online. I have also been recording my screen using QuickTime and other software. Still, I've never been fully satisfied by the quality of the results when it came to recording the R studio interface. With the perspective of having a semester of full courses online, this worries me a lot. I was wondering whether someone more experienced than me would be happy to share good practices for teaching students using R and R studio via videos, possibly including video editing or the use of different programs for screen recording. Thanks in advance.

Stay Safe!

OBS Studio (https://obsproject.com/) worked well for me for another statistical analysis program. For the very basic editing afterwards (cut the time that the kids ran into the room out of the video, join videos together) the video editor that comes with Windows was enough for me.

Also see: I need help adapting my academic workflow to the COVID-19/coronavirus crisis – where do I start?


Normalizing other people's data on number of significant figures I am presenting a table in my paper which summarizes and compares data from other papers. I'd like the data to be presented uniformly, with the same number of significant figures for all data. However, some of the cited papers have more significant figures in their data than others.

Here's an example: instead of presenting the table below:

    | Smith, J.    | Doe, J.    | Anon, Y.       | My data    |
|---|--------------|------------|----------------|------------|
| X | 1.42+- 0.31  | 1.3 +- 0.1 | 1.314 +- 0.287 | 1.4 +- 0.2 |
| Y | 1.43 +- 0.10 | 1.4 +- 0.2 | 1.421 +- 0.234 | 1.5 +- 0.3 |

I'd like to normalize the number of significant figures to make it easier to compare them:

    | Smith, J.  | Doe, J.    | Anon, Y.   | My data    |
|---|------------|------------|------------|------------|
| X | 1.4 +- 0.3 | 1.3 +- 0.1 | 1.3 +- 0.3 | 1.4 +- 0.2 |
| Y | 1.4 +- 0.1 | 1.4 +- 0.2 | 1.4 +- 0.2 | 1.5 +- 0.3 |

Can I (or should I) remove significant figures from their data, for consistency purposes? If so, can I still use the expression reproduced from Smith, J., or should I use something as adapted from Smith, J.?

You are free to choose how many digits to keep, and whether to do it consistently - although you are advised to use as many as it makes sense.

Reporting 1.314 ± 0.287 clearly does not add any useful information to 1.31 ± 0.29 as there is no meaning in the last digit. As a referee I would have requested the original publication to ignore the last digit.

Keeping Doe, J as 1.3 ± 0.1 together with Anon, Y as 1.31 ± 0.29 in a review makes perfect sense, as it shows that Anon's data is actually more precise than Doe's.


Online repository for double blind submissions Some conferences in my area require double-blind submissions. I'm a junior faculty member and I would like to put a timestamp on my results by publishing them online, as there is a nonzero probability that someone else might come up with a similar result soon.

The problem is that none of the existing online repositories for publishing research papers that I'm aware of (arXiv, EEE) don't have an option for (temporarily) hiding the authors of an uploaded manuscript.

  Is there any repository that I'm not aware that would allow me to do this. Or is there any other way to get a public timestamp on my results while still being able to submit to double-blind venues?

I think the premise in double blind reviewing is that the reviewers will not try to discover the author's identity. Searching for it is implicitly (perhaps explicitly) discouraged. So an honorable double blind reviewer would not see a signed time stamped preprint on, say, arXiv. Some journals with a double blind policy clearly allow that.


Should numeration of a list of axioms be continued? I have a definition like the following:

Definition System of sides is ... conforming to axioms:

...
...
...

Definition Monotone system of sides is a system of sides conforming to additional axiom:

...

Definition Distributive system of sides is a system of sides conforming to additional axiom:

...

My question: Should I continue numbering of axioms as above, or should the additional axioms be numbered from one (not from four or five as above)?

Also note, that every distributive system of sides is a monotone system of sides.

I would recommend thinking about this presentation problem in the following way: if you were inclined to be verbose, it would be perfectly correct to say:

Definition Monotone system of sides is a system of sides conforming to the axioms:

...
...
...
...

As such, it is not so much that you wish to continue a list of axioms, as it is that you wish to take advantage of the similarity of the two lists of axioms to present this information in a way that is more streamlined and easier to understand.
As such, I would recommend making the elision explicit, as in:

Definition A monotone system of sides conforms to the same axioms 1-3 for a system of sides, plus an additional axiom:

...

Definition A distributive system of sides conforms to the same axioms 1-4 for a monotone system of sides, plus an additional axiom:

...

Notice also that I have extended the italics to the whole statement "X system of sides," rather than just the adjective, since you are not defining e.g., "monotone" but rather "monotone system of sides."


How to obtain the h-index or number of publications for a given academic as a function of time? Services like Google Scholar can provide you with the h-index of a given author at present. Is there a way or a service that provides a time series of the h-index (or the number of publications) as a function of time, or even provides a plot of this time series?

Scopus has an author search option. You can then examine a range of graphs that show academic output over time. Many universities have a subscription to Scopus.

As with any citation and  publication based metrics, the values are contingent on the citations and publications included in the underlying database. Scopus is fairly broad, but there is quite a lot of quality control. So the numbers will be quite a bit smaller than for example Google Scholar. Another option might be PublishOrPerish which is a downloadable free program which uses Google Scholar as the underlying data source.

Below I show an example for Albert Bandura (one of the most highly cited psychology researchers) using Scopus.

Citations per year

Documents by year

h-index by year

I could not see any easy way to just get the h-index by year. However, the h-index tab, does allow you to filter on different years. So you could manually, change the end year and repeatedly obtain the h-index to see how it went up each year.


Placing large figures at end of paper I have some elaborate drawings that need some space.  I think putting them "inline" would  break the flow of the (mathematics) paper.

Questions:

Where exactly should they go?  Just before the References? Do I have to make a section header for them, like Figures or Appendix?
Some of my figures will remain inline.  Do I number the figures in order of appearance, or in the order they are referenced?

Thanks!

The journal you are submitting to might have a style guide which will tell you what to do. If not, do what you, your advisor, or a different journal style guide suggests. Your paper may get administratively rejected if they do not like the formatting, but they will tell you what to fix and let you submit again. In my field, all figures go at the end, one figure per page, in the order referenced, after the references and appendices when submitting. The copy editor/publisher deals with laying out the manuscript once it is accepted.

Basically, it doesn't matter, just do something reasonable.


How can I seek permanent Personalised Assessment Arrangements, rather than reapplying each year? I'm severely disabled. Under Outcomes and length of arrangements:

If your condition is long-term and unchanging, the Personalised Assessment [henceforth PA] Arrangements Committee (PAAC) will approve arrangements for the duration of your programme, meaning you do not need to reapply each year.

Under 3) International student:

You can apply to sit your examination at an alternative venue [henceforth AV] if you are either:
a)      Taking a resit and/or replacement examination and you are a non-attending student. You can only apply to sit in your home country.
OR
b)      Taking a resit and/or replacement examination and you are applying to take the examination during the August exam period. You can only apply to sit in your home country.

I asked King's College London (KCL)'s Exam Services why AV can't be approved permanently (for the duration of my degree), like PA. But the Head regurgitated without explanation that this is possible only for PA, before harshly alleging that this matter was closed.
How can I challenge them? Can the Equality Act 2010 help?
Additional Argument, in addition to inability to live alone long-term.
Requiring me to reapply each year throws my life into uncertainty, thwarts me from planning how long to rent my apartment, and and forces me to rent for longer than needed. How?
Option 1: I lease until June, as I wouldn't know if AV'd be approved this year when I sign a lease. But if I learn that I'm approved for AV no earlier than Jan. or Feb., then lease payments from Mar.-Jun. would be wasted as I'd fly home.
Option 2: I lease until Mar. 2019. But the risk is lacking residence in London, if my AV is denied and I need to write exams in London in June.

