Does the duration of doctoral and postdoctoral phase *always* matter for a W1 position in Germany? Junior professorships in Germany are claimed to have, essentially, restrictions in terms of the speed of progress: https://de.wikipedia.org/wiki/Juniorprofessur says

  In principle the employment before the graduation and as postdoc altogether must (in some federal states: may) amount to not more than six, in the medicine not more than nine years, whereby the regulations differ among the federal states.

The above text (due to "in principle", whatever it might mean) is somewhat imprecise.

1) Which laws/regulations, if any, improse such a restriction in the 16 federal states? (@Roland pointed to http://de.wikipedia.org/wiki/Landeshochschulgesetz, but I failed to find the corresponding passages, for Bavaria, Bremen, Hessen, NRW, and Saxony-Anhalt. Moreover, some passages in the corresponding laws say "bleiben außer Betracht". E.g., if for Hamburg we see "Behinderungsbedingte Überschreitungen dieser Zeiträume bleiben außer Betracht.", does it mean that impaired applicants get an extension?)

2) In practice, have there been any junior professorships without restrictions concerning the duration of the prior academic career?

There are two different regulations applying here:

On the federal level, it is mandated that barring exceptional circumstances, a researcher is not supposed to exceed 12 years in total on temporary German university positions. Since a typical duration for a junior professorship is 6 years, that would mean no more than 6 years of temporary employment at German universities before that. This rule does not apply to certain external funding sources inside Germany, and not at all to positions held outside of Germany. Thus, this imposes a rather tight deadline on people intending to have their whole career in Germany, but does not matter much for those who are doing part of their career elsewhere.

In addition, each state has their own law describing who exactly is eligible to become a junior professor. For example, in Hamburg one may not have more than 3 years of postdoc experience. Since there are 16 states, listing all laws is not feasible for me. Also, do not count on this information being listed explicitly in job adverts.


Can we use students' class homework solution for research purpose? A colleague of mine would like to compare 25+ different Java implementations of the same homework. Is it OK (ethically/legally in the US) to share my students' class homework solutions with him for his research purposes?

You need to run this by your Institutional Review Board (IRB), as you would any time you use data from human subjects for research.

From what you describe, it has a good chance of qualifying for an IRB exemption under one of these categories (if identifying information is removed before giving the data to the researcher):

It is using existing data
the data comes from normal educational practices

but even then, the IRB needs to be the one to make that determination.


What can I do to make figures I've created generally available so others can use them? I have spend over a day making beautiful figures in Tikz
for project proposal seminar.

The figure are beautiful (the code is not).

These figures are to an extent reusable,
since they are about existing well known methods.
I didn't use the diagrams from the papers as I wanted to take advantage of the extra space I had on a slide, rather than the narrow 1 column images from papers. Also because I didn't want to try and cut any images out of the paper PDFs, since I would lose the vector scalability.

What can I do, to make these images generally available so that others can use them? (Benefit the community by saving others time)

Further more, when I publish my own work with figures, what should I do with the figures to make them available? Should I perhaps on my website with papers, include a .zip of the paper source and images?

You can

License them under a Creative Commons license that allows reuse. Put the figures with a notice regarding the license terms on your own website.
Contribute them to Wikimedia Commons. If appropriate, you might also add them to the Wikipedia articles for the methods they are about.
Post them on a site like Figshare which gives them a DOI, to make it easier for others to cite them when they use them.
If you're willing, also make the source code available under a permissive license (with whatever disclaimers you want to put about the code not being so beautiful...) so that others can create modified versions more easily. (You can put code on Figshare, too.)


What are the Do's and Don'ts of Computer Science PhD viva? Going into ones viva, there are obvious do's and don'ts. For example, do not try to show off, do be prepared to go into an in-depth discussion...

What, in your experience as either the PhD candidate or the examiner, would you consider the do's and don'ts to be for a candidate in a Computer Science PhD viva?

I am a PhD student in the UK.

Some obvious points that come to mind. In my view there is nothing special about a Computer Science Phd Viva that would differentiate it from another subject. There are minor differences between countries in the conduct of a viva so some of the answers are may be UK specific and some general to all Phd defence. For example, in some places the viva is in public and anyone can ask questions. In the UK it is usually held in private and often the research supervisor does not attend and you have a different internal examiner and also an independent chair who sometimes comes from another subject. The external examiner would usually be a national or international subject expert, but there is a degree of variability of panel makeup and regulations.
Yes; you can show off, as if your Phd is very good that would perhaps make you one of the countries or subjects experts in the topic of your Phd. It may be something you can be proud about. However, attempting to show off when the external examiner (another subject expert) thinks you are wrong may be a mistake. You have to read the social cues to ascertain which it is!
Certainly there be be some very in depth discussions. They want to know what you know.
Some do's and don'ts:
Do

Come prepared, Bring notepaper, pens. Take notes when appropriate. Bring a rough copy of the thesis you can write all over if they suggest a change, or use to show them where in the thesis is the answer to their question.
Sleep beforehand. Be rested and alert so you can clearly understand what you are being asked.
Remember the independent chair will be on your side. Their role is to ensure fair play. If you want to take a break, ask for one. Ask for refreshments if you need them.
Try to attend in person. Even if a remote viva is offered, like with Skype or Facetime this is never as satisfactory as talking across a table. If the viva goes badly you will regret saving a few pounds on that airfare.

Don't

Get into a philosophical fight with the external examiner, or imply the external is an ignorant nincompoop for not understanding your research. It will not go down well, as the external is the representatives of the subject experts. They are expected to know what they are talking about. They outrank you on every scale.
Expect your supervisor to come running to your aid, speak for you, or tell you the answers to hard questions. They are usually not invited anyway. If you got this far with your supervisors hand-holding you will now find yourself alone and on thin ice. This is you test that you make the grade alone.
Assume that critical questions mean that they don't like your work or think it not worthy. They just might be testing how fully you understand the implications of your work. Handling critical questions well is a sign of a good candidate.
Don't take it too personally, which is often very hard. Being critical of your writing does not mean that you or your conclusions are in some way lacking. It is their job to examine in detail and they are only doing their job.

Some general point, which I hope are somehow helpful. Best of luck.
(I answer as an experienced examiner and independent chair).


Is it inappropriate to apply to a long list of PhD programs? So I plan on applying for a PhD program pretty soon. I’ve done quite a lot of research into the people who do interesting things in my area and I’ve come up with a list of universities that I want to try to get into and people in those universities with whom I’d like to work. My problem is that the list is too long...

Is it wrong if I apply to too many places? I’m a good student and I can get pretty impressive recommendations, so there is a good chance I’ll be accepted in more that one place and I don’t know if I’ll look bad if I turn down offers after having talked to several professors and everything.

There is no such thing as "too many places", except if it is compromising the quality of your applications (or your other life activities). Start applying at your most wanted places, making sure to polish your application to your best effort, and keep going until you run out of time, energy, or programs you would actually want to attend.


Should I supply code along with my paper submission? I am submitting a paper to a machine learning/computer vision conference. Is it worthwhile to include some source code of my implementation so that the reviewers can test it themselves or gain a greater understanding of my idea? It will take time to clean up my code and make sure it is anonymised.

Is this a common practice? If so do reviewers pay attention to the code?

Is it worth the time to prepare anonymised and clean code?

The code will be included as a ZIP archive through the paper submission website. After the paper has been accepted I intend to release it with an open source license.

Should I supply code as supplemental material?

Yes, but it would be better if you published it in an open access fashion.

  Is this a common practice?

No.

  If so do reviewers pay attention to the code?

Depends on the reviewers.

  Is it worth the time to prepare anonymised and clean code?

That depends, don't do more than necessary.

Also read:

Ten Simple Rules for Reproducible Computational Research
Top Ten Reasons to Not Share Your Code
(and why you should anyway)
Open Source Software Publishing for University Researchers


How to calculate/decide impact factor of a new journal I have published my paper in a new journal in our field. The reason for submitting for this journal was the editorial board which consists of some of the top professors from best global universities (including University of Cambridge, University College London, Technical University of Munich, etc.).

Now I am applying for a job which requires me to list the impact factor for all my publications. Since the journal has only two issues yet there is no impact factor. How should I deal with this issue?

Deal with it honestly.  Say exactly what you said here.  "Since only two issues of the journal have been published, there is as yet no impact factor."


Appropriate ways to propose moving from a single to a joint appointment Consider an assistant professor who does fairly interdisciplinary work, regularly publishing in journals for more than one field, or where you can make a case that, depending on how you spin it, they could clearly be an X or a Y.

Currently, they have a single academic appointment in X, but are potentially interested in a joint appointment, perhaps to advise students, or to combat the perception that they're "really not a Y" within the field, or another reason.

What's the best way to raise this desire? What practical objections might be raised?

