Is Computational Social Science better as a degree or as a field of research for various disciplines to collaborate in? I'd like to go to grad school, but I've been dragging my feet on it for so long (I'm three years out of college, with a Bachelors in Computer Science) because the sound of traditional CS research sounds uninteresting to me. However, I recently found out about the field of Computational Social Science, which asks are questions that I'd enjoy doing research on (see examples here: https://as.cornell.edu/block/computational-social-sciences).

Basically, I'm motivated by social and people problems rather than technology problems. I'd like to be someone who has a strong grasp of the technical and can use it to answer questions about the state of the world. I'm also motivated by having an audience (sounds shallow, but I might as well admit it), i.e.: my work matters to people and spurs discussion.

I even realized that the undergraduate research thesis I wrote was technically in CSS. I was training language models and then using them to predict societal gender disparities (e.g.: can you tell from the English language model whether the word "tennis" is more male or female? And using that, can you predict how many male vs. female tennis players went to the Olympics?)

Since doing my research on CSS programs, it seems like it's a field of specialization rather than an actual degree (so far I think only George Mason University offers it as an actual degree). My question is, which of these is better:

Do a Computer Science PhD and then specialize in CSS.
Do a PhD in some other related field to CSS (e.g.: Data Science, Informatics, Economics, Sociology, other ideas?) and then specialize in CSS.
Do a PhD in CSS directly, even though this is uncommon.

I'll add that along with finding something that I'm interested in, I do have long-term considerations like which degree gives me versatility, respect and income.

I have very little guidance right now, so any words of wisdom could help. Thank you!

My background, in case that helps:

I work at a large tech company, and I've done both mobile product engineering as well as some research in deep learning (my current role). I transitioned to the research team to see whether I'd like to dedicate five years of my life to those kind of problems. Unfortunately, reading about neural networks/adversarial attacks/bayesian neural nets etc etc is not my cup of tea, nor where I think I excel.
Some of my strengths (according to the last three years in industry): communication skills, design thinking, looking at macro patterns, executing and driving projects, mentorship.

This is an interesting question. I was just hired to an assistant professor position for which the desired specialty was computational social science, so I may have some relevant perspective. My field is communication, a field which sometimes describes itself as part of the humanities but is better described as a social science with a strong professional orientation as well.

First, I should note that your question does not make it clear what kind of career you would like to pursue after you get your PhD (if you choose to get one). I will answer this question as if you prefer an academic career (i.e., you would like to be a professor).

With this in mind, I should note that professors in computer science departments earn much more money than in the social sciences. According to this, the median assistant professor in CS earns $107,000. Assistant professors in the social sciences appear to earn a median of $63,000 (but do note these are two separate sources). Based on what I know about the field of communication, I'd be surprised if there are any newly-hired assistant professors making $100,000, at least outside of a few places like the state of California where such a salary doesn't go nearly as far.

That being said, you should of course not study CS or in any other discipline if you do not like it. The ultimate reward of a PhD is, in my and many others' opinions, not worth suffering for 4-7 years to get the degree. If you like what you're studying, and find the typically low pay such students get tolerable, then it can be quite rewarding.

I think most quantitative social science fields have growing interest in computational social science. In communication, there certainly is, thanks in part to the existence of so much widely available data that constitutes communication (tweets, news archives, etc.). Training in this area would require initiative on the part of the student — few graduate programs have a formal program available. The best thing to do would be to find programs with more than one computational social scientists on their faculty (more than one makes it more likely you have some "in-house" courses and protects you from having an important faculty member leave you with no adviser).

One thing you may enjoy is that your background in computer science could give you a significant advantage over your social science peers in terms of technical skill. Most computational social scientists in the field are like me, people who self-trained their computational skills in an ad hoc way. You will surely have technical skills to learn but you should have a much easier time picking these things up. You will find at many programs that a significant portion of students are at least mildly repulsed by scientific computing — they think highly of those with skills, but see it as too challenging to attempt themselves. Among senior faculty, this attitude is even more prevalent.