A quick review of the link you've shown suggests that the two classes you've listed, personalized assessment and alternative venue, are open to two completely different groups:

Personalized assessment is for students with recognized learning or physical disabilities;
Alternative venue is for international students.

You're effectively trying to conflate the two types of accommodations, by requesting an alternative venue as a means of handling your disability. Based on the response of the chair of the committee, they are proceeding according to this distinction. For this to be successful, you need to be able to explain medically why you need to be at home for the exam period. Raising financial costs as a reason will not be a sufficient reason—by that rationale, you're no different from any other applicant wanting an alternative venue.


How to deal with unbalanced collaborations? As a postdoc in a theoretical STEM field, I have had many wonderful collaborations where all authors contribute non-trivially to the final product. However, there was also many "unbalanced" collaborations: where one author does 90% of the work for example. I am not talking about a situation in which a senior professor is automatically given authorship because of politics. For this question, let's say that we talk about collaborations between researchers of the same academic age/position (e.g. all postdocs).
These unbalanced collaborations are often not a problem per se but can be draining and time-consuming in the long run. To give an example, I have had collaborations where I was almost feeling like a PhD advisor to my collaborator, having to explain/redo everything. In contrast, the balanced collaborations that I experienced were always extremely enriching and efficient in comparison.
As a young and inexperienced researcher, my question is: what is the best approach to choose collaborators?
I see two extreme options:

Don't worry about it. Accept and nurture every collaboration as they come. If your collaborators are not useful, take the time to help them and make them grow, even at the expense of your own growth. At some point, you might also be the "useless" collaborator and you will be thankful to having been accepted in the collaboration.
Avoid unbalanced collaborations by seeking only collaborators you can benefit from. This is probably the best approach career-wise. However, I feel like it can lead to toxic behaviors which might do more harm than good in the long run.

Even though there is probably not a right answer to the question, this is something that has been bothering me lately, and I would benefit a lot from insights of more experienced researchers.
Many thanks!

In any collaboration, some degree of imbalance is inevitable. I've been on both sides of the matter, and the question I've always used to guide my collaboration decision is:
"Are all of the collaborating parties benefiting from the relationship?"
There are a lot of ways to evaluate this question, some very pragmatic and some very personal. Here are some factors one might consider: joy or lack thereof, how the relationship affects future job prospects, impact of the work, access to interesting future projects, opportunity cost for working on the project. It sounds from your description like your answer right now is no, so you should probably stop working with the person in question. Before doing so, ask yourself: "what would change this working relationship for me? Is there a way to make that change happen?" You might find some reasonable requests that encourage continuation, but more importantly this will help you wrap things up better. You do have an ethical obligation to bow out gracefully, though nothing is forcing you to and this may not be possible.


Open access journal with editor's summary I'm looking for open access journals, whose scientific articles come with an editor's summary (not written by one of the authors!).

The articles and summaries will be used as data for benchmarking automated summary methods, so ideally the raw text would be easily accessible (not pdf if possible).

Perfect example: PLoS Medicine

Thanks for helping me out!

Discrete Analysis has been launched a few months ago. It's an arXiv overlay journal, so you have access to the raw text by following the link to the arXiv and clicking on "Other formats".


How hard is it to get paid to do PhD in the US as an international student in engineering? Quick background about myself

I just want to give a quick introduction to my background but I think this could be relevant and beneficial to a lot of people. I am a Mechanical Engineering student studying at Imperial College London and working towards a GPA 4.0 equivalent, with a GPA 3.7-3.8 predicted/guaranteed. I will be graduating with an MEng degree in the summer of 2018. I also hold a Turkish passport (non-EU).

Into the question

I want to know how hard it is to get fully covered for tuition fees, accommodation and other expenses while getting paid a salary on top (I would still be consent with not getting paid as long as I do not pay anything other than my pocket money). From minimal research I came to find that this can be extremely unlikely, although, I also found that you have slightly more chances in some fields such as engineering since a lot of capital flow from the industry.

So from base line knowledge, I suspect my main options are to secure a scholarship that covers you fully, get the university to fund you or get a company to sponsor your research. I also know that it is usually a combination of the above.

I am a very driven person with a lot of passion for the field and I will be applying to universities such as Stanford and MIT. I am currently doing a research internship at Stanford and I also hold past research experience from Imperial College London. I will likely be getting published in a decent journal from my current research internship (at the age of 20). I just want to know what are the chances of getting paid let alone paying for tuition fees since I do not want to ask my parents for financial help. I would rather find a good job then to pay thousands of dollars for another 4-5 years, although doing a PhD has been my aspiration since very young.

Please do not hesitate to point to further resources as answer to the question and any help is appreciated.

In engineering, the primary source of support for international PhD students in the US is:

10.4% via teaching assistantships
71.7% via research assistantships or traineeships
11.5% via fellowships or grants
Small portion via other sources (e.g. self funded, employer funded).

Source: Survey of Earned Doctorates, TABLE 35. Doctorate recipients' primary source of financial support, by broad field of study, sex, citizenship status, ethnicity, and race: 2014

In STEM fields in the US, both US citizen and international PhD students are generally offered admission with funding, which will be provided via teaching assistantships, research assistantships, or some combination of the above. US STEM PhD offers that don't come with funding are generally not worth accepting. So it's not about specifically trying to get funding, it's about getting a real offer of admissions (which should come with funding).


Do US university professors consider papers published in IJERT Do US university professors consider papers published in International Journal of Engineering Research and Technology (IJERT)?

For an undergraduate student applying for research program, what do professors check? The journal in which the research is published or the quality of the research, because I personally have had seen many papers getting desk rejected not because they are not up to the mark considering quality, but the editors had more better papers to publish.

Sorry but ...

It’s on the blacklist of predatory journal so yes it is considered, but considered very badly.  I would see this as a black mark against anyone, and in fact recommend you take it out of your CV if you are co-author.

The suggestion that a paper cannot be published because the “editors had more better paper to publish” is in itself a statement about the quality of the submission.


Tables or Stadium seating for a conference? I'm organizing a conference and we have the option to set up the seating either around multiple tables ie a wedding arrangement or in the classroom style. There are benefits to either strategy but the way I see it, the tabular format allows people to put their stuff down and relax. On the other hand, the classroom style creates a much better learning environment for people to actually pay attention to a talk and creates a more cozy impression for the speaker.

I'm curious, what do people typically expect out of a conference and what is the ideal scenario for a one day conference? Does it make a difference if it's a bunch of students or a bunch of of professors?

Since it's a one-day conference, I'm assuming it's a little more relaxed than a powerhouse 3-day affair. But even then, I think the classroom format is a little more appropriate. Here's what happens with the table format:

either people will have to move chairs around to see the speaker, in which case you've effectively created a classroom format with much less desk space.
or people start talking to each other and ignoring the speaker. I've seen this happen in particular at business meetings, where arguably it's less important to listen closely, but the level of noise created is still annoying.

Either way, it's not serving its purpose. By all means use the table format for the coffee area or break spots. But I don't think it makes sense for the conference itself.