As Nate Eldredge points out in the comments, there are two types of joint appointments:

With a courtesy appointment, you get the public recognition of having both titles (Professor of X and Professor of Y) and you can advise and teach in both departments.  However, administratively you have a primary department that pays your salary and sets your teaching/service duties.  The main drawback is that if you want to split your teaching between the departments, it may take some arranging.  [In my experience this can often be done, but it's not guaranteed by a courtesy appointment.]
With a fully joint appointment, the two departments split your salary and duties in some set fraction (usually, but not necessarily, 50-50).  This makes it easy to do substantial amounts of teaching in both departments, but it can mean a slightly higher service load, since a 50% appointment often doesn't really cut the number of meetings in half.  The biggest drawback of a joint appointment is having to keep both departments happy, especially if they disagree on how you should be spending your time.  [This is a real danger for tenure cases.]

If you'd like a courtesy appointment in another field, you need someone in that department to serve as a champion for your case.  You can sound out friends or mentors privately to try to convince someone to advocate for offering you such a position.  Once someone brings it up at a department meeting, you then need a good enough reputation that the department is happy to have you associated with it.  Ideally, you should be someone they would have loved to hire if you hadn't already joined another department; in practice, you can sometimes get away with a slightly weaker case than that, but you still need to look strong enough that there's no fear you'll hurt the department's reputation.  Once the department is behind you, there may also be some administrative hurdles (perhaps including letters of recommendation).

Switching to a genuine joint appointment is much trickier, since you need to convince the other department to start paying for you.  Why should they do that when they could offer you a courtesy appointment for free?  There are various possible answers, such as:

You're so famous that they'll cheerfully do whatever you want.
They really value you, and offering you this appointment will keep you from leaving.
You'll fill a role in the new department that they would have had to hire someone else for anyway (e.g., teaching certain classes).
There are deals being made behind the scenes.  If department Y takes over half your position, what might department X offer them in return?

If you want to bring this about, you'll need to spend some time crafting a compelling argument.  There are many directions you could go in, but ultimately it will depend on the department's needs.

As I mentioned above, tenure cases can be really tricky for joint appointments.  Both departments end up with a de facto veto, since if one turns you down the other isn't likely to be enthusiastic about coming up with the extra money to save your job (taking the other department's reject doesn't feel good).  Before tenure, I'd consider a courtesy appointment to be a much better idea.  Once you get tenure, you can then reevaluate and see what your options are.


How much does one explain on a PhD application if an MA took 3 years instead of two? I am applying to History PhD programs, and recently finished my MA thesis and coursework in August 2016.  But I began initially began MA studies in Fall 2013, and so it took me three years instead of two.  Basically I took a full-time course load for one year and then shifted to part-time (my undergraduate study was completed in the common 4 years).  I would think that my reasons for delay would be fairly common, but I'm entirely unsure on how decisive the admissions committees typically look at these kinds of things, if it is necessarily to explain them, and if so, to what level of detail:

1) I'm a veteran, but ran out of GI Bill funding after first year of study (Fall 2013-Spring 2014).  MA students aren't funded where I went, so I was strapped for cash and had to stretch money and span out my education expenditures.

2) I'm married, and from Spring 2014-Spring 2015 the marriage basically exploded and ran off the rails.  The catalyst was the intensity of time/being I devoted to graduate study and undergraduate study previously, which ignited the underlying marital issues type of thing.  So we cut back on everything and took time to work on the relationship.  Everything now is resolved in its entirety, and except for a medical emergency requiring me to care for my partner, none of these previous issues can really possibly arise any longer.

3) I did fieldwork and took extra time in revising and extending my thesis, which ended up to be more like a mini-dissertation.  At least as my professors told me, they all supported the project because of this potential and weren't too concerned about me taking Fall 2015-Summer 2016 for its completion (and its still a work in progress with numerous gaps).  Most of the professors in the department I worked with have encouraged me to apply to the top PhD programs (Harvard, Yale, Brown, etc.).

Number 3 seems easy to explain and incorporate if I need to.  But number 1 and 2, I'm not sure.  I do not want it to appear as if I could not handle the workload or something; although, I could see that in the most immediate, practical sense, I couldn't actually handle it, since I could not balance my marriage/family issues with my scholarly pursuits.

Anyone been in the same situation when applying to PhD programs?  Any advice or tips?

From what I have been told, no one cares if it took you a little longer.

Especially if you don't have multi-year gaps in employment + education then there really isn't anything to explain. You could spend some words in your Statement of Purpose on explaining the good things that you did during that time (fieldwork and working with profs).


Is 100 hours per year of teaching a heavy load for a lecturer? I have recently been appointed as a lecturer in a scientific department. This is a permanent position. The responsibilities of the position include: teaching, conducting high level research, administration tasks, mentoring and supervising students. The teaching load is 100 hours/year, which I found a little bit excessive.

My question is: are 100 hours of teaching a heavy load or is this common in academic institutions (universities)? In particular, scientific departments (chemistry, mathematics, physics ...).

The load seems reasonable for an established lecturer, but is a little heavy, by UK standards, for a first year lecturer. It might be worth asking for a partial teaching (or marking or tutoring) release for the first year.

Many universities, including those in the UK and US, talk about the split between research, teaching and admin. A split of time of 40% research, 40% teaching, and 20% service is not atypical at a UK Russel Group university. In the UK, the work year consists of about 1800 hours (37.5 hours per week times 48 weeks a year). With a 40% teaching load, you should be doing 720 hours of "teaching". I have never heard of a Russel Group university with a teaching load lower than 30%. The non-Russel Group universities I am familiar with don't go above 60% teaching time.

Teaching obviously consists of more than just standing in front of students lecturing. My UK university work load model credited us with time for supervising undergraduate final year project students, our mandated office hours, marking, tutorials, and lecturing.

We typically had 40 office hours (2 hours per week of the two 10 week semesters) and 150 grading hours. This left about 530 hours of traditional teaching time (tutorials, lectures, and practicals). For every hour of tutorial and lecture, we are given either 4 or 8 hours of prep time depending on if it is new teaching or not. This means an established teacher would have 132.5 hours of lecturing a year and a new lecturer would have 66.25 hours of lecturing a year.


What is a suitable job title for someone responsible for creating large data sets? I write and record hundreds of sentences and format them in a way so they're ready to be fed into an AI model used in a chat bot. What job title would you consider this to be?

I think you are a "data curator."
This paper indicates that US participants consider a data curator as one overseeing the entire data management cycle, while their European/Australian counterparts have a narrower view focused on technical aspects of archiving in the final stages of the data cycle.
Below is an excerpt:

The use of the term data curator and its broad understanding was quite prevalent among the US professionals, while Australian and European participants made a clear distinction between data curators and data managers and did not use the terms interchangeably.
Participant P stated: "Data manager is for the first part of the data life cycle and data curator is in the last part of it. The data curator reviews, migrates, and enhances data and metadata, whereas the data manager helps with data collection, metadata standards, and creating coherent and authentic data sets (that ideally subsequently need less curation). A data curator rather works with the final data objects, to optimize them to a final version that can’t be manipulated anymore after that.


Can a professor influence the graduate admissions committee if he or she is interested in a particular student? I've had a promising Skype interview with a great professor from a top-level university in US. Our research interests are closely related and he encouraged me to apply BUT he says that all decisions are finally made by admission committee there.

The question is "Is a professor in such a high-level university able to affect admission committee if he really wants a student?" or "Does admission committee decision-making process become easier if a professor really wants an applicant?"

The main point is the difference between my transcript (which is a real catastrophe!) and my research background which is pretty good so the professor's decision might be different from admission committee.

Being on the graduate committee of my department, if a professor sends us a note that they'd like to have a student admitted and state that they will take on their adviser role, we will only not admit that student if there are any red flags in the file. Most other considerations (including GPA) are not all that important any more at that point.

The reason for this is that what you get to see about a student from their application file is really just a very inexact science. You get transcripts that don't say very much about the standards in each of the classes a student took, letters of recommendation that sound the same for almost all students, and statements of purpose that most of the time are pretty generic as well. In my assessment of files, GRE scores and the statement of purpose often carry most of the weight, but I am fully aware of the fact that GRE scores poorly correlate with success in graduate programs. In other words, if I can get a personal opinion from one of my colleagues stating that they're excited to work with a student, then that is worth a whole lot and it will carry the day unless there are obvious reasons in the file of a student to reject the application.


Is it possible for someone to do their masters in Maths once they've earned their degree in Computer Science? I was wondering. Is it possible for someone to major in Maths as in do their masters in Maths once they've earned their degree in Computer Science?

Yes, you can. I know several people who have switched their graduate degrees, e.g. Math -> Computer Science, Biology -> Chemical Engineering, etc. You might have to take some extra classes, though.


Are professors allowed to accuse someone of cheating based on a general increase in test scores? Let’s say a professor has seen that the average score for the midterm exam was a grade and a half higher than it was in previous years. Because of this he gained a reasonable suspicion of cheating (he has been teaching the course for several years in the same way and this is the first time he has received such high scores). He looked at the score distributions and found it to be bimodal:

He went on to assume that, since this distribution wasn’t like his normal distribution he had received on his test scores in previous years, one third of all his students cheated on the mid-term.