Clever students with CS background could bring insights and skills from CS that wouldn't be particularly novel to computer scientists but might be very useful and otherwise unavailable to people in the social sciences. You might also be able to better comprehend new developments in CS while most other social scientists wait for these innovations to be better explained to non-experts (and perhaps wait for a C or some other less accessible implementation to be moved to Python/R or whatever).

Of course, the challenge in terms of curriculum will be a lack of background in the subject matter. I can't speak for political science, for instance, but my field regularly recruits people with no background in the subject area to its graduate programs. I only had a humanities background paired with some self-study in preparation for grad school when I started my PhD. I like to think that you do not have to be a genius or extensively trained to become a competent social scientist over the course of a PhD program as long as you are willing to work hard, know how to write/communicate, and are comfortable with abstract and empathetic thinking about the social world.

Just to boost my own field for a moment, here's why you might consider a degree in communication:

Although communication is not a high-paying field as far as professors are concerned, it has a much healthier academic job market than virtually any other humanities or social science field. One easy metric to consider is this: There are more faculty job openings each year than there are new PhDs. I expect faculty hiring to continue to increase because the discipline is very popular among undergraduates (for good reason).
If you have broad interest in social science and want the freedom to study topics that are interesting to you and other people might find interesting too, I think you may find a home in communication. The example you gave about examining gender bias through language is certainly a thing communication scientists do (but linguists and surely some others do as well). I was attracted to the field in part because so many different subjects can fall under the broad umbrella of communication — politics, social relationships, child development, information technology, public health, and many more things.
The field is notoriously open to outside perspectives, particularly when it comes to methodology. This is partly why it has been so accepting of computational social science and why so many job ads explicitly target these skills. The field isn't terribly tool-oriented; there aren't constant battles over the best methods of analysis like are common in economics and political science. So if you want to use the toolbox of computer science but don't want your days to be occupied with minutiae of algorithms, communication is a discipline that's quite open to this. I don't want to say the field doesn't care about rigor — in fact a journal was just founded to help develop and refine computational methods — but there will always be a demand that your method not just be sound, but also that it should teach us something about the social world.

Other fields of interest: information science is one you didn't mention but they are trying to develop these skills and want to become the home of data science on college campuses. Sociology is good, especially if you want to do social network analysis (the statistical methods, not necessarily studying Facebook, etc.), but a very difficult job market. Economics pays well but it's a difficult job market, hard to get into without prior economics training, and economists are not big fans of non-econometric methods (speaking very broadly). Based on what I know, if there are data science PhD programs I wouldn't bother with them and would rather prefer applied statistics or sticking to a social science field.


Why does a mathematics department want student evaluations of a famous professor? If a professor is very famous for his research and belongs to the most prestigious academies of science for his lifetime work, I find it unusual that the math department would ask us to evaluate him.  We did so anyway and submitted the evaluations to the director of academic affairs.

Is this typically done at most American universities, irrespective of a professor's age, status or fame?  I would think that after a certain point in a professor's career, student evaluations aren't necessary.

Is it sort of a sanity check?  He was 85 years old.  Is it done to try and find reasons to force retirement of professors?

Being a good teacher and being a good researcher are distinct skills. If someone has a job that requires both skills, they should be being evaluated on both.


How to read/react to students' evaluation? For my first course on CS topic (first course on the topic and not the first overall), I used the university evaluation system to ask students about their feedback.

In addition to responding to questions by giving rates, the students were also asked to specify what they liked and what they didn't like. There are some comments that are obviously wrong but among which, there are comments that the students believe are true.

One common comment is that the slides contain many formulas and they claimed that most of them are not necessary because they didn't understand the lectures. In contrast, they could understand the topic from youtube videos without all these formulas.

I wanted to teach the topic from the right perspective of master university level. but it seems that the students prefer animated lectures, which are useful to understand the overall idea but not the core of the topic, especially because math/algebra is important in this course.

I am wondering whether I should satisfy the students' opinion or I should keep the current way which I find more useful to reach deep understanding.