Can I publish parts of the Ph.D thesis as a paper in a journal? I recently finished my PhD thesis which will be published as a book soon.
Now I'm wondering if it's possible or allowed to submit parts to a journal?

Normally the process would be the other way round I think: Submitting papers and "gluing" them together for the thesis. I've read the guidelines of some journals which state "that the work described has not been published before" or that "Papers must present scientific results that are essentially new".

As a general rule, you cannot publish anything as original research that has already been published.  (You may be able to reprint it in other venues, but most research journals do not do this.)

Of course, the trick is what counts as "already published".  Nowadays, many publishers (including all mathematics publishers, for example) do not count informal distribution on the internet as prior publication.  It's common not to count extended abstracts from conference proceedings, although the journal may require some revisions or extensions.  Nobody counts submitting a dissertation as prior publication, even if the university makes it available for download or purchase, and technical reports are generally in the same category.

On the other hand, publication as a "real book" definitely counts as prior publication and would rule out journals.  Of course, this just brings up the question of what a "real book" is.  Basically, if it's published by a serious academic publisher, with some nontrivial selection and editorial advice, then that counts as publication.  On the other hand, if it's some random publisher printing copies of Ph.D. theses and selling them online, then you could make a strong case that it's not really published (and that this is not so different from ordering a dissertation copy).

However, I think you need to discuss this explicitly when submitting your paper.  For example, you could add a sentence to your submission letter along the lines of "This work is based on my thesis from University X, which is available for sale by Y but has not been traditionally published".  It's much better to deal with this upfront than to have someone later ask "Wait, why is someone selling copies of this work online?"


What percentage of STEM PhD applicants have peer-reviewed publications? I am simply looking for a rough estimate on how many PhD applicants typically apply having published a peer-reviewed paper (or papers).

Particularly, I am interested in Computer Science (or STEM fields in general).

Also, it would be interesting to know the same percentage for the admitted students.

These questions can likely only be answered by those on (or previously on) admissions committees, but all responses are welcomed!

I'm in a CS department at a mid-ranked school in the US, and have reviewed applications for Ph.D programs in CS for the last 6 years. I didn't compile detailed numbers, but my sense is that the number of candidates with "actual" publications (as opposed to fluff pubs) is of the order of 5%. I suspect this number is higher for the top-ranked school.


Resubmission of a manuscript to another journal which has been already published in Arxiv Suppose Dr. X has submitted his manuscript to a journal A and published a pre-print in Arxiv before receiving the review results. Unfortunately, journal A rejected it and he decides to submit it to a different journal B with only minor modifications.

The problem now is that the major of Dr. X's paper with the results and figures are left unmodified and will be reused in journal B as it is in the Arxiv version.

Will this be considered plagiarism?

No, it won't.

Two points:
1) The papers on the arXiv are preprints (in former times this meant "before printed publication"…) and as such, it is normal that they will be eventually published in a journal. Hence, many journals do not have a problem when the receive submission of paper that are already on the arXiv. So, uploading to the arXiv prior to submission to a journal is not plagiarism - it's just the same paper.

2) The first submission of the paper to journal A is not public. Submitted information is confidential for most journals (there are newer concepts of open review processes, but I assume that this was not the case here) and also journal A decided not to publish the paper. Hence, you are free to submit the paper to another journal and again, this is the same paper and no plagiarism.

Both points together imply that your in situation there is no plagiarism. You have one paper, available as a preprint, once rejected, once resubmitted. Totally normal… (I had the same paper available on two different preprint repositories and submitted two times to different journals.)


What is the difference between a "statistician", "applied statistician", and an academic applying advanced stats within their field? Within academia, I am wondering how statisticians use the titles/description of "statistician" versus "applied statistician."  Also, what is the difference between an "applied statistician" and an academic researcher whose work focuses on or involves the application of (relatively) advanced stats to questions in their field (I'll call this a Quantitative ________, where the blank can be any field).  What types of training and expertise do these different titles/terms imply?

Context: I am a PhD biologist and am applying for a lectureship in a stats department and am not sure how my definition of these terms/roles compares to those of actual statisticians.  To my peers I refer to myself a "quantitative ecologist." I am wondering if I can call myself an "applied statistician" or if that would be overreach given my training (I have taken a number of applied stats courses but am mostly a self-taught user of stats and programmer).

In my mind

Academic statistician: PhD in stats, math, or biostats and highly trained in fundamental mathematics and theory of stats.  Might work on theory, methods development, or directly on applied questions.  Key diagnostic: can convey statistical ideas entirely in matrix algebra.  EDIT:Publishes all their work in statistics journals.
Applied statistician: PhD in any academic field, whose research/work is focused on development and/or application of novel or highly advanced methods to applied problems.  Might or might not have high levels of formal training in math and stats but is fluent in mathematics.  Key diagnostics:   EDIT:Publishes most or all of their work in statistics journals.
Quantitative _______: Similar to applied statistician, but whose training in math might be less complete or formal, and/or might focus more on computational aspects of statistical application than mathematical aspects (Such as development of computational algorithms, statistical packages, best practices, etc).  Key diagnostics: is fluent in a programming language and/or teaches their department's grad-level applied stats class.EDIT:Publishes their work in journals within their field.

It is always interesting to me to see how different people outside of statistics perceive it. (I am a Ph.D. in statistics who had worked in academia, international organizations, and industry.)

In American academia (I am not qualified to speak for other countries), whenever you see somebody with the title that has "statistician" in it, it probably means they run SAS PROC POWER for somebody in medical school or in agriculture (grant land universities with outreach programs). This is a lowly job, for the most part, and you rarely if ever publish: more often than not, you are an acknowledgement on a paper, not a co-author. Biostatisticians though can often advance themselves to co-authors and co-PIs when a grant/project requires a statistician to be written in as a senior staff member of the team for quality control purposes.

I would have a somewhat difficult time imagining a stat department in a research school looking at somebody whose degree is not in statistics nor mathematics for a tenure-track position. The teaching positions can be filled with the department's own grad students or recent graduates who could not find an academic job. I heard that in some universities (California state system), hiring somebody to teach statistics courses runs into an odd difficulty: statistics is taught at math departments, but math departments are only allowed to hire graduates with a degree in mathematics.

So your hopes shouldn't be very high, and if you are hired into a stat department, you probably won't be given any courses above the first couple of undergraduate intro courses -- t-statistics, ANOVA, regression. A 3+3 load would also leave no time for any work back in biology for you.

Having said all that, I think it would be fair if you were to call yourself "an applied statistician" in your letter. I had called myself a "quantitative methodologist" when applying to quant psych jobs (to no avail).

Your classification is a bit silly, BTW. There are branches of statistics, Bayesian methods or rank methods for instance, that do not think in terms of matrix algebra at all. And, with few exceptions, econometricians or reliability engineers don't have any reasons to call themselves applied statisticians, as it does not give them any promotions or any additional funding. And even if they did, "proper" statisticians (those with PhDs in statistics) may not agree with this denomination (even though a good econometrician knows asymptotic theory of statistics way better than an average Ph.D. in statistics these days).


Masters application with bad 1st year transcript When I started the course I had a very negative attitude and did not participate or even bother trying to pass. I am not proud to say that I failed multiple subjects in my first year of degree.

In my second year I came to realize that this is the opportunity I have been given and actually started working really hard on pushing my CGPA up. I have successful done so bringing it up to 3.25 out of 4.0 from a low of 1.9. Once I started actually trying I found that I do have a passion and would love to pursue a master.