Now here comes the question, is it ethical and reasonable to assume that one third of the people in his class were cheating? Maybe the distributions were different and bimodial because some students studied harder (causing peak at better scores), while others didn’t (peak at lower scores). Are professors allowed to make everyone retake the test because of this data (even the ones who took it honestly). This punishment seems like he is punishing the supposed two thirds of the class that took it honestly.

The professor goes on to claim that those students who had significantly higher scores than in their previous test must have cheated! Are professors allowed to that? What if they got a bad score on the previous test because they didn’t study and they got a good score on the mid-term because they did study? Also what if a student has a good score on the previous test and the mid-term because he cheated on both? Or what if the student was honest and received a good score on both test because he is a hard working student? So my question, Is it normal practice and ethical for professors to accuse someone of cheating just by looking at the student’s test scores?

PS: This didn't happen to me. I just heard about it from a friend.

First, as you already noted, the better scores and the bimodal distribution may have other reasons. For example:

One of three TAs for the course did an outstanding job.
The professor reused questions from previous exams (perhaps without noticing) and one third of the students informed themselves about previous tests.

Most importantly, the following thing is odd: It’s highly implausible that the rate of students who decide to cheat on their own increases by that amount from one year to the next. Thus, they would have to decide for cheating together or due to some common motivation. This in turn only makes sense if the cheating is a collaborative endeavour or if somebody is helping the cheaters.

Now, while such scenarios are not unthinkable, they are usually as likely as possible explanations that do not involve cheating (your mileage may vary depending on the circumstances). Moreover, even such a scenario happened, just repeating the exam is unlikely to solve it. Therefore the professor should first find out what actually happened.

So, the statistics may point at something being unusual, but without further investigations you cannot say that it’s cheating. Moreover, even if it is cheating, statistics can only tell you that it happened, put cannot point to any individual involved in it.

To address your individual questions:

  Are professors allowed to accuse someone of cheating based on a general increase in test scores?

  The professor goes on to claim that those students who had significantly higher scores than in their previous test must have cheated! Are professors allowed to that?

Technically, yes. Almost everybody can accuse everybody else of everything as long as we are not entering the domain of libel laws. Will it be successful or a good idea? Probably not, at least in any reasonable university or jurisdiction. And that’s not even considering that he has not one but many students against him.

  is it ethical and reasonable to assume that one third of the people in his class were cheating?

Assuming something cannot be ethical or unethical; acting upon an assumption on the other hand may be, but that depends on the action.

  Is it normal practice and ethical for professors to accuse someone of cheating just by looking at the student’s test scores?

Normal practice – I never heard of it. Ethical – certainly not. There are several possible reasons for a good individual test result, e.g., hard work and plain luck. The professor should be aware of this and thus the accusation is unfounded and hence unethical.


Promotion But No Change in Salary? Recently I received notification that my application for tenure and promotion to associate professor was approved. However, I have not yet received a letter indicating what this actually means as far as any potential changes in salary. Is it unusual not to find out what those changes would be when you are promoted from Assistant to Associate Professor? Or do you typically not find out until the beginning of the next semester?

It will depend on a specific department, I guess the best way to find out is to ask (the department head, or the business office of the department). For example, at our department, Assistant to Associate comes with "automatic" $5k salary raise, while Associate to Full has no automatic raise whatsoever...


What do "AE", "EO", and "PROD" stand for in a journal submission system? What do "AE", "EO", "PROD" stand for in the manuscript status in journal submission systems like ScholarOne?

AE means Associate Editor: Responsible for communication with reviewers of a research manuscript.

EO means Editorial Office: The formal group/office comprising of Editor-in-Chief (EIC), and Editorial Assistants/Admin Assistants.

PROD means Production Department: Responsible for printing of articles post acceptance.


Designing the "user experience" for labs without giving too much away I have a rather unusual UX to design.  I'm writing a laboratory manual for engineering students learning how to build electric circuits.  The manual will be an interactive webpage.  One of our biggest complaints that we get from students is that the labs are too "cookie cutter", meaning that we often just list the exact steps they need to take in order to complete the lab.  Students would prefer to explore more on their own.

My idea is to design the lab manual in such a way that tasks that are not relevant to the learning objectives, but which must be done in order to achieve those learning objectives, are presented in the cookie cutter way.  Tasks that are relevant to the learning objectives are described differently.

An example of the first type of task would be: "Plug the red cable into the red jack on the DMM", accompanied by a picture.

An example of the second type of task might be: "Taking as many measurements as you think you need, generate a data set you can use to determine a model of the sensor".

Here is my problem: I want to create this lab manual and test it on real students.  However, I don't know which actions students will take while working towards the goals of the lab.  I know what I would do, but that's only one possible way to achieve the goals.  If I observe students who are working on the lab to determine the steps that they take, I can determine which tasks are frustrating them.  I then want to take those frustrating tasks and determine which ones are not really relevant to the learning objectives, so I'll just make them cookie cutter.  However, how do I generate that list of tasks?  I can think of two ways, neither of which are good:

Make the first version totally cookie cutter and observe student frustration
Make the first version completely not cookie cutter and observe student frustration

My issue with 1. is this imposes my method on the students, which is exactly what I'm trying to avoid.  It won't give me any information regarding which tasks need to be more open-ended.  My issue with 2. is that there are some tasks that are not intuitive and just need to be explained quickly. It won't give me any information regarding which tasks are really frustrating for the right reasons, since students will be frustrated by irrelevant tasks as well.

Any thoughts?

As @MassimoOrtolano mentioned in a comment (and I think this extends to all lab courses, not just EE), "the main factor is the time constraint." Clearly your suggestion to make the preparatory/emphasized steps "cookie cutter" and the learning objectives more open-ended is a way to approach this time constraint with balance.

It sounds like your main concern is in determining which of these steps should be cookie cutter and which should not. You give two approaches: start from the beginning and work forwards, or start from the end and work backwards.

However, that assumes you are going into this with no information. That might be a principled approach in some cases, but if I can be a Bayesian for a moment, you are missing a crucial piece of prior information: you should have some idea of what your learning objectives are before you even start.

The approach I would take is to first identify learning goals, then sketch out the procedure and identify which steps are relevant to the learning goals and which are not. Cookie cutter those that aren't, leave open-ended those that are. Surely, this won't produce a perfect lab course on first pass, and it might take some tweaking over time, but it seems like you expect this and it is a better approach than either extreme.

Second, involve your students in your goals. I think it's best to think of students as if they are quite capable and smart. Let them know: "I designed these labs so that I give you a step-by-step through some of the things that aren't relevant to the learning goals of the day. At the start of each lab, I will provide you with a list of the intended learning goals. I am looking for feedback if you either a) feel like you are spending too much time on something that isn't a learning goal, or b) feel like the answers are being handed to you for the things that are."

When in doubt, it seems like it makes some sense to bias towards cookie-cutter towards the beginning of the course and towards more freedom in the end, but that depends on how well the different pieces fit together and how complex the problems get by the end.


PhD Application Consultants/ 'Services': Can US/EU professors/ admissions committee tell when someone uses these? Disclaimer: I did not use these, but I have acquaintances who did.
I'm asking from the perspective of an international student.

These 'PhD/ MS Consultants' do the following (in ascending order of sketchiness):

Assist in CV/ Resume/ Visa Interviews
Provide a list of universities to apply to based on your CV strength
Write your SOP for you

My question is: Can admissions committees tell? Some people who used these got into pretty good universities (Ivy League), which seems rather weird.

If consultants are honest and do their job well, I doubt that the reader of an application could tell. I also have no issue with using consultants. People who are unsure of how to proceed with an application seek advice many places. Some seek it here, actually.

An honest consultant will work with a candidate to develop an application. Saying that they "write" the SOP is a bit incorrect if the ideas in it come from the candidate. This might be especially true for non native language speakers applying outside their own countries. But the honest consultant will work closely with the candidate, not just put their own ideas to paper.

But a dishonest consultant would be more likely to provide "boiler plate" information, not really related to the candidate. Those might be easier to detect, but only if a given committee saw previous applications that were similar.

But for a lot of candidates who get in to the ivy league, their own parents may be good consultants who do all of what you suggest. Of course, the recent news also suggests a few are willing to pay bribes as well.

I think that writing the SoP, if done properly, is fine. But if a "writing sample" is requested from the candidate, that person should be the one to write it. But even there, seeking advice on what to say and how to say it is probably pretty common.


What is the motivation to start a new journal in a crowded field? I've recently noticed a trend of big names in my sub-field starting new journals whose scopes substantially or fully overlap with pre-existing journals, and the motivation is not very obvious to me. To be clear, these are intended to be reputable journals with rigorous peer review, hosted by major publishing houses such as Wiley or Springer-Nature, so I guess it's not a money-grab or anything similar.