I spent many years of my professional life discussing how to present complicated ideas. The first rule that I developed was: "Any comment, however stupid seeming, should be taken seriously". In the OP's context that means try to understand what the student comments are getting at, even if the students who are commenting cannot explain it. Something you said evoked that comment. If you don't like that comment say something differently next time.

The second rule is: disregard any specific suggestion for how you might say it differently. Only you know what you want to say. Your students do not.


Is there any good reason to write "it is easy to see"? Many academic papers, particularly in mathematics and similar fields, use the phrase "it is easy to see that..." (e.g. in a mathematical proof). I never understood why this sentence is used. Such a sentence is inaccurate at best, since it is not easy for everyone to see; maybe it is easy for the author or some of the readers, but there are certainly readers to whom it is not easy.
Authors often try to shorten their paper as much as possible, so it is not clear why they would lengthen their paper by an inaccurate sentence.

Is there any good reason for an author to use this phrase?

Mathematical papers, especially, and many others, are not written for the complete novice with no understanding of the field. One tries to tailor the explanation of a new concept to the general level of understanding of the audience and tries to avoid being overly pedantic giving every detail and argument back to Euclid.

College lecturers often use such phrases, knowing the level that their students should have attained and, thus, permitting the lecture to flow more smoothly and be less boring.

But writers do the same thing, envisioning the reader of the paper, or perhaps just the reviewers. If I say such a thing and the reviewer calls me on it, then I know I have to say more. But I trust that the reviewer can validly stand in place of the audience and will be able to easily fill such gaps.

When such a phrase is used (we can conclude X) it implies that X flows from the previous statement(s) and isn't just an unsupported statement inserted into the flow. It indicates a hopefully simple, but unstated, argument.

The alternative of including the complete argument is longer, more pedantic, more boring papers.

The other alternative of starting every sentence with "Therefore,..." is also stilted and, eventually, boring. Some variation of phrasing makes the reading more pleasant. Writers, in general, like to have a repertoire of, more or less, equivalent phrases to help the flow.

On the other hand, it has happened that the statement is used incorrectly when it takes a lot of argument and deep insight to go from point A to point B. Sometimes the author just doesn't notice the width of the gap. But, for the most part, it seems to work out.


Plagiarism of my work My classmate (now a lecturer at Imo State University, Owerri, Nigeria) published my entire masters thesis’ work in an internal journal (IOSR Journal of Computer Engineering (IOSR-JCE)) without my knowledge and didn’t reference me in any way. How do I go about reporting this for the work to be retracted?

I handled three cases of Plagiarism so far. The fastest way is to write an email to editor-in-chief of the journal and provide some documents showing that this is your work. For example, you can sent your master thesis and specify the similar parts. For me, in all cases, the editor-in-chief quickly removed the paper because they are responsible for the reputation of the journal. In case this doesn't work, then you can ask your university to handle this, but the procedure would be much longer.


Are delays and 'being stuck' normal in PhDs, and how much should I work to compensate? I'm doing a PhD in Computer Science in France (completed 10 months out of 3 years), and I am annoyed at how slow I am to produce results.

Long story short, I have explored various potential solutions to a certain problem in Computer Vision using Deep Learning - defining the problem properly was by itself very difficult - meeting various dead-ends and delays like buggy open source code and issues to reproduce results from existing papers.

I have produced small-ish results, but I haven't got enough for a quality paper yet (e.g. CVPR). I should be close, but then I've been convinced of that for a couple months.

I work full-time on my PhD (8h-17h), with occasional 1-2h overtime. I would say I am usually quite productive although there are days it would have been more useful to stay at home sleeping. I rarely work during week-ends: it is way more efficient to test / develop the algorithms in the lab, and I am just tired. The exception is when I have something to write, which is not the case right now.

My supervisors are somewhat disappointed. On the one hand, I feel like I could  do more, like by working at home or something. It is true that in the beginning of the PhD I wasted some time by leaving work earlier at 4pm (which I kinda regret) and by exploring algorithms that were useless in hindsight. I also feel guilty if I spend my week-end binge-watching movies or playing games on my PC. On the other hand, I am also usually out of ideas or things to try and may not do something useful anyway.