I am worried that I stand no chance because of that first year record. My question is do I stand a chance to get in a masters program and what do you think would help strengthen my application.

Schools do like to see that students have improved overtime so you do have that going for you. I would say the answer to your question depends on the type of program you want to get into. I can only speak from research university experience but I have seen people with not great GPAs (around 3.3) get into even PHD programs if they have enough research experience (i.e. posters, papers, lab manager experience, etc.)


Sharing preliminary draft versions of papers with people in the field I am a PhD student in mathematical economics and had an interesting idea last month. I modelled my idea and wrote it down. For the moment, it is a preliminary draft but I think my idea is pretty interesting.

I would like to discuss my idea with some people in the field (researchers, professors, other PhD students etc.) with showing them the model in order to take their advices but I am afraid if some people can pick my idea. (I have already heard about this kind of unethical attitude in academia from my friends.)

As it is not a working paper yet, if somebody pick the idea and make a working paper before than me, I think I could do nothing than accepting the situation.

How to deal with this kind of issues ? The best way is to keep this preliminary model for me until the time that I put it as a working paper ?

Per Pete L Clark's comment:

When you feel like you've developed the idea enough to present it to anyone else, show it to your advisor and see what they say. One of the main things that advisors can help you with is to tell you which other people to contact to get help and information.


Why is having multiple college majors seen as a bad thing when applying to graduate school? I have been told that triple (or more) majoring and/or taking numerous minors is seen as a bad quality when applying to graduate school. Can anybody explain we why they do not want academically oriented students that like to learn stuff?

It seems to be a common fallacy among undergraduate students that completing more majors and/or minors means that you have learned more in college.  I think this comes from the mistaken belief that completing the coursework required for a major in a subject means that you have mastered the subject.

In actuality, the coursework required for a major in a subject should be viewed as the minimum amount of coursework necessary to be able to claim any expertise in the subject.  If your goal is to study a subject at the graduate level, you typically want to take many additional undergraduate courses in the field beyond those required for a degree before you can reasonably begin graduate work.  Graduate schools look for this sort of deep experience in potential applicants, and tend to frown on those who have completed only the minimum requirements for a major.

So graduate schools don't see extra majors and minors as bad, exactly.  But if you spend time completing lots of extra majors and minors you probably won't have enough time to develop the expertise in your primary subject that you need for graduate school.  Instead of taking on a third major, you should plan to take roughly six extra courses in your primary field.  This might seem like it doesn't accomplish anything since it doesn't help you satisfy any official requirement, but it's exactly the sort of coursework that graduate schools are looking for.


Choosing between PhD offers - top supervisor at my current institution or good supervisor at new university I have offers for a funded PhD at equally prestigious universities in the same country. One is the university I did my undergrad (and doing my masters) in, with a "rising star" PhD supervisor that is very well known in my (small) subfield. The supervisor at the other (new) university is more senior, known in the field but not extremely popular.
In academic terms, it is clear that I should stay at my current university. However, I have heard many times the advice that it is good to change university for personal and academic development. From a personal point of view, I would feel excited to move university (and city). I am aiming at an academic career and so I feel that it would be too risky not to take the top supervisor at my current university (since this would give me stronger LORs and connections).
I have asked PhD students who know the advisors, and they all strongly encouraged me to take the one at my current university. They didn't do their undergrad there, however, so they didn't have the experience I would have of being 8 years in the same city and university...
My questions are:

Should I stay at my current university with the top supervisor?
If so, how to mitigate the negative effects of remaining in the same city and school?

Thanks a lot!

A PhD starts a career, it doesn't define it.
There are benefits to moving, there are benefits to staying. Benefits aren't limited to now. You can seek those benefits later.
Move at some point in your career, not necessarily now.


How to deal with insignificant work / wrong methodology in papers, when it is discussed correctly? I had a strange situation a few months ago:

I was reviewing a paper which was on an interesting problem and the authors used machine learning to solve this problem. Unfortunately, they seemed to have little experience with the methods so they obviously ran into the problem of overfitting without noticing this. Therefore, they drew wrong conclusions from their experiments. (Short summary for people not familiar with machine learning: They did not use the methods correctly and so their results were invalid).

I elaborated on the problem in my review and stated that the result cannot be generalized due to this problem and that the methods were used wrongly.

I was a bit surprised to receive a revision of the manuscript, where my remarks were just included in the discussion section: In fact they did not improve the experiment, but in the discussion they more or less stated that:

  it is possible that everything we wrote in here is invalid due to the problem of overfitting.

So in the end they had a paper with a good justification for the project, a maybe working method which was not applied correctly, and they interpreted the results correct – so all in all it was a well documented example for a failure, and it was formally correct.

Still, my recommendation was to refuse the paper, but I was considering if it might be helpful to others because they could learn from the mistakes. On the other hand, publishing such a paper would not be a reference for the authors since this is a severe flaw in the use of methods (and readers might skip the discussion and think the results are valid).

Did you have similar experiences before? And how did you react?

I haven't personally had similar experiences before, and probably am much more junior than you (only really have reviewed a relatively small number of papers at all still), but here's my thoughts (I am familiar with the specific case of Machine Learning though):

  I was a bit surprised to recieve a revision of the manuscript, where my remarks were just included in the discussion section: In fact they did not improve the experiment, but in the discussion they more or less stated "it is possible that everything we wrote in here is invalid due to the problem of overfitting".

Did they really only just add that in a discussion, or did they also adjust other places? Typically, a very short (e.g. one-sentence) summary of results is included in places like Abstract / Introduction / Conclusions, something like "our approach X performs well on problem Y". If there are any claims in any places like that, those would be unjustified in my opinion, and that would be a serious problem. There really shouldn't be any unjustified claims about performance anywhere in the paper.

  So in the end they had a paper with a good justification for the project, a maybe working method which was not applied correctly, and they interpreted the results correct - so all in all it was an well documented example for a failure, and it was formally correct.

If the intuition / ideas behind the proposed approach are sound / interesting and new, if it all sounds like it could work out and be interesting... I think there might be some value in publication. Of course this also depends on the venue, some have lower standards than others. I suppose I'd treat it as a paper that simply didn't have any empirical evaluation at all, try to decide whether or not you'd still accept it then?

  Still, my recommendation was to refuse the paper, but I was considering if it might be helpful to others because they could learn from the mistakes.

That's not what peer-reviewed papers are for. I do believe papers with "failures" in the sense of interesting ideas that, after a proper evaluation, turned out not to work should be valued more highly than they tend to be (only success stories that "beat state of the art" tend to be accepted). Such failures can provide useful insights when published, prevent others from coming up with the same ideas and wasting their time on them again. But accepting a paper with a methodological flaw so that others can use it as an example of what not to do in a paper? That doesn't seem valuable to me.


Ask thesis supervisor for permission to include his name as co-author of a journal paper and risk being denied? I did my Masters Thesis at a reputed organization, under a supervisor who is an expert in the field. The organization is notoriously protective about the data I acquired from there which I need in my calculations in my thesis. I would like to publish a paper with his name too, though he had very little to do with my actual work. But I am afraid that if I ask him, he will say no, owing to the over-protective nature of the organization (though it was I who took the readings and collected the values myself). I have the option to publish it without naming my supervisor or the organization. What would be the right approach here?