To give some more background, my sub-field already has 4 well-established journals devoted to it, as well as >10 journals whose scope intersects with my field (think bioanalytical chemistry vs. analytical chemistry), not to mention the Science and Nature-level journals and the catch-alls such as Scientific Reports. Many of these are highly-regarded society-led journals, with 20+ year histories and the journals all have stable impact factors that range from incremental (1-2), standard (3-5) to relatively high impact (6+), accommodating a wide variety of work.

Thus, it seems a bit mysterious to me why someone would go to the substantial effort and expenditure of personal political capital to create a new journal, harangue your colleagues to submit, convince people to review, etc., when there isn't a clamoring need in the community for yet another journal?

Being able to set editorial policies can have a significant impact on how science is done in the field. Some examples of such policies include: encouraging the use of preprint services, mandatory data/code sharing, transparent peer review process, encouraging replication studies, etc. For the big names who are not satisfied with simply setting the direction of their own labs, setting up a new journal can be another ideal career ambition.


Could a journal reject an article due to the style or quality of accompanying code? I'm a student working on a doctoral thesis. We're working on a paper for which I've done most of the coding for the statistical analysis (the field is microbio/bioinformatics). I'm new to coding and the whole thing is more of an add on to my "real" career, which is medicine. Therefore, my style of coding is more than basic I'd say. Now I fear if we're handing in the manuscript plus the code to a journal for peer review it will be rejected or ridiculed. Is this possible?
edit: I use R to conduct a large statistical analysis. If someone would like to point out online learning resources, esp. for the fields of medicine/biology, I'd be very grateful.

You will not have a paper rejected for poor coding style. Particularly not in bioinformatics. Unless the paper is a tool development paper, the chance that a reviewer even looks at the code is not that high, and if they do, it will just be to check that its reasonable. In the outside case a reviewer might spot a bug, or poor assumption that actaully makes the result wrong, but they will not reject you for poor style.
However, having the code associated with the paper massively increases the chances that it will be useful to someone else.


Can I cite lecture notes? I’m now writing a masters thesis in mathematics. I’d like to introduce basic definitions and theorems in the beginning. By basic I mean truly basic, like the definition of a connected graph and the theorem about Eulerian paths (such a path exists if and only if even degrees).

The lecture notes written by my professor is really nice so I’d like to use his definitions (I’ll cite, of course). In this case can I cite his lecture notes?

While there is no real harm in citing it, it is unlikely to be necessary. Common knowledge is one of the exceptions to the requirement for citation. Many things that you first see in a course fall under this cover, even if they are new to you.

But you seem to be more speaking of copying the notes, rather than citing them. That may be a different issue if they can be considered to be copyrighted. In that case you want permission from him.

Do a little research in a textbook or two. Do those definitions, or something essentially similar to them appear there? I suspect they do. If so, there is no need to be concerned. And also note that one of the exceptions in copyright law (most places) is that for some things there is only one effective way to state something, so it's expression can't be copyrighted.

And it wasn't your professor who originated these ideas.

But an acknowledgement to your professor for introducing you to these ideas would be a courteous thing to do.


Removing articles from ResearchGate Over a decade ago, when I was about 11, I fancied myself as budding social scientist and wrote a few "papers" of extremely dubious quality  which I uploaded to SSRN. I kept up the interest in academics, in physics, and recently became aware of their continued existence. I deleted them from SSRN, but it seems ResearchGate had already created pages automatically for them. I can remove the papers from my newly created profile but I can't find a way to delete the pages from accessibility via Google. I have quite a distinctive name, so there's no deniability there. What should I do?

I am not familiar with SSRN, but it seems that when you publish content there you give SSRN a license to display the paper, but this is not a transferable license like a Creative Commons one. If that's the case, and if you did not publish the paper on a journal or elsewhere, then you are the copyright holder and Researchgate does not have a license that allows them to publish it. Then they are infringing your copyright, and the correct legal step to take is filing a DMCA takedown request using this PDF form.

IANAL.


Is it disrespectful to do research in two labs? Context: Undergraduate computer engineering student in the US looking at attending graduate school in two years. I’m trying to figure out which research topics interest me—hopefully to find one to pursue in graduate school. I’ve only done one semester of research so far and I’m switching out of that lab because I didn’t enjoy it (unhelpful PI and graduate assistants).

Question: Is it seen as disrespectful to be in two different labs at once when trying to figure out a research topic to pursue? If not, should I be aware of any other conflicts when working for two labs?

I’m concerned primary about how this will be viewed by the professors, not the ethics of being in two labs (the research topics are pretty different).

We had an undergraduate in our group quit abruptly at the end of the quarter, saying he liked the research better in the other lab he was working for. This is fine, everyone knows some people won't work out for whatever reason.

However, this was the first time my PI had heard he was "two-timing" us, and yes, she was pretty upset.

I do not think it's per se disrespectful to work in two labs at once, but it is certainly rude to hide that fact from one or both groups. That said, if you tell two PIs that you're working in two labs to figure out what you like better, they may be less inclined to help/mentor you because they know there's a big chance you'll drop their lab pretty quickly because you can fall back on the other lab you like more.

I don't recommend this course of action, but as long as you're transparent with both labs, I would not say it is wrong of you to attempt it.


Do postdoctoral studies have official certificate? I have seen that some universities give postdoctoral fellows an official certificate (similar to the PhD diploma) after finishing their postdoctoral job. On the other hand, some of postdoctoral positions are just simple research (or even academic) jobs. I have even seen that some professors pay the postdoctoral fellows without contract (from their grants).

My question is: How common is a certificate of postdoctoral studies? Do future employers expect applicants to give them certificate of postdoctoral studies as well as PhD diploma?

Certainly not in the US.  I never got any kind of certificate for the postdoc I did, and in fact I'd never heard of such a thing until your question.

My current employer never asked for any formal verification of my postdoc.  They received letters of recommendation from my postdoc supervisor and other colleagues at that institution, and I think most US academic employers would consider that sufficient.

Then again, they never asked for my PhD diploma either.  In the US, we don't use the diploma for official purposes; it's just a decorative piece of paper.  The official document of choice is a transcript sent directly from the university (and my employer did ask for one of those).


Introducing myself to researchers from my dream school I am applying to a PhD program in a few weeks, and I am also going to give a presentation at an upcoming international academic conference. I heard that a group of researchers from my dream school is also going to present their work at the conference, and at least one of the researchers might be a member of the admissions panel. I would like to introduce myself to them, but I don't want them to think that I am trying to win their favor just to increase my chances of getting accepted.

I recently had an informal Skype meeting with a potential PhD advisor, and she agreed to supervise my research if I get officially accepted. She does not belong to the research group and she is probably not attending the conference.

Could you give me some advice on how to talk to them in an ethical and appropriate way? Would it be fine to let them know that one professor is already willing to accept me to their program? (The conference will take place before the deadline of the application.)

[EDIT]
Thank you @ReinstateMonica for your answer. As (s)he pointed out, there was inconsistency in what I wrote. My potential advisor is willing to take me in, but she is not the one who will make the final admission decision. (My understanding is that my application will be assessed by her and one or more other professors.)

That is called networking and it is about getting to know people and people getting to know you. It will increase your chances and that's exactly the point.

There is absolutely nothing wrong, immoral, or illegal with it, by the way, it is a necessary skill for all professional careers. Conferences usually have intermissions for that exact purpose, with snacks, refreshments, etc.

The "standard" way of doing that would be to walk over, politely introduce yourself (don't go all formal), from which school you are and briefly, very briefly, what you are working on. Don't be pushy, don't force the conversation. It is easier if a common acquaintance introduces you (for instance, another researcher that knows you and them). Bonus points if you are familiar with their work/field.

It's easier after they see your presentation, but that's not entirely necessary. The most 'busy' researchers don't usually attend the whole conference, so don't waste chances.

More importantly: forget dream, don't be starstruck. They are just people, it is a school, just like countless others. Something I saw people do wrong: don't get stuck talking shop, especially if you have more time (as in the formal dinner some conferences have). Again, professors/researchers are people, they do more with their lives than just research and certainly have some other interests.


Thesis: supervisor's project or my project? Two years into my PhD, I am troubled by a situation that made me having to decide on whether to focus mainly on my supervisor's assigned project or my own project as part of my thesis.

The story begins like this. My supervisor promised me a PhD project at the beginning of my PhD to attract me to join his lab (I have my own PhD studentship with all funding attached at that point). But after I joined the lab, I found out that the project is never meant to be done as no one in our lab works in that area or possess the technique.

He then assigned me a few projects that come to the lab from collaborators. The projects did not pan out well due to miscommunications with the collaborators that involve multiple parties, and I begin to lose interest in them to the point that I just want to get them over with. When the assigned projects get stuck in limbo, I started to work on my own project, as I really want to finish my PhD. Doing my own project is difficult as the project involves some knowledge that falls outside the expertise of my supervisor, but I persevere and the project starts to take shape. I am fairly confident that I can get a publication out of it and should be able to write my thesis with it.