I am somewhat at a loss, hence my question: how far should I go? Should I always try my hardest all the time, like when I prepared exams for engineering schools (classes préparatoires, where free time is an unknown entity)? The thing is that I just do not know how to completely solve the problem I am researching. It is very different from studying for an exam, where I know precisely what to do. If I had the solution, I'd be happy to write the paper...

I always could do something, like looking for new papers to read or studying deep learning. I also sometimes hear about people working until 2am in other labs and publishing papers after 6 months, which does not help. I do not know what I should do, and afraid of regretting my decision either way :|

What you describe seems pretty normal, except for the disappointed supervisors. But maybe your work habits are inefficient. It seems like you may be stressing time in the seat too much. If you don't take regular breaks, get enough sleep, and tend to your health, then your mind won't work efficiently. You will get stuck and pounding harder isn't the way to think deeper. Take a break regularly, especially when you get stuck. It doesn't need to be long or elaborate, but a short walk, run, or bike ride, can restore both your body and mind.

Your mind doesn't just work when you try to force it to. It actually works all the time, even when you are sleeping. Sometimes the break is what it takes for your mind to stop focusing on minutia and start to integrate what you have been looking at.

But, if you are really doing research, and not just going through the motions, then you can't schedule results. They come when they will.

“If we knew what it was we were doing, it would not be called research, would it?” ~~Albert Einstein

Another trick is to talk to people about what you are doing. They need to have some knowledge, but if you just try to explain it you will, perhaps, come to a better understanding yourself. Some people even "talk" to a Rubber Ducky that they keep on their desk. Tell it to the Duck. But people can give you feedback.

The "dead ends" you explored may also actually be valuable, later if not now. They might actually do nothing more than provide a break from trying to push forward. And those breaks are essential.

If you do too many push-ups your muscles get saturated with lactic acid (I think I got that right) and weaken. Something similar happens with your brain. Work hard, but take breaks. For me, random breaks, rather than a schedule, works best. When I'm not being productive, do something else for a while.

But if your breaks take you away from your desk as they should, you can also carry a few note cards, including blank ones. You can use these to remind yourself of partially formed ideas and capture new ones if they occur during exercise. Don't force yourself to work on a break, but have them ready to capture any serendipitous thoughts.


Should amount of citation/references be taken into account when grading an assignment? As I don't like looking up the internet and read all the materials or references and all that when doing assignment, thus I try to pay full attention during lectures and/or tutorials. Therefore, my assignments are often long and with minimal to no plagiarism detection rate as all the contents are written by myself from my own knowledge - not paraphrasing. Perhaps I'm not until the stage where I need to often look around for more materials I guess? I'm currently still a year 2 undergraduate.
There's sometime where I have to lookup on the internet so adding references is unavoidable in this case. But in general, I ended up having my assignment to contain only a small amount of references, maybe 3 to 5. My plagiarism detection result is usually just around 0% to 1%. Or even in most cases, I just refer to my lecture notes and that's it.
But recently as I enter year 2, this started to give me problems. I just ended my first semester and was given lower than usual marks for my assignment, with the lecturer commented that the amount of references and/or citation is insufficient, although the plagiarism checker finds no match. Hence, marks are being deducted.
Therefore, my question is:

Should the amount of references/citation be taken into account when grading?
Let's say, this idea or knowledge is on my mind, or maybe I learned it from lecture, and it is sufficient for me to complete my assignment, without the need to actually refer back or anything. Should I take the extra effort to find out the related sources and reference or cite them?
Or, is my way of doing assignments actually wrong and improper? Should finding external sources of information as references when doing assignment is actually a must?

I also need to clarify that all my assignments are getting reasonably good grades.
Please do correct me if I got any idea and/or concept wrong.

Plagiarism is not about whether your work passes some % threshold on software that detects plagiarism.
Plagiarism is the representation of words and knowledge/ideas as your own. When you learn from a source, you need to cite that source when you write about it.
Over time, some knowledge becomes so commonly known that it doesn't need to be cited any more in most cases; for example, Newton's laws. Lecture content might sometimes fall into this category and sometimes not, you can ask your instructor for guidance on their expectations. However, most of the content in a paper you write at a college level will come from a source you need to cite, unless it's work you've physically done or your own unsupported opinion.