It sounds like you need to consider three distinct issues:

Trade secrets / copyright: Is the data truly yours to publish? I am not a lawyer, but depending on location, type of employment and contracts / NDAs you may have signed, the simple fact that you took the readings and acquired the data might not make you legal copyright holder. What you may need - given that the organization in question is notoriously protective or even over-protective of their data - is permission to publish by the head of that institution, even if you do not intend to publish the entire data set but merely results derived from it. Formulations like notoriously protective make it seem highly advisable to look through any formal papers you may have signed prior to starting there.
Academic integrity: Even if advisors seem to have very little to do with a project, they still may have provided guidance or maybe even just the opportunity to acquire data (as in, they did the work of putting together equipment necessary to acquire the data). In those cases, it is still necessary to put the supervisor in the author list.
Affiliation: Putting the organization in the affiliations is - as far as I understand the situation - necessary, because without their equipment / setup, you could not have collected the data. Think of the CERN or DESY: Sure it's you spending the night on site when you have beam time, but you'd still put that organization in the affiliations.

I may be mistaken, but your question sounds like you feel that academic integrity warrants putting your advisor as co-author, but if you do that, people might notice that you publish work based on data acquired at that institute. And that institute might object to you publishing that data, hence you'd rather avoid "waking sleeping dogs". If that's the case, i.e. if people at the institute could object to you publishing the data, you should ask before publishing.
If it turns out they'd rather not have you publish but have no legal way to keep you from publishing, there's no harm in asking and you can always publish anyways. But if they have legal means to keep you from publishing, just publishing anyways could be a very bad idea with potentially serious consequences for your reputation and your career (plus perhaps penalties to be paid, but again, I'm not a lawyer).
Email your supervisor, ask them how to proceed. It is very likely you're not the first who wishes to publish somthing based on research done there.


What are some steps an undergrad can take to get on a Ph.D. track? I hope this question isn't too broad.
I'm graduating next semester and I have been accepted into grad school, but I'm having difficulty finding a full map of what one should do to successfully go from where I am now, to a Ph.D., to (eventually) a tenure track--hopefully as a full-time student through the process. Obviously, this is over the course of 10+ years, but I want to do everything I possibly can, as early as I can.

Some things my advisors have told me for the near future:

Write a thesis as part of your Master's program
Find a professor to research with (goes with the first bullet)
Go to at least two different schools throughout the whole process

Undergraduate advisors didn't have very much advise past that. I'm looking for a broad roadmap of what my future would require/look like if I were to go down this path.

Many students who want to study for the PhD in the US apply directly at graduation from their undergraduate education. A MS isn't needed for most fields, but might include one along the way for little or no additional effort. But expect that such a doctoral program will include additional coursework in your field prior to starting research, and, perhaps, prior to choosing a research advisor.

The advice you were given is good, but the MS isn't actually needed (most fields). What you need is a solid record of accomplishment and good letters of recommendation that suggest you will be a success in graduate study.

The advice about going to more than one school is so that you have more opportunities to view a variety of approaches and a wider range of ideas than you are likely to get if you stay at the same institution throughout.

In some doctoral programs you can get a MS just by asking for it and paying a fee (some paperwork). In some you write a thesis of lesser scope than a doctoral dissertation, but possibly giving some practice with research and writing.

The path might be something like 6-8 years, possibly as long as 10.

You need a way to support yourself. The common way is to serve as a TA in your doctoral department. Research Assistants are open as well, but to fewer people in some fields.

But in the US, the best advice for right now is to apply to a few programs that interest you, including some that are more likely to take you than some others.


How should I write a statement of interest about how my research will fill gaps in the field, when I don't know enough about the field yet? I'm applying to do a master's at Canadian universities. My background is Earth & Environmental Sciences.

When writing a statement of interest, I am familiar with the various research in the field I want to go into, however, a professor told me I should talk about "gaps in the data and where my research could fill those gaps". While I believe that's a great suggestion, I don't feel like I know enough about different methodologies and their faults to write a good statement of interest. Should I keep it on the vaguer side and relate it to the professor/research group's common interests?

On a different note, my marks aren't the best, they're about the admission requirements/slightly above. I have a lot of work experience in the field, and TA'd quite a bit. I also did an undergraduate thesis that I'm quite proud of (and hope to publish soon). So I know that already sets me apart from my peers and may make up for my lower average.

Within that framework, should I discuss my marks and explain how I am a better researcher/writer than I am at taking exams, or do I leave out grades completely?

This statement of interest is both a persuasive and reflective piece. You need to sell yourself as best as possible. Below is one good way to do that.

  General advice: Sell yourself, but be honest. Be specific and concrete - a few detailed examples are better than lists of stuff you did (which goes in a resume if one is requested). Highlight experiences that suggest you are ready for graduate-level research. Relate your experiences and interests to the research going on in the department/program to which you are applying.

Paragraph 1 - State your intention (admission to M.S. program). Here is a good place to very quickly summarized your qualifications and to highlight your general research interests.

Paragraph 2 - Why the admissions/selection committee should give you a spot. This paragraph is the place to mention your experience, your TA activities, and your thesis. If you have a lot to say, group it by categories (like coursework, research, service/teaching) and make more than one paragraph. Do not worry so much about how your current experience is shaping you to contribute greatly to the field. Instead, focus on that thesis experience and what you learned from it. Do you think you are more prepared for graduate-level research than other undergrads might be because of this experience?

Paragraph 3 - This paragraph is an opportunity to be frank about anything that others may see as a limitation and/or weakness. Then you should describe how these limitations are not so serious or are counteracted by some additional experience/strength that makes you stand out. You can also describe how you are addressing these limitations so that they will go away. You should mention your grades in this section. Do not hide from them, but do not fixate on them either.

Paragraph 4 (optional) - If you have some unique story about how you because interested in a field, subfield, or research project. If your reason boils down to "it sounds neato", then incorporate this content into another paragraph. You can bring up your thesis again and discuss how you chose the topic and how the work has shaped your interests.

Last paragraph - Wrap-up. Restate your intent and summarize the key factors why they should accept you. This is a good place to write some specific wordage for the program you are applying to: "My undergraduate thesis was on the effects of X on Y, and I would like to continue study in subfield Z. Projects being undertaken by professors J, K, and L at Institution M are especially interesting to me because..." If you do this, you are showing that you did your homework about the program. You can also put this kind of stuff up front.


Language of application and CV for Junior Professorship in Germany I am in the process of applying for a Junior professorship in Germany (see also this earlier question here. If the job listing is in German, and does not explicitely state a language requirement, should the application be in German, or can it be in English? Further, does the same apply to the required "CV"?

Unless stated otherwise, you should apply in German.

Most undergrad courses are taught in German, and usually it is expected that your German is good enough to teach in German, and also good enough to write an application in German. You may check the departments website if they have any courses in English, and if you even find that they offer a degree where everything is taught in English you may consider asking the contact person (see the job ad).


What are the benefits and purpose of presenting a paper in an academic conference? If i have completed all the research work and compiled a research article then why should I present that paper in a conference and not submit it to a good journal for publication ?

The answer depends on the discipline.

In many disciplines you can do both. There are conferences where you can present work that has been published in a journal (or at another conference) or that shall be published in the future.

In other disciplines, conference publications are as "valuable" (or even more prestigious) than journal publications.

To know what is the case for your discipline, talk to your advisor.