My supervisor is unhappy about this, but he lets me do my work as he was occupied with other matters. Recently my supervisor told me that he expects me to treat those assigned projects as my PhD project and to include them in my thesis. I am happy to work on those projects as my side projects, but I want to focus mainly on my own project as it is beginning to take shape. However my supervisor wishes me to work mainly on those assigned projects, and he made it clear that he is not interested with my own project.

My impression is that a PhD student should be able to determine what projects to work on and to include in the thesis. Obviously I am happy to do some side projects to keep my supervisor happy, but I am hoping that I should be able to decide what I want to work on without offending my supervisor.

Any opinion and advice is much appreciated.

My impression is that a PhD student should be able to determine what projects to work on and to include in the thesis. Obviously I am happy to do some side projects to keep my supervisor happy, but I am hoping that I should be able to decide what I want to work on without offending my supervisor.

In an ideal world, yes. In reality, there are practicalities to consider:

At least here in Europe the biggest factor is what the grant that pays for you says. If you are, for instance, funded via an H2020 project, you are most certainly not free to decide what you want to work on. Your money comes with a clear "description of work", and substantial deviations from this work plan need to be justified. Other grants may be less (or, in case of industrial funding, even more) strict, but there is certainly no universal rule that as a PhD student you should be free to work on whatever.
Another factor is the strategic research plan of your advisor. Your advisor has, or at least should have, a long-term plan, and if your project does not fit in with the plan, your project may be, speaking bluntly, a waste of time and money for him, even if it is an otherwise nice project.
There is also the problem that your advisor also requires some competency in your project, both to help you when you are stuck and to evaluate your progress and final dissertation. Many advisors will be unwilling to supervise students on research attempts that are too far outside their core expertise (usually also in combination with the previous point, that those are often simply not very valuable to their long-term goals).
Finally, your advisor may also be wary that the project may not be academically promising enough. I have seen often that younger researchers tend to confuse projects that are "interesting to work on" with those that are "likely to lead to interesting results". You should at least consider why your advisor is "not interested in your results", and ask yourself the question whether other senior academics will feel the same.

Of course this does not mean that you always need to slave for your advisor and should bury all ambitions of developing projects on your own. In practice, the best PhD students juggle their own interests with the interests of their advisor.


Expected undergraduate semesters and requirements for graduate students I have been wondering recently about how graduate schools and in general anyone who reviews my academic record views coops. By coop, I mean a semester taken off from undergraduate studies to work in a related industry. If the student takes more than 8 semesters to graduate, is it a problem? Should the student (if they can) extend their studies by an additional semester so that they graduate in the spring, or is a fall graduation equally acceptable. Do grad programs accept students to start in the spring, or only the fall?

I tried to keep the question above general pursuant to the guidelines in the FAQ, however I will appreciate anyone who is willing to review my specific case.

I am a sophomore in CS at a strong US engineering school. I have 2 summer internships, and now a coop under my belt. My problem is, I do not like any of the work I have experienced. I don't mind programming, but it is not something I can do for 40 hours a week without getting really bored. I only really enjoy the difficult math problems, which don't come up that often for most CS jobs,and I absolutely hate wires, soldering, network-admin and low-level computer work.

I want to switch to Math and pursue a graduate degree in either data science or applied math. I can graduate on time by dropping to a math major and a cs and stat double minor, or I can add a semester and get a double major in math and cs or stats, or take graduate classes. I should also mention that my GPA is currently at 3.2 largely because I have tried to alter the CS curriculum to incorporate the things that interest me (a realistic expectation is a 3.4-3.5 graduating GPA). My final consideration is that the math dept at my school is somewhat low on most academic rankings, whereas my CS dept is in the thunder-weight category trailing the likes of MIT. It would not be hard for me to find research opportunities in either department, which I intend to do either way.

I have been wondering recently about how graduate schools and in general anyone who reviews my academic record views coops.

Coops are fantastic.  Especially for programs in computer science / applied math / data science, relevant industry experience is a strong advantage in graduate school applications.

  If the student takes more than 8 semesters to graduate, is it a problem?

No.  Nobody cares.  Even if someone on a grad admission committee noticed, the longer time would quickly be explained by your coop semesters and your change in majors.

  Should the student (if they can) extend their studies by an additional semester so that they graduate in the spring, or is a fall graduation equally acceptable.

Acceptable to whom?  If you mean graduate admissions committees, then I repeat: Nobody cares.  In particular, graduating in the spring is no barrier to starting a graduate program the following fall.  (Of course, you have to eat, but that's a separate issue.)

  Do grad programs accept students to start in the spring, or only the fall?

Some do, some don't.  Every grad program is different.

One last point: You mention coops, GPAs, and program reputation, but those are not the most significant bits.  Graduate admissions committees at top departments are primarily looking for strong evidence of research potential.  Assuming my quick Google search correctly identifies your university, you should have lots of opportunities for undergraduate research experience with world-class faculty.  Take advantage of them!  Start now!


Doctoral Consortiums: When, How Many and Are they actually useful? I am a fourth year graduate student of information science. Broadly, I work in a rather interdisciplinary area at the intersection of location based social networks, usable privacy and surveillance studies.

I am post A exam - which in my university refers to a combination of qualifiers, orals and dissertation proposal/prospectus confirmation. I am regarded as ABD/doctoral candidate in my university. I go on the job market in another 6-12 months (depending on certain criteria such as in progress journal articles being published on time etc.)

In my specific field, folks publish in a combination of journals and conferences tending more towards the latter although my committee prefers the former.

My adviser and I have been discussing the possibility of my presenting a general overview of my doctoral dissertation work in doctoral consortiums in various conferences to get feedback and exposure to the community as a whole. Some of the sample conferences where my work is a good fit are here, here and here. I am looking to go into academia primarily (looking for both calls for tenure track positions as well as post doctoral positions)

My questions to the academia.stackexchange community are as follows:

How useful are doctoral consortiums for feedback and presentation of your dissertation in-progress to the broader academic community?
When is a good time to start attending doctoral consortiums?
How many doctoral consortiums are "enough"? (assuming funding to attend multiple ones)

Thank you for reading this question.

Having attended one of the doctoral consortiums you linked to as well as one you haven't, here's my perspective (as a student) on what doctoral consortiums provide a venue for:

A) Networking with peers and senior researchers in your field in a very targeted way.  A prolonged period of time ranging from 1-2 days is usually provided where you'll be closeted with other consortium students and senior researchers.  This gives you a set amount of time where not only will you have a bunch of students with you who are also interested in networking, but where senior people in the field who may not generally be approachable during a conference will be available and open to talking to you.  In addition, it also gives you a subset of people that you know will be at the conference that you can continue to network with during breaks and meals.

B) Getting an outside opinion on your research.  Doctoral consortiums will usually give you time to present your research so that the senior people in your field can give you feedback.  As a PhD student, sometimes it's difficult to get a perspective outside of what your advisor's agenda is.  Feedback during consortiums can help to provide new insights into how your work will be received in the larger research community, what people in the community perceive to be the strengths and weaknesses in your topic area, and how they think about what you're doing.

C) It gives you a place to practice presenting your research to a wider audience than just your advisor or your lab.  Even in a specific research area like human-computer interaction, which you linked to, there is a wide spread of topics that people will be doing research in.  Presenting at a doctoral consortium gives you a chance to really try to explain your research to a receptive audience that may have no background in what you're doing.  It's sort of like having a low stakes first shot at what you'll have to do when you eventually give job talks.

D) Depending on the conference, doctoral consortiums are arguably really nice for your CV because some of them are very selective and difficult to get into.

Not all doctoral consortiums are the same, but generally they are targeted for the point in your graduate career when you've picked your topic, done preliminary work or published a paper or two in that area, but before you're really entrenched in your planned research and can still change direction.

The idea is that by getting that outside feedback from senior researchers in the field, they'll be able to give you a nudge in the right direction if they foresee real problems with your topic/work in time for you to make corrections.

The general opinion that I've heard/witnessed has been that going to more than 2 is overkill and that at that point you won't be getting much out of them.  However, it's really good to get into at least one as a student.

A last point, since you mention funding, many doctoral consortiums provide some level of funding for students that have been accepted to ensure that they can attend.  In addition, they will often cover the registration fee for the conference that they're attached to.


How to penalize students who copy each other but don't realize they have plagiarized? I gave my students an opportunity to rewrite one of their papers for extra points. As I was grading, I realized that two papers were almost identical. They had a similar structure, organization, and presented ideas in a similar manner. I asked the students about plagiarism but they denied it. Since it was a rewrite, I told them that I wouldn't add any points to their grades and they should never do this again.

One of the students, however, emailed me stating that she is worried their final assignments might look similar as well. She was trying to convince me that her paper is her original work and the second student "worked really hard to make sure their papers don't look alike!".

She included screen shots of their fb conversation as evidence. In FB conversation the one with the original work is telling her friend to use her paper as a basis but change the sentences and examples so it won't look like plagiarism.