Is it acceptable asking to join a researcher in co-organizing their conference session? I have a friend at another university that I met at a conference a couple years ago. Since then, we usually make an effort to attend each other's sessions, grab coffee, etc. Last year he organized a session at our flagship conference, and I think he's organized a similar session several times before. I think it would be fun to co-organize a session together, but I would assume he's doing his usual session. Would it be rude for me to ask if he would like help organizing the session (i.e., adding me as a co-organizer)? Or is this the academic equivalent of asking, "Can I invite myself over to your house to play video games since I don't have a N64?"

For context, we are both at universities in the USA. He is an Egyptian-born Canadian citizen, and I am an American. He is a few years senior to me; he is in a semi-permanent research position, and I am a 4th PhD student. For the record, I don't think he would view this as rude because he is a genuinely friendly guy, and I think he could easily tell me "no." But I am more curious about the general etiquette of these things.

I would not directly broach the subject. If you want to judge interest, the kinds of questions I'd ask are:

  What do you have to do to organize a session?

If your friend mentions needing a co-chair, you could ask your friend if he has someone in mind.

But do not ask directly to be a co-chair for someone else's session. What you might instead want to ask is: "would you like to be co-chairs for a future session sometime?"


Bad reference from PhD supervisor My PhD supervisor and I didn't really see eye-to-eye on a lot of thing but I had thought we got along well anyways. I have graduated and have decided that academia isn't for me and I want to go into the private sector. I am having a very hard time finding a job, and I am not being picky. I am applying to industry scientist jobs and also for positions like sales reps or administrative roles. The truth is I am desperate.

Although I don't get many interviews one of the places I got far along with checked my references and said my PhD supervisor said she couldn't recommend me for the position, as I had problems with communications skills. It may be true that I am awkward, but I don't think that I am that bad. I also have my MSc supervisor as a reference and another professor in my department that worked on a group project. Now I have asked my department head to be a reference as he was also on my committee. Each of these people seemed happy to be a reference but so did my supervisor.

Is it a red flag that I don't list my supervisor? I can try to talk to her but I don't know what to say. I feel like my life is falling apart, I have to get my parent's help to pay rent and I'm worried my girlfriend will break up with me as it has been causing a lot of stress.

What can I do?

Given what you describe, I think you better not include your supervisor. Her recommendation will be the most dominant because she knows you the best. Given that in the best case you will get a mediocre recommendation, and in the worst case even a bad one, it is not worth it to include her.

Do not include her, but be prepared to explain why you do not include her. This explanation should be convincing, but not too damaging for you. For example, if you just say that you had conflicts with her all the time, your potential employee might conclude that you are a conflicting person.


How to become a visiting student in a UK University I'm about to finish my BSc in Computer Science, and in September I'll start an MSc in UK.

What if I don't want to waste my time during the August and September months? Would it be feasible to ask a university for a short period as a visiting student in their department?

What are the steps to follow?

There's no simple formula, and each university will have its own visiting student schemes. This being said, there are usually classic methods for visiting a UK university:

Enrolling in a degree

Obviously you can apply to be enrolled in a degree, pay your tuition fees and study for the degree in the UK. You can usually get a Visa via this mechanism (except for London Metropolitan University which is no longer allowed to issue visas by the UK Border Agency).

Duration: 1 to 4 years.
Cost: a lot. ~£4,000 to £10,000 for EU students, ~£20,000 for non-EU students.
Requirements: apply to target uni. Proof of academic competence required, usually good grades and a BSc/BA for a MSc/MA position.

Applying for an semester abroad as an Erasmus student

You can use the Erasmus Programme to visit a EU university as a EU student. Some non-EU universities located in Europe may also be eligible.