How to toughen up against hostile students as a TA? I did not have a good experience when I TA'ed the first time. I faced a hostile student who refused to accept that he was wrong and didn't give me a good reason why he should deserve more marks. He showed a propensity for violence, shouted at me loudly, punched the table and gave me an extremely evil look. I was very afraid and shocked then.

I know I should have stopped the meeting and called the security. But I was at a loss then. I don't like that I was so easily frightened by a bad student. Though I haven't met such a student later, one never knows when the next time will be. Can anyone advise how to become tougher when facing such "evil" badly behaving students?

Your responsibilities as a TA do not include being verbally abused or physically threatened by irate students.  At the first indication of abusive behavior, immediately stop arguing or doing anything else that might further provoke him.  Instead, in as calm a voice as you can muster, inform the student that you understand his concern but that you don't have authority to grant his request but that the course instructor does and that you propose to set up a meeting for him with the instructor.  Immediately afterward, send email to the instructor explaining the problem and let the instructor deal with it.

If it's already gone past that point, and he's pounding the table, shouting and exhibiting threatening behavior, get away from him as quickly as possible.  Tell him you need to go to bathroom or whatever it takes to get away without being followed.  Do not return. Call campus security.


Convention regarding inclusion of both an abstract and introduction in a mathematical paper Good afternoon,

I am a high school junior in the process of preparing a real analysis paper for submission to a mathematics journal. I have written my proof and conducted an exhaustive literature review and now I would like to take the next step towards finishing my paper but I am unclear as to the convention with regards to including in my paper both an abstract and introduction or just an introduction.

I have read published papers such as this one by Erdos which include both an abstract and introduction but I have read many others such as this short proof of the prime number theorem which includes just an introduction. Then there are some like this one that have what appears to be an abstract without an explicit heading.

I have also read guides regarding how to write mathematical papers. There is this one which includes an introduction but no abstract. Then there are other guides like this one which make mention of both an abstract and an introduction.

My question is, is there a convention regarding the inclusion of an abstract in a math paper? If so, what is it? I understand that scientific papers traditionally employ both but I do not see a trend when it comes to math papers.

Thank you in advance.

The purpose of an abstract and an introduction are very different, so it may be useful to include either or both. An abstract is a summary of the whole paper, focusing on the main result. It might exist separately from the paper itself as, say, an online "teaser" to get people to read the paper. But an introduction is intended to give background on the problem to be addressed in the paper and to situate it within the literature. You would almost always include an introduction. You might also write the abstract, but not actually include it within the paper itself.


How does the tenure process work I am curious to know how the tenure granting process works in the US. How much weight is given to research, teaching, and service. I have heard that a lot depends on your relationship with your peers - department colleagues. If they feel you are a good fit, you can be granted tenure even though you have less than a stellar record.

Is there a minimum requirement for number of publications. Do publications before joining the institution count? I would appreciate your inputs.

The two most important considerations are publications and teaching: you have to have enough good publications, and you have to be not horrid at teaching. This assumes a typical teaching, research and service obligation -- research won't matter in a teaching-only position, and vice versa. Although teaching is usually considered to officially take up more of your time, research is usually given greater weight in a research institution, and teaching in teaching-oriented schools. Teaching tends to matter less than research in sciences, and teaching tends to be more important in humanities.

Officially, collegiality is in last place and is in some institutions forbidden as a criterion. However, likeability can influence people's subjective evaluations of other criteria. There is a growing trend to require departments to have explicit criteria, for instance stating that a book is required, or that the norm is 3 peer-reviewed publications per year. I understand it to be the normal case that all of your publications are part of the tenure package.

The external evaluations are, in my opinion, more important as a measure of your research productivity than the raw number of publications, so a huge number of crappy papers will do you no good, unless you can get a lot of crappy referees too.


Should I cite the author of software tool or script that I use? I'm writing a paper for my Ethical Hacking class. In 'hacking', you use a lot of tools written by other people, some of them are mainstream and/or made by big teams, others are less known and made by individuals or small teams.

If I'm using a relatively uncommon software tool for a particular task, a tool that my readers may not know of, would it be courteous/helpful to cite the individual or lead developer of said tool? Would it be acceptable that the reference is just the website, or should I find another article that talks about the tool?

(NB: We use Harvard referencing)

It is entirely appropriate to cite notable tools. How to cite, exactly, depends on the origin and nature of the tool.

If the software is closely tied to a scientific work, then you should cite both the website and the key associated paper. The website will typically instruct you on the preferred paper to cite.  If it is not tied to a paper, just cite the software.

Authorship of software typically falls into three cases:

A personal creation, by one or a few people: cite those people as authors,
e.g. Facade is authored by Michael Mateas and Andrew Stern.
An organization: cite the organization as author, e.g., Fortress is published by Sun Microsystems.
An informally organized open source community: leave author blank or put "X Development Community", as weight of authorship is unclear and the set of authors is constantly in flux.


Focusing on GRE, subject GRE, TOEFLS, IELTS before applying? Applying to the US:

I just finished my master's in mathematical finance. I want to apply for a PhD in math (but not in mathematical finance).

Can I start applying this year while studying and taking exams (GRE, subject GRE, IELTS, TOEFLS), or might my time be better spent on the latter?

I'm fluent in English, it's my only language, and I have a master's in math so I don't expect the GRE, IELTS or TOEFLS to be too difficult, but I may have to spend a lot of time studying for the Math GRE, which appears to be the equivalent of an LSAT/MCAT for master's or PhD and a bar exam/USMLE for bachelor's or master's.

What is the common practice in this matter? Do graduate school applicants first focus on studying and taking GRE, subject GRE, IELTS, TOEFLS, etc and then worry about applications after?

Suppose a graduate school applicant intends to study for one of those. On average how long does it take to study for, apply for, take one of those exams once (for the sake of example) and get the test (just one, for example) score?

For grad school, the GREs and TOEFL are treated more as thresholds. Once you cross the target score it may not have much of a bearing on your admission. For the general GRE, do some of the sample exams provided by ETS and see how far your score is from the prescribed targets. You can count on improving at about 5 points per week (so if you score 310 and your university needs 325, plan to study for three weeks). The TOEFL shouldn't be an issue for you based on your other Academia posts. The subject GRE requires at least 2 months of serious preparation. Again, try to see where you stand.

Try to do the exams at least a month before the application deadline, as that is how long it could take for the scores to reach their destination. If you are applying for a competitive program, you will need all your scores in place. Since it is only June, you have enough time to apply this year (to join next Fall).


Working in industry before pursuing a PhD in a different field I am an undergraduate student in mechanical engineering and would like to pursue my graduate studies in computational Physics in UK/US. The two subjects only align with respect to the 'computational' aspect, otherwise, they are pretty different. I have some relevant research in Physics.
But before applying for graduate schools, I'll have to work in the industry for a few years for financial reasons. My work in the industry will most likely be related to mechanical engineering,  such as structural analysis or aerospace engineering or with some luck, computational work.
How will working in the industry, say for 2-3 years in mechanical engineering, affect my graduate school application for Physics? Will it be a major disadvantage? If yes, is there anything I can do to counter that?