This is a clear case of plagiarism. Correct? I am not sure how to handle it. I know they are not realizing that's plagiarism, otherwise they wouldn't have shared those fb conversations. So I don't want to report to the school (yet!). But I am also not sure how to penalize them? Give a zero for the assignment? What do you recommend? Should I give zeros to both of them?

Learn about your school's policy. Learn about whether your school has an honor code, defines plagiarism in its catalog, or requires mandatory training such as an online orientation. Many schools have specific rules about what kind of punishments are allowed, and these rules may be based on their own interpretations of local laws or their past experiences with lawsuits. For example, my school's policy specifically tells us that we are not allowed to give a student a failing grade in the course for dishonesty, and it also spells out different levels of consequences for a first and second offense.

Look at your own syllabus to see what you said about plagiarism; usually administrators will support you on anything that's laid out clearly in your syllabus.

Don't assume that administrators will support you. Their priorities may be very, very different from yours.

Once you have done all your homework, talk to your dean and propose how you want to handle the issue. Make sure your dean is on board with what you plan to do. Consider "soft" penalties such as forcing the students to meet with the dean.


Collaboration on a suggested project - problem with a colleague I would like to ask you for an opinion on how to act in the following scenario.

A year ago, some colleague PhD of me has suggested an open problem to me. This problem was already published in his paper, which is on arXiv.

He suggested that problem to me and invited me to collaborate on it.
However, he is not very hard-working and I personally suspect that he is just waiting for me to prove it.
He is working in that way quite often.

I, somewhat blindly, agreed to work on it. However, I do not like the way he
“collaborates” and I would like to work on that problem on my own since he is not helping at all and only waits till the problem is solved so he can write it as a result to his grant.

We are very far from being published. Actually, not much work was done yet. I want to work and solve this problem on my own.

How should I proceed?

Simply ignore him (he didn’t speak about problem for months) and publish the results?
Tell him about my opinion, quit, and publish the results?
Proceed and publish the results with him as a co-author.
Do something else.

I will come at from the other direction. I will assume that your summary is correct, and that this person truly did nothing other than point you to a question that had already been posed in published work. In this case, you are under no obligation to work with him. You must be careful to cite his work appropriately, and probably acknowledge him in the acknowledgment section as having suggested this line of research, but I don't think he has a legitimate case for co-authorship.
That said, he could still create a messy, public confrontation. So, I would send a note like this:

John,
Some time ago, we discussed collaborating on an effort to prove [blah] as an extension of your work in [blah]. So far I don't think either of us has made much progress, so I wanted to reach out with you about resurrecting this work.
At this point, I think it would be best if I tackled this on my own. If successful, I will write up a paper that cites your paper, and will acknowledge you in the acknowledgments. What do you think?*
-Name

Depending on whether you are willing to consider working with this guy, you could also replace the last sentence with:

If you would prefer to collaborate on this paper as a co-author, we can discuss, but I am hoping to publish in the next ~6 months, so we should meet ASAP to discuss what you will contribute and when it will be ready.

Then there are a few possible outcomes:

If he ignores you, or says "good", then all is okay.
If he claims to be interested in collaborating with you, you will have to discuss this with him.

You may need to be fairly aggressive in telling him that you don't think collaborating will be feasible, but better to have this argument now and in private, rather than after publishing without him.
If you are willing to give him a chance, you can try to define his contributions and the deadlines now, and let him know that if doesn't have satisfactory material by the deadline, you will publish your results without him. If he is serious about working with you, then this is reasonable; if he is lazy as you say, he may withdraw his objections.

If you cannot come to terms, or if he reacts very poorly, then you can decide whether you want to risk a nasty, public fight over authorship, or whether you want to drop the line of research.


My advisor completely ignores me what should I do? My advisor became an assistant professor nearly two years ago. I worked with him for one year but did not publish a paper, and he thinks my progress is too slow. He asked if I want him to assign a new PhD student on this project. After that, he completely ignored me and stopped funding me. I also find our research interests are not a good match. The project he gave me requires something new to him and me, and I think that’s a hard problem which needs more time.

What should I do? I want to change advisor and don’t want him hate me. Should I go to his office directly to talk with him, because he did not reply me after I send him several emails. I am just afraid the bad relationship will influence my reputation in department.

If your advisor has stopped funding you, it has already affected your position in the department.

You should consult with the graduate chair of your department and see what your options are. I’d like to say that there are solutions, but this is unfortunately very much a function of who has funding and is doing a project in an area you’re interested in pursuing. You may need to apply elsewhere, if you can’t find a solution at your school.


How effective is ResearchGate as an academic selection and recruitment tool? I've informally noticed that ResearchGate seems to have increased in popularity over the last year or so. I also noticed that, while I'm not on the job market, ResearchGate was able to successfully identify an available academic job in my area and in my country and bring it to my attention (for more info see here).

Thus, I ask the following question as a potential recruiter or as a member of my department who is keen to see the hiring of good applicants.

What was the experience of anyone who has used ResearchGate to recruit for an academic position?
Did you get many people applying because they saw the position through ResearchGate?
How do you think this medium of academic job advertising compares to other options? Do you think it was value for money?

Some mathematicians I know (me included) appear in Research Gate. Many many others don't. As such, in the areas I'm related to, RG is not a significant source of information. It might be significant with respect to a single person who worked on her/his profile, but not representative of the market. When I click on "related researchers" on RG, the omissions in the list are way more significant than the inclusions.

More specifically to your question, I didn't know that RG had any relation with recruitment. We wouldn't use it because it is not obvious that our target audience is well represented in it.


Should I submit a revised version of my paper before hearing back about the first version? I submitted a paper to a decent mathematical journal more than six months ago. Later, after communicating with several people, I have come to find the notation that I used in the paper very confusing, and thus fear that people may have serious difficulty in understanding my work.

I have since revised my paper by eliminating some notations and adding more examples and explanations. I think the revised version is much better than the previous one, even though there are no changes affecting the results of the paper, and I haven't found anything wrong in the proof.

I am worried that the referees will be annoyed by the notation that I previously used, and thus lose interest in my paper. So, I am considering submitting the revised paper to the editor to help the referees better understand my work. But some people say the referees would be unhappy to see the revision if they do not ask me to submit one.

Two weeks ago, I got a reply from the editor saying the paper is still under review, but he did not say when the review would finish, saying something like "it is difficult to put excessive pressure on the reviewers." So, I guess the review may still require some time to finish.

Should I submit the revision or not?

You should not submit your revised version at this time. If it had been just a day or two since you submitted, it would be a different matter. However, more than six months later, it is quite likely that the reviewers will be angry to receive a new version of the paper, particularly since you have made a great deal of changes. This will be even more so if they are a substantial portion of the way through the review process. (It is also unfair to the reviewers and editors if the author can keep changing and revising the paper while it is under review.)

Your best bet will be to wait until the reviews have been returned, and use your revised version of the paper to "jump-start" the revision process.


How should I compare my algorithm to others when their code is not available? In computer science, we usually implement our work into algorithms and codes. So in order to compare our work to others, we also need to implement their approaches as well.

But the problem is that usually there are recently published works in each area which have used complicated mathematical methods and claimed to beat other previous methods. But some of them are difficult to implement by just reading the papers; or they have not mentioned all the necessary details in the paper for a precise implementation of their work and neither have they make their code available.

How should I compare my work to these most recent algorithms for which the code is not available?

Asking the authors for the code is of course always an option, but from my personal experience this almost never works (there is a reason why they did not put it online in first place).

I don't know which area in computer science you are from but normally there is some quantitative measure to determine which method is better and those measures are somehow in the paper. Those can be things like run time or precision-recall curves on certain data sets.

If you want to compare on the same dataset, you can ask the authors for the numbers / plots themselves and then plot your own curves together with them.

If you want to compare on a different data set, you can ask the authors to run the code for you. In my experience, this works more often because many code is not published because its messy and needs a lot of parameter tuning - so it is unlikely someone else will produce good results with it.

If you have Bachelor/Master students to supervise, you can give the implementation as a project to them (although you need to give them enough time to do it).

In my personal opinion, it is not worth the effort to implement a method which is not described in enough detail anywhere. It will probably cost you an unreasonable amount of time without even reproducing the quality shown in the paper (for various reasons).


How to edit citation style in CSL? or What citation style is this? What Style is this?

I'm trying to work on a bibliography for a paper that has to conform to an unspecified citation style. It's basically the CEEA2016 style:

I saw this great link when googling which seems awesome [CLS]. The problem is that the closest I could get was IEEE with URL which is close in many respects one of the major issues is that the citation style I need uses full names and the IEEE style uses Initials and Last names (Sarah Jane vs S. Jane). Is there a style that is closer to what I'm looking for?

How do I make this style?

Alternatively is there any way to edit the IEEE with URL style to give me full names? I've tried listening to webinars and none of them seem to get into that in my scrubbing and I've even found this primer which seemed to hint towards it but then completely dropped the topic of author names in favor of authorship dates (presumably because it's a heading for citation not bibliography as I would eventually figure out).