Duration: usually 3 to 6 months.
Cost: free, paid by your university and the EU's Erasmus mobility budget.
Limited scholarships available, usually ~€400 / month
Requirements: must apply to your uni of choice, selection process varies. Your uni often must have a prior agreement with the target uni.

Applying as an exchange student

You can apply outside the Erasmus scheme if you uni has an exchange agreement with the target UK uni.

Duration: usually 3 to 6 months.
Cost: depends on agreement, can be free or can requirement payment of tuition fees.
Requirements: depends on agreement.

Applying as a visiting research student.

You can get opportunities to visit foreign unis as part of your PhD, a bit like an internship. This is fairly common across the world.

Duration: 3 to 12 months.
Cost: free.
Requirements: must be enrolled in a PhD-level course, must have found a supervisor to welcome you in target uni.

Applying for an internship.

You can also join a uni as part of an internship programme, if a position is available in a research group. This normally does not involve any teaching, or in marginal amounts.

Duration: 2 to 6 months.
Cost: free.
Remuneration: depends on uni, not guaranteed... ~£330 per week in some London universities.
Requirements: there must be an internship position available, and you must be the best available candidate. You must work.

Applying for a volunteering position.

You can also join a uni as part of an internship programme, if a position is available in a research group. This normally does not involve any teaching, or in marginal amounts.

Duration: depends.
Cost: free.
Remuneration: none.
Requirements: there must be a volunteer position available, and the supervisor must agree to take you in. No deliverables required.


Is it OK to ask a professor if they have a postdoc position available? I am a PhD student working in applied probability theory. I have submitted my PhD thesis and started to apply for postdoc positions.

Is it OK to ask a professor whether they have a position available? If so, what should such an e-mail contain?

Yes, it is fine. It never hurts to ask. Some people will ignore you, but some people will reply.


Admitted to plagiarizing (second misconduct), and afraid of expulsion. In need of advice Important note: This was not the first time I was reported for academic misconduct. The first time was when I cheated on an exam for another class. I disclosed how I cheated and accepted the punishment. This time, I told my professor that I didn't intend to plagiarizing but ended up doing it in the end.

During my meeting with my English professor, I told her that I wasn't feeling well at the moment and when I was completing my final assignment.

(Background) Over the weekend, everyone was able to start on our final assignment - travel piece - that was due Wednesday. On Sunday, I had time to travel. Monday, I hit my head, thought it was nothing, but decided to lie down soon after it happened to forget the pain. Slept all the way up to Tuesday afternoon, went to the very last English class and worked on the final assignment in-between naps to get my mind off of the headache. Vomitted a little in the bathroom, had a hard time concentrating and thinking, maybe I over-ate before I left home. While I was working on my essay, I and other classmates were reviewing each other's works and researching on the travel destination we wrote about. In my notes, I mixed up the info I got from articles with my notes. Didn't properly cite all of the info yet, but wrote down general comments on some of the paragraphs saying which websites they came from. After much editing later, my words and words from the articles were mixed up. Yes, I f'ked up terribly. Went home, slept. Wednesday, I went to the medical center after I felt a head bump while sitting in the passenger seat. The doctor said that I had a minor hematoma, and needed to rest for at least two weeks. E-mailed the professor about that.

(Fast-forward) I admitted to plagiarism, and described what happened and why. The professor didn't take notes of my account when she was going to file a report. On top of that, she just emailed me about something that I already told her right after filing the report. Either she wasn't listening or my story seems really bogus. Right now, I'm scared of what my professor wrote on her report because she might not have mentioned anything about my health, and make it seem like I had plagiarism in mind. I might get expelled over this. I have a printed receipt of my doctor's visit. I don't know if submitting that to the academic misconduct council will help prevent expulsion from happening.

Consider asking to meet with your Professor (e.g. during reception hours). At that meeting, or by email if you can't schedule a meeting, ask her for a copy of the report she submitted. Alternatively, ask the disciplinary body if a procedure has been opened involving you, and if it has, ask for a copy of the complaint through there. If your Professor asks what you need it for (which she shouldn't, it's obvious) - tell her that you're anxious and it's important for you to know how your story was reflected to the higher authorities, given that it involves all sorts of circumstances and details.