This answer may be valid only in the US.
The industry experience certainly won't be a plus, but as a minus it would probably be minimal. Can't predict precisely since every admissions committee is different and is composed of individuals.
But changing fields after a BS is pretty common here as is going back for a doctorate from the "working world".
But, it will be essential, I think, that  you maintain contact with your current professors over that span so that they don't forget you and the (obviously) wonderful things you did as a student. You will still want good letters of recommendation from academics to pursue a doctorate. I think the supervisor of any physics research would be especially valuable to keep as a contact.
You could also, perhaps, take a graduate course or two as a "non-matriculated" student, which is permitted in some places. Or even some undergraduate physics courses that might be missing from your background.
But generally, look to what you will need to present in an application and work to assure that such things will still be available and valid.
And, the shorter the delay, the better.


Letter of recommendation from online classes I am living overseas for work for the next two years and finished my masters 15 years ago.

Now I am taking graduate courses at Oregon State U online to prepare for applying to a Phd program.

I will have to get LORs from these professors but am unsure of the best strategy.

The country I am living in is not English speaking so I cannot take classes locally.

Assuming these are proper online courses, with proper work you turn in or at least exams, you should just email a couple of professors a month or 2 before you need the letters.  Explain the situation, briefly remind them who you are, and ask for recommendations.
They will be able to say in their letters what was covered in the course and evaluate your performance, so choose professors who you think will be most familiar with your work.

This shouldn't be that different from a letter a professor for a class you physically attended, but who you never had much personal interaction with.  Note you probably get at least one reference from your undergraduate days, at least assuming that was reasonably recent.


My masters project is very unclear, is it realistic to expect me to complete it successfully? I am doing a masters in electrical engineering which involves a project done in association with a company related to the university. I initially thought this would be a good thing as I expected the people at the company to already have the resources and knowledge to train me on the relevant things. But as I have come to realize, the project I was given was chosen out of a wish to have a certain product, without really knowing how feasible it would be.

There is existing literature by groups who had done similar things in the past, but all of them had access to different resources that I cannot use (fabrication processes with certain steps that do not seem available in what I have access to). In addition, their focus was more research-oriented, while in my case the intention is to make a commercial product eventually. The papers also tend to lack important information which, to be honest, even makes me doubt the amount of rigor that has been put into this kind of project before. Of course I have already done a literature review on what has been done, and I have some ideas about how to implement certain things, but basically everything I do is based on my guess for how things "ought" to work given what others have done and my understanding of the theory. I have no idea about how the fabrication will work out in practice.

In addition, before doing this project I had no prior experience with any of the chip fabrication details. In undergrad we had electronics courses, and I have sufficient understanding of the electronic circuit design, but the project also involves chemical aspects that I have never had to deal with before. It also requires knowledge of process details which are not usually needed for most applications, and are therefore not documented in what I have access to. I have tried to figure out a lot of this when doing the literature review, and I believe to have done a good job understanding relevant concepts, but my lack of any real experience prevents me from ever being confident that what I am proposing has any chance of working in real life. And none of the other persons I work with have ever done any similar work on that before, so I don't really have someone to guide me.

I regularly have meetings with my supervisors, and I have explained my concerns, but it seems like we keep having misunderstandings about what can be done. I usually try to explain rationally the problems that I see with particular ideas, but they tend to rely too much on "what the other group has done", and seem to just assume optimistically that certain things will work out. Of course relying on previous work is generally a good idea, but given the important differences in terms of available resources and goals, there is no way for me to simply replicate what others have done, and to me it currently looks somewhat far-fetched.

So basically, I am worried that I will eventually reach a dead end due to infeasibility or issues that I have overlooked, and that I will then get blamed for not completing the project. Perhaps I am wrong in expecting this, but I thought that there would already have been something organized or planned out before I joined the project, but it is really all from scratch and with little guidance, and relies on various things working out which I have no control over.

So am I right in expecting more concrete guidance, and should it be a problem if the project turns out to be infeasible or not work as expected?

Welcome to the wonderful world of research! You're describing what research is like: nobody really knows the answers, so nobody can really give you concrete guidance; nobody really knows what will work, so the only thing to say is "try it and see what happens". It might sound optimistic, and in some sense it's a good optimism, because no matter what happens you've discovered something new.

So relax and do your best. If you try something and it doesn't work, explain why it doesn't work to your supervisor. If you get stuck, also let your supervisor know. Your supervisor cannot really spell out what to do for you every time; it's quite possible he'll say "okay, we're stuck. What do you think we should do next?" and you can try thinking of something (don't worry if you fail; after some time he'll probably think of something himself).

Finally don't worry about what happens if the project turns out to be unfeasible or not work as expected. Nobody can guarantee beforehand if the project is going to work as expected. You're likely to be graded over your work, not your results. If your supervisor had given you a project that turned out to be more complicated than expected, he'll undoubtedly factor that into the grade, as well.


I want to opensource my code. Is it legal? Can I still publish? I am a PhD (stipend) student at a Max Planck Institute (for a biological science) here in Germany. I came here to write software, but ended up spending practically all my time doing wet-lab work. As a consequence, the programming I wanted to do had to be done in the evenings outside of the institute (although what constitutes 'PhD time' and 'programming time' is a bit of a blur, since I use my programs to solve PhD problems...)

Coming to the end of the PhD, I am now finally ready to "publish" the first of the three programs I have written during my time here in Germany, but there are three stakeholders all with competing interests in my software which make it difficult for me to know how to proceed...

The Max Planck - they will want to claim ownership of the software, because I wrote it while doing a PhD with them. Over the course of the PhD, no one from the Max Plank or the University have had any input whatsoever on the software, however, certainly between 10-20% of the code was developed 'on PhD time'.

The Journals - publishing is not a requirement, but it would be nice. It forms a stamp of approval (in some people's minds) and acts as free advertising at the very least. But for this to happen, I suppose I cannot "publish" my code already, meaning open source it and share it so people can bug-check it before publication?

The Users - Arguably the most important stakeholder for me, because I wrote this software for them. I want to make the code's licence as permissive as legally possible, probably under Creative Commons Zero to aid with this, but I feel this will make publishing impossible, and it may not even be allowed if I am not the owner of the copyright in the first place.

How should I proceed?

I'm the main developer of several open-source libraries, one published and one under review, so I can give you a pretty up-to-date overview on open-source in the machine learning community. This may differ for your field, but probably not much.

Whether or not your university will allow you to open-source and/or publish depends entirely on them. Based on my experience, open-sourcing can be sensitive depending on how old-fashioned your university/lab is. However, if they are fine with open-sourcing, they will certainly be OK with publishing too (after all, it's a free paper!). Only way to know is to ask your advisor.

The only move you have here is to ask your advisor. To my knowledge, at least some MPIs are very much in favor of open-source (e.g. Bernhard Schölkopf, head of MPI intelligent systems, is a co-author of an important open-source mission statement within machine learning).

Releasing software before publication

  I suppose I cannot "publish" my code already, meaning open source it and share it so people can bug-check it before publication?

Yes you can and in fact you should. Typically you need to show active user interest before you can publish your software formally (e.g. github stars, download, mentions on twitter, ...). See for instance JMLR MLOSS guidelines, which state "Evidence of an active user community should be demonstrated ...".

In any case, releasing software prior to submitting your paper is not a problem. Publications don't work like patents.

Publication venues

Lately, there is a lot of journal interest in software. To name a few:

JMLR MLOSS
Plos Computational Biology: Software
The R Journal
Journal of Statistical Software

A more complete list is available at http://www.software.ac.uk/resources/guides/which-journals-should-i-publish-my-software

Next to journals, you have a lot of conferences/workshops specifically about software. For many projects, you are actually better off publishing there with the added benefit of shorter review times and far less drama.