I was able to find part of the answer
Out of Editor
Here are lines 81-96 or the original IEEE with URL csl file. I was unable to find out how to do it in the visual editor but I was digging around in the XML file itself and saw this:
  <macro name="author">
    <names variable="author">
      <name initialize-with=". " delimiter=", " and="text"/>
      <label form="short" prefix=", " text-case="capitalize-first"/>
      <substitute>
        <names variable="editor"/>
        <names variable="translator"/>
      </substitute>
    </names>
  </macro>
  <macro name="editor">
    <names variable="editor">
      <name initialize-with=". " delimiter=", " and="text"/>
      <label form="short" prefix=", " text-case="capitalize-first"/>
    </names>
  </macro>

removing the initialize-with=". " seems to have given me full names. After this it looks like the only aspects I would like to change is adding URL at the end. Workable for now but I would like to know how to edit the CSL file as it would be enormously helpful and faster than what I'm going to have to do with REGEX.
In Editor
Knowing what I was looking for and knowing the way programmers like to think I was able to find a similar setting in the visual editor

Bibliography > Layout > author (macro) > Names > Name
In the name section below is the "Initialize with" option.


How should I cite a publication where the author(s) are anonymous (but the organization is not)? I'd like to cite the following articles from "Scientific Data" (a journal from the Nature Publishing Group), but no authors are mentioned (as far as I can tell):

http://dx.doi.org/10.1038/sdata.2015.4
http://dx.doi.org/10.1038/sdata.2014.10

However, it's likely that it was written by one (or more) of Nature's editors.  If, for example, I am using the BibTeX formatting system, how should I describe the author of the article?  For example:

1. author={Nature}
2. author={Nature Publishing Group}
3. author={anonymous}
4. author={}

Or should I leave it blank (option 4)?

It probably depends on the citation style you have to use.
The Modern Language Association style (MLA) states

An Editorial & Letter to the Editor
Cite as you would any article in a periodical, but include the designators "Editorial" or "Letter" to identify the type of work it is.
"Of Mines and Men." Editorial. Wall Street Journal east. ed. 24 Oct. 2003: A14. Print.

But the American Psychological Association style (APA) just substitutes the title for the author. See APA blog.

“No Author”: For Sure
In some cases, there truly is no way to pin down who the author is. We treat this as “no author.” In reference citations, we handle this by moving the content’s title into the author position (with no quotation marks around it). This most commonly occurs for wiki entries, dictionary entries, and unattributed website content. In the in-text citation, the title (put inside double quotation marks) likewise takes the place of the author’s name.


How can I minimize the damage of my PhD advisor's bad recommendation when applying for industry jobs? I did not get along well with my former PhD advisor. I was able to defend and graduate; however, I have learned that my advisor was giving bad recommendation letters. No wonder why all of my postdoctoral applications were unsuccessful even though I have good academic standing. Since we had several intense arguments in the past, I can conclude with confidence that any reference from my advisor would be damaging.
I have decided to go to industry (non-research) not just because of this problem but also because of poor job prospects in academia. Now, I am wondering how I can minimize the damage. I do not know how references work in industry, but I can certainly exclude my advisor in any list throughout a recruitment process. My PhD advisor also has several connections in HR. This can also be damaging if a company background-checks through the university HR department.

You are worried to much.

My PhD advisor also has several connections in HR. This can also be
damaging if a company background-checks through the university HR
department.

First, HR is not allowed to say anything bad about you with no clear evidence (for fear of being sued). They will just give minimal information, and that's it.
Second, background check is often done by a third-party, who is only interested in ticking all the boxes that you declared. They are not interested in hearing some random stories.

I do not know how references work in industry, but I can certainly
exclude my advisor in any list throughout a recruitment process.

For non-research positions, nobody care about references.


What proportion of course material mastery should we consider is "passing?" What proportion of course material mastery should we consider is "passing?"

In the US a typical grading rubric is
A = 90%-100%
B = 80%-89%
C = 70%-79%
D = 60%-69%
F = below 59%

As a professor I often curve the numerical range of grades in my course, and depending on the class, the raw score for a passing grade might end up being even lower than 50%. My question is, at what point does this stop?

A professor could decide that mastery of only 15% of the course material is "passing" because a curve can make 15% into any number. If the professor writes and grades the test he or she could also just decide to only teach and test over 15% of the actual syllabus. In each case students are happy, administrators are happy, etc. because of the "nice grade distribution." But it seems a bit disingenuous to say that a student who learned only 15% of the course material actually passed.

I've heard that accreditation boards have various requirements for a university to maintain its accreditation. For instance, students have to pass enough courses or their major. But is there any accountability for the students to actually learn a minimum amount of material? It seems that everyone in a university could agree that the only requirement to pass a class and graduate is that the student pays tuition. Obviously this is would be big disservice to society.  But what incentives do professors have (other than moral ones) not just teach less, and pass more students?

TL;DR: As much as a student would need to know in order to succeed in their career.

I think part of this answer will be subjective - does a student even need to master course material to pass, or do they need to be familiar enough with it to know how to re-learn it later in their career?  I come from a STEM background - I know how to do calculus, but if you asked me to come up with a Taylor polynomial right now off the top of my head, I'd give you a blank stare.

In my opinion, the goal of any class is to teach familiarity with the subject at hand.  No student will ever use 100% of what is taught in a given class - their career will dictate what they need to know.  As they spend more and more time working in a particular field, the knowledge that is important will stay with them, and the knowledge that isn't important will be set aside - not entirely forgotten, but not readily accessible without review.  The point is - they still know how to re-learn the material; they just don't know it off the top of their head.

With that in mind, I argue that the proportion of course material mastery that we should consider as "passing" is however much is needed to ensure that a student could, given a reasonable amount of preparation, re-learn the material at any point later in their career.  That amount will vary from class to class, and it's worth remembering that some skills will carry over and be reinforced from class to class.  To my mind, this means that fundamental skills - calculus, introductory classes, writing courses - need to be held to a higher standard.

As for incentives for professors - there's a variety.  For one, if you want to work at a high-caliber institution, you're going to want high-caliber students.  This means pushing them to learn and master more of the material than perhaps a professor at a not-so-high-caliber institution might care.  For another, there's an element of peer pressure involved: if I teach my students poorly, and don't require them to learn enough of the material, then my peers will have to pick up the slack in later courses.  That reflects poorly on my teaching, and it means that I may have to do the same thing with these students in later courses that I teach.

So what proportion of course material mastery should we consider is "passing?"  Whatever is necessary for a student to (1) be able to relearn the material in a reasonable amount of time and (2) be able to retain the core concepts for use in later courses.


I want to gain expertise in a specialized topic but not necessarily go on to research career, is a PhD the way to do this? If I simply want to gain expertise in a very specialised area of scientific research that is in its infancy, and not necessarily go on to do further research, is a PhD the way to go?

Is a PhD solely a door to a career of research?

There is currently little known about the phenomenon I'm interested in and even less research, so there is no explicit education in the area.

Whether a Ph.D. is good or bad for your career depends on a lot of things, like your country, your subject area, and your non-academical abilities and interests. In science and engineering a Ph.D. can open up the path to research and development, and any Ph.D. can be helpful to instill trust in clients, e.g. as a lawyer or broker. On the other hand doing a Ph.D. can be seen as procrastinating, i.e. people believe that you rather stay in academia then get a "real job". This is probably a problem in parts of humanities, or if your previous education or your Ph.D. took significantly more time then necessary. On the other other hand this won"t be a problem if your future employee is related to your studies, e.g. when working for a publishing company.

The fact that you are not sure whether you want to stay in academia is not important, since doing a Ph.D. serves to find out whether you actually like research or not. So succesfully doing a Ph.D. and then leaving, even if a Postdoc position is on offer is quite common and nothing to be frowned upon.


Are all master degrees fully funded for North American universities? For whatever reason I had the misconception that graduate study is fully self funded except for some opportunities for scholarship or, in extraordinary circumstances, a full ride scholarship. So you can imagine how surprised I was to find out that certain amount of money is automatically given on an annual basis for graduate studies.

Is this true through out North American universities? This sounds like a wonderful opportunity wonder why not more people go on graduate school.

Most master's degrees are not fully funded (or even funded at all) in the United States. Funding varies by of study field. Some fields, such as business, will rarely offer funding, while others are more likely to.

Perhaps you have been looking at PhD programs in math and science - these do tend to offer funding. But that is the exception, rather than the general rule.  At the master's level, funding is more rare even in these fields.


Convincing professors to help with the founding of new university Background

I'm doing some work for a new online-only university that is being founded, based in the US and offering degrees up to doctorate in courses like history, philosophy and literature. It's heavily research-based and doesn't allow credit transfer.

One of the great things about this university is that it will offer scholarships to people in developing countries allowing them to complete a degree at a US university for as little as $100. The university is not designed to make money, but only to keep itself going. (This does not mean it is non-profit; in fact most non-profits are designed to make as much money as possible, they just don't have shareholders.)