This may not solve any of your problems but at least you'll know what you're up against better.


When is it appropriate to describe research as "recent"? I want to write: "A recent study ...",

The particular study I want to cite was published two years ago. I don't think that this is very recent in terms of journal appearances. But it is the most recent I could find compared to similar studies, which is what I want to emphasize.

But what are the general semantics of "recent" when referencing sources?

Good question. The semantics of the word "recent", in general, and in academic writing, in particular, is not clearly defined (that is, fuzzy), which makes its practical use quite tricky, as evidenced by your question.

While @vonbrand's answer offers some valuable insights, such as considering the fluidity of a particular scientific field or domain, I would suggest a more practical solution to this problem, as follows. Consider literature that you reference in a particular paper. What is the temporal range of the sources? I think that this aspect could guide you in to where the word "recent" is appropriate and where not so much.

For example, if you cite sources from the current century as well as 1930s, then a paper from 2010 should be considered recent, but not one from 1950. If, on the other hand, your temporal range of references is rather narrow, say, recent 20 years, then you should refer to as "recent" for sources that are from approximately last 4-5 years. You can come up with your own rule of thumb (10-20% of the total range sounds pretty reasonable). The most important aspect would be not the actual value (for the rule of thumb), but rather your consistency in applying it throughout the paper.


Can I pursue Masters in a field different to the one in which I got my Bachelors degree? I will be graduating from BS Aeronautical Engineering in about 6 months. But over the last couple of years, I realized that I'm more passionate about Geopolitics, international relations and diplomacy. So, I'm thinking of changing fields in Masters. I intend to opt a degree in International relations, public policy and economics.

Now, as mentioned in the question, how difficult is changing majors like that? What is the attitude shown by universities toward applicants like me? And how do I go about convincing professors to take me in?

It is not so rare to see people opting a masters programme that is far different from the undergraduate one. So, there is no need to feel out of the crowd. Such people who go after their passion do succeed, but not without the initial struggle to adapt to the new subjects. This would mean you would have to do more homework yourself than others in the same programme.

The masters you choose should depend on the career you are aiming at. If you are highly confident that you will be working in that field then you may choose the field that highly deviate from your undergraduate degree. But be wary of the fact that you might not be able to switch back. This act might belittle your undergraduate degree, so seeking for a job relating to it might have you at a disadvantage in most communities. That is, unless you choose do masters for that degree too.


How to ask good question at the end of lecturer interview I interviewed yesterday for a lecturer position at computer science. At the end of my interview, the Head of School asked me if I have any questions to ask them. This is my first time to interview, and I don't know what to ask, and just said to the HoS that ``I saw your research project on Youtube, and I was very interested in that topic, and is possible to have any future collaborations?'' I did see his research project on Youtube. However, I can feel that the HoS was not very happy. Maybe I screwed it up. Is this a sensitive question? Could anyone give me some suggestions on how to ask good questions? Thank you.

One good question to ask is, "What is required for a new lecturer to succeed here?" and the likes. I've asked this myself and the Head of School was very eager to share with me the answer.

Asking people whether they would collaborate with you seems too early, as you will need to show them that you have something to offer.


What's the difference between 'research topic' and 'research area'? I am writing an essay to apply for a summer research project and is supposed to write about 'general research topic that interests me' and 'area I would like to focus'. I'm kind of confused about these two terms. What's the difference?

For example, if I'm interested in computer science, where should I write it?

p.s. I have asked this question in English Language & Usage site but didn't get answer. So I suppose that these two words may only have difference in academic field?

A research area is what a research topic is placed into, but is much broader than the scope of the topic. For example a research area can be human physiology, computer science (as you mentioned) or even relate to a specific field within these broader terms such as cardiac electrophysiology or machine learning respectively.

A research topic would be a specific question, hypothesis or problem you wish to investigate and answer which is under the scope of your research area. That is to say, my research area is in neuroscience/neurophysiology and my research topic is investigating the mechanisms of neuronal communication, as an example.