License

  I want to make the code's licence as  permissive as legally possible, probably under Creative Commons Zero to aid  with this ...

Creative Commons licenses aren't really suitable for software. Be aware that choosing an open-source license isn't entirely trivial, that is open-source licenses don't necessarily allow users to do whatever they want. Most commonly used permissive licenses include BSD, MIT, Apache and WTF licenses as opposed to the GPL. I do recommend informing yourself about the main differences of highly permissive licenses vis-a-vis GPL-style licenses. Some questions you should ask yourself include

Do you want your license to permit commercial use within closed-source projects for free? If not, slap a GPL on it and (optionally) dual license your software.
Do you want to permit non-GPL open-source software to build upon your work? If so, then make sure your license isn't GPL (this is because of the copyleft nature of the GPL).

In my opinion, the best license types for relatively small (but useful) research software projects are usually highly permissive (BSD, Apache, ...). Your university's technology transfer office may disagree, if you even have to go through them (if MPI claims IP ownership of the software you developed you have to pass through the TTO).


When reading papers, what's the most convenient way to check a citation without disrupting the reading process? Papers can include clickable-link formatting with in-text citations.  It's convenient to click a link to check the citation, however, it's disruptive to have to manually scroll back up to continue reading.

Is there an easier way to resume reading after checking a citation?  Alternatively, is there a less disruptive method for checking a citation?

If you're using Adobe Acrobat Reader (which I suspect you are), you can press alt + left to jump back to where you were before clicking the link. I find it amazingly useful.


Are journal papers published in journals more useful than arXiv papers when applying for a postdoc? I am a PhD student in applied probability looking for postdoc jobs after submitting my thesis. What is the value of arXiv papers (not yet published in a journal) compared to papers published in a journal while applying for postdoc? For example, if I have two journal papers and one arXiv paper, whereas someone else has three journal papers, will he gets any benefit over me in applying?

My arxiv paper got rejected from a very top-tier journal after almost two years of review. I am working on the reviewer's comments; then I will submit to a new journal.

ArXiv papers are preprints, not publications, so their value in the context of a job application is definitely lower than a paper that has been accepted for publication in a peer-reviewed journal. In your example, assuming all other things being equal, the answer is that yes, the job candidate with 3 journal publications would be at an advantage relative to you with your 2 journal publications and 1 arXiv preprint.

Of course, all other things are never equal, and papers differ enormously in their quality, scope, and significance, so that it’s quite possible that your one arXiv preprint might still end up overshadowing any of the three journal publications of the other candidate. So I would advise you not to get too caught up in these sorts of numerical calculations. The number of papers has some significance, but it’s very far from the only thing people care about.


Is it correct protocol to thank your committee members in a PhD dissertation? My question is: I would like to thank the committee members of my PhD dissertation explicitly thanking them for their time and effort and writing down their names Prof. Name1, Prof. Name2, etc...

This is of course before the formal defence after they found the dissertation worthy of being defended.

I am a bit concerned about whether it is correct, or impolite or not, or protocol wrong... if you know what I mean.

Any advice, opinion, suggestion that could help me?

P.S. The thesis is about mathematics, if it may help.

In the American style, at least, your acknowledgements are yours to do with what you like.  Other answers on this site include thanking the makers of Dr. Pepper or dieties and pets.  Thus, if you feel thankful to the members of your committee, you should feel free to thank them in your acknowledgements section.


how not to burn bridges between two academic jobs? Last year I have been submitting my CV to different faculties for a lecturing position. Of all the ones that I applied only one was more serious and wanted to keep in touch (institution A), the other one (institution B) was completely silence and only they reply with a general "we are interested, but we will tell you when there are open positions". Actually the following has happened:

Institution A has offered me a full time position with good salary, and the freedom to make research or even to work in other places part time.
Institution B contact me a few days before the offer of institution A, telling me that they would like me to work part time with them; when I told them that I would like to have a full time position they started to tell me "that procedure is going to take time". A couple of days passed and I got the offer from the job that I mentioned in the first point.
Now last week Institution B called me and they told me that they want not only to offer me a full time position, but also a position as a student coordinator of the career. The drawbacks are: the salary is 14% less than A, the hours are not; fixed that means that one should stay for overtime unpaid if the goals have not been reached, the research is keep to the minimum and I will not have the chance to work in another place part time. The only benefit is that I will be have a higher rank than in A. This same institution has already booked me for some partial hour lecturers in a couple of courses. I have been sincere with them when they called me and I told them that I have been offered another position (from institution A), so I need to wait to their answer. Even with that institution B has continue insisting me for getting the job with them.

So by factors of time, research and money; institution A seems a pretty good choice, but how I can reject politely the offer from B without being "marked" for not working there or not to burn bridges with them. Maybe somebody could say "why I do not want to burn bridges with them?, well it is just to have like a backup plan. Also institution B has the story that they are used to cut off their lecturers at any time they want, so what to do?

Thanks

What stood out to me is:

  This same institution has already booked me for some partial hour lecturers in a couple of courses.

Have you, in any time, either written or orally, communicated with institute B indicating that you will take up the position (even just the part time one)? If so, the polite thing would be to honor this commitment with Institute B, even just for one term (if you really want to work at Institute A, you can try to talk to them to see if they can arrange for the offer to be deferred for a year or a term).

If you have not indicated to institute B that you would take up the position, and they, without your knowledge, advertised you as a part-time lecturer for their courses, I would be very, very wary of joining their faculty. It is simply not the case that a department can strong-arm a potential hire into working there just by listing his or her name on a website.

Aside from the above: the job market is competitive. It is expected that you will be looking out for your best interest. As long as you have not made any formal commitment to either of the institutes, you are free to choose which one to affiliate yourself with in the future. If you really prefer the offer given by Institute A, you should just be honest and reply to Institute B and say that Institute A has given you a better offer and you regret that you will not be able to work for Institute B.

This really should not be a situation that counts as "burning bridges". From your description it sounds like just the normal competitive hiring process. If the administrators at Institute B are the type that will hold your declining of their offer against you in the future, I really doubt you will want to work for them anyway. (That just doesn't sound like a healthy work environment.)


Is a "Scientific Journal Impact Factor" of around 4 or 5 good for a philosophy journal? I am considering (for a variety of reasons) submitting an article to a philosophy journal, which happens to have a Scientific Journal Impact Factor of 4.699. This would be my first submission.

Is this considered to be a decent impact factor?
Or should I try a higher ranked journal?

Why not check the impact factor (or similar metrics) at a well-known, reputable source, and then compare it to the rest of the field? I've never heard about Scientific Journal Impact Factor (this one: http://www.sjifactor.inno-space.net/?), but it sounds suspicious and it doesn't list several well-known journals (at least in biology). The "original" impact factor comes from Thomson-Reuters, but in case you do not have access to it (you library should have it though), there are also free reputable services that offer similar metrics. SCImago journal rank or Journal metrics from Scopus comes to mind. Compare the journal you are thinking about with others in the field using one of these services. If the journal you are considering cannot be found there, I would consider this a red flag.

A journal ranking list in philosophy from SCimago can be found here. If you order that list by "Cites per document (2 years)" you will have a very close approximation to the Thomson-Reuters impact factor. From what I can see, an impact factor of >4 would be off the charts for a philosophy journal, which makes me even more sceptical about the metric that you have been looking at.

What's the name of the journal you are considering?