We need academics/professors to volunteer to advise and help us get started, especially during the current period where the application for a new university is being considered. We expect them to help by:

associating with the university for the sake of the application, even if only in name;
marking theses, when students reach that stage (though no teaching will be required).

The questions

I've tried emailing professors asking for their help, but it seems no one is interested. I get the impression that online universities don't have much respect from these people and that no one wants to risk their reputation by being involved with something new and different.

What is the best approach to convince established professors to contribute to this project? Would they expect to be paid in return? (A stipend is possible, as well as a title, but no salary.)

There are a number of issues here:

The new university probably isn't accredited (yet?) and is for-profit (at least that's how I interpret "this does not mean it is non-profit").  In principle a for-profit, unaccredited university could be innovative and wonderful, but it will face a lot of prejudice because most such universities are not.
Joining a new venture like this involves putting a lot of trust in the people who are running it.  If they turn out to be crazy or dishonest, then everyone involved will look bad.  It's difficult to reach this level of trust, and almost impossible starting with e-mail from a stranger.
Advising research students takes time and effort.  It's not just a matter of proposing a topic and waiting for the thesis to come in; instead, there's a lot of advising and mentoring.  This is a major commitment, and I wouldn't want to have my name associated with something like this unless I was doing everything necessary to help the students succeed.  Some of your comments (such as "virtually no need of professors until it comes to marking theses" or "we need academics associated with the university for the sake of the application, even if its only in name") sound like I would be setting students up for failure or misleading them as to my level of involvement.
Time is a major limiting factor.  If I had all the time in the world, then I would cheerfully volunteer to help with all sorts of things.  As it is, though, there are a lot of students at my own institution who seek supervision, and working with them in person is more satisfying and productive than supervising someone over the internet.  If I maintain my current level of engagement with students in person, and add internet activities, then what am I going to cut?  It's not enough to make a case that participating in this new university is valuable.  Instead, you have to make the case that it is more valuable than whatever I might be doing instead, such as research or family time.
What you describe comes across as saying professors aren't really necessary except for validating research output and ought to be willing to do that for relatively little money.  This philosophy won't be popular with many professors, who would like to believe they engage in plenty of crucial activities.  If this isn't the impression you would like to convey, then you need to modify your sales pitch.


Citing sources and the "Right to Publicity" (USA) Something that came up the other month, I was asked to sign a declaration that something I'd scribbled, amongst other things, didn't contain the names of any individuals: living, dead or fictional.... without "consent". Which lead me to ask a few questions such as WHY, and how can a fictional individual grant consent to cite a nonexistent work they haven't created. Anyway the WHY is apparently down to "Right to Publicity" statutes in various US states (There's no direct equivalent in the UK).

Anyway I'm still wondering if similar declarations are standard in all US publishing agreements, and whether there really is an assumed grant / waiver, on having something published, for others to cite it?

I don't think I've ever seen any such clause in an academic publishing agreement.

As an example, I and some coauthors recently published a paper in a journal run by the American Mathematical Society (a US organization).  The publishing agreement contained no such stipulation; the closest thing is a clause requiring us to certify that our paper "does not libel anyone, infringe anyone’s copyright, or otherwise violate anyone’s statutory or common law rights."

Indeed our paper mentioned the names of lots of individuals, both living and dead (though none fictional, as far as I know), in the context of citing their work.  We never asked their consent and it was never suggested that we should.  It is conceivable that this might violate the "statutory or common law rights" of those individuals, if there really are laws such as you suggest, but I've never heard a suggestion that merely mentioning people by name was likely to pose actual legal problems.

If I did see a clause like the one you mention, I'd probably do one of the following:

If I were feeling lazy, I'd just sign it even though it's not actually true, and assume that no real trouble will result.
If I were feeling conscientious, I'd tell the publisher that I can't sign the agreement as it stands because my paper does mention people by name, and it's not feasible to ask their consent.  (I could add something about this being an undue restriction on academic freedom, etc.)  If they insisted, I'd withdraw my paper and look for a publisher with more reasonable lawyers.


Applying for a different PhD, should I say I am already in one? I am considering on applying for a different PhD position in a different university and even different country, but I don't know if I should mention I am already in one, and I'm planning to leave it, or just address that as a research assistant position, what should I do?

When applying for a job, be honest. Just assume that people will find out eventually, because most of the time they will. Say you got accepted, and your new advisor happens to talk to your old advisor on a conference. Now (s)he has the impression that you were dishonest. That is bad.


Does your previous university’s reputation matter when applying for a PhD? I have been applying to PhD programs for the past 2+ years and keep getting rejected. I have pretty good degrees that I worked hard for from good universities (not the top unis).

For the past year I’ve been doing everything I could think of to improve my CV; working for free as a research assistant at a research institute, publishing, attending seminars and conferences, etc.

I always thought that all applicants were treated equally and were judged only by their grades, personal statement and CV. However, I just got my 15th rejection letter, and the university was “kind” enough to tell me that I was rejected because I didn’t meet their entry requirements, specifically, that the universities where I did my Bsc and MSc don’t have a good enough reputation for my application to be considered.

I have been told by academics in the past that potential PhD candidates aren’t judged using this criterion. So my question is, are Phd applications one of those things where people are told that everyone has an equal opportunity while the reality is wildly different? Because I would like to know if I’m wasting my time applying and putting myself through all this stress unnecessarily.

I always thought that all applicants were treated equally and were judged only by their grades, personal statement and CV.

Applicants from different universities are not treated equally (at least not by my department's selection committee).

Your grades are looked at as a baseline (to filter out obvious rejections or single out interesting cases), and then a discussion goes on about the rest of it (CV, statements, references and research experience). You are missing two key parts (which you refer to in your comments but not in the question body): reference letters, and publication record. You say that you have read your reference letters: have you read all of them? It could be that you are experiencing selection bias - the referees who are comfortable with you reading their letters are ones who generally like you. In addition, nowadays top schools (in computer science at least) may reject your application if you haven't had at least one decent publication.

  I have been told by academics in the past that potential PhD candidates aren’t judged using this criterion.

This must have been a misunderstanding.

The institution the conferred your degree absolutely matters. There is a huge difference between how a top 5% student from a top university and one who hails from a less renowned university is perceived.

This cuts both ways - good universities may produce inadequate graduates, and less reputable ones can produce excellent students. The institution is just a signal of your likelihood to succeed in your PhD.


Advice for writing Lab Manuals for undergraduate students I was wondering how lab manuals for freshmen or junior year engineering students are created. I am currently working on documenting a lab manual for a project. Although, I am fairly well-versed with the subject matter and have written the code for the project myself during my undergraduation, I am required to write it from the point-of-view of a student.

It would be helpful if I can divide the project into session-based labs and provide step-by-step remote mentoring of students.

The manual should emphasize creative learning but also not encourage spoon feeding. I need some templates/examples to get started with.

Having written up a few such sets of course lab notes, the best advice I can give is to offer an "idiot-proof" introduction so that anyone can get the first lab started. From there, I tend to curve the difficulty of the tasks, such that the first task should be trivial, yet the last task of the session is more challenging. I then tend to suggest a couple of improvements or suggestions for the curious to consider or try out.

For subsequent labs, I presume knowledge from previous sessions is retained, and consider it a prerequisite. I give progressively less guidance on using tools or techniques for repetitive tasks through the different sessions.

To give an example, if it was a programming exercise, the first set of notes will be thorough and tested on an unfamiliar colleague, to ensure they can run the software needed, and get a "hello world" to run. This includes showing which buttons to press, and how to save and load work. While experienced students may skip this part, that's their choice... I find it worthwhile to write this, even if just to give the TA something to point students towards if they have problems.

As a student works through a given session in the notes, I make the tasks gradually reduce the direction given. So the first exercise could be to ask the user for their name and echo it back - I'd tell them to use the input command, then the print command. By the end of that session, the recap exercise night be to write a program to ask for 2 numbers and multiple them, returning the result. There wouldn't be any more guidance than that. For "optional extra ideas", I might suggest to keep asking for input until the user provides none, or something similar as a little teaser requiring some reading ahead and independent research.

The next session would not go into the same detail on getting set up, and would begin from a higher difficulty level (wouldn't step the student through which function to use, in the case of my trivial example above).

By the final session, there would be limited guidance and much more explanation of concepts or suggestion of references to look at. I favour leading people to good sources and suggesting they read it, rather than trying to reinvent the wheel, but this might not work in all cases.

In particular, physical laboratory activities with chemicals or equipment may not work with this model, as you may have obligations to detail all procedures for health and safety purposes. In that case, I would leave the analysis and explanation to the students, giving progressively less help in finding the right places to read about the expected results etc.

Ultimately this depends on the discipline and the expectations of the principal academic teaching the class. I do find students like the rising difficulty, as there's both sufficient help to get started, bus also a good sense of accomplishment to finish the exercises and have worked it all out.