You would want to say topics that interest you which relate to a certain problem that you may be aware of, whereas in the research area you would want to outline your inclinations towards a particular field of academia.


How to cope with YouTube and use it as an aid for effective teaching YouTube rules the roost. It is first resource that people refer to when they want to learn something new. After all, who would teach me how to replace a RAM on my laptop or to change the new windshield wiper blade on my old car?

YouTube is an extremely valuable resource. However, things do not work out that well if it is something more complicated like Linear Algebra or NMR spectroscopy.

Frequently, I meet students who have watched all the YouTube lectures even before the semester begins. They are also very judgmental about classroom lectures. I am soliciting help from the community about

How to tell them that watching videos is no substitute for learning. Usually this needs to be conveyed at the start of the course, when they pay no attention to it. By the time they understand it, we are well into the depths of the course and it is too late.
Not watching videos is also not a wise thing to do. There are excellent makers who create excellent animations which I wouldn't be able to do ... actually never! How do I tell this to the students without appearing like abandoning my duties?
The biggest problem is enrolling students. Students (often the brighter ones) believe they have learnt the subject via YouTube well enough to skip the course altogether. How do I convince them that I will really help them study this subject beyond what they can manage via YT? How do I do this without sounding like a pimp? How do I politely tell them that they haven't learnt the subject via YT (or other online resources) at all beyond some mumbo-jumbo? Some of them might actually have learnt the subject to some extent ... How do I convince them of the utility of my course?

Thank you all.

EDIT: In light of objections by Anonymous Physicist, I must add that a succinct summary of my question is : "How to handle YouTube-aware students? 1) At the time of enrollment 2) at the begining of the course and 3) during the course?"

I've just embraced YouTube as part of my teaching. I've not used it to replace lectures or any classes but created my own separate YouTube content that serves a different purpose.

I am a copious consumer of YouTube, so I am perhaps familiar with some of the content there. I find that the viewers want to watch someone solve a problem or do something interesting or difficult but not be "taught" in the traditional sense.

I found that students need was to ask how to solve a problem when I was not around to show them how I might solve that problem. Although we had small group sessions when we could discuss problem solving, these were not really frequent enough for many students. Deferred gratification is a difficult thing for some students who prefer not to wait until the next support session.

To solve this dilemma I created some new unique problems that emulate the class work and create similar challenges without being useful for plagiarism. I then solved these problems as if I was a student and made the same set of blunders, many genuine on my part. I then verbalised how I would solve such an issue, create a working solution, and prepare it for classwork submission.

The idea was, that they could use these as a substitute for me being at their side and talking through a problem solution.

In the main, this has worked out. The episodes are not perfect, and could be improved; but it is path that teacher and class can walk together, and one has to start somewhere. Some students, foolishly just copied the work from the YouTube screen and handed it in as a class solution, when it was even a different problem; but they were the minority. Some students complained that  I did not solve their specific problem in the video, when there was clearly an analogue of a solution therein; but in the majority it was helpful. It was also a clear marketing ploy, in that some just picked the class "because it has YouTube" content!

What I did was additional and optional content. No student was required to use it, and all the information it contained was present elsewhere in written class material. It was just another form of delivery to complement existing media which helped some students.

Give it a try!


How I can efficiently use Google Scholar to find prior research on a topic? For starting a new problem I generally need to look for work already published through Google Scholar. For example, recently I came across an equation, the Pochhammer-Chree equation. When I type this equation name in the Google Scholar tab, a large number of publications on this equations piles up. It is not possible to look for every single publication to check what type of work has already been done on this equation.

Let me elaborate a little more. Suppose I need to check if the Lie symmetry analysis on this equation has been carried out or not. Then I have certain options in advanced search, that to include the words symmetry or symmetry analysis in the title, abstract or in the whole article along with the word Pochhammer-Chree. Here of course the time range can also be given. Unfortunately, even by this type of search I can miss some of the article that have been already published on symmetry analysis of Pochhammer-Chree.

Is my way of search correct? If not, how should I search through the web by not missing a single article on the topic I am looking for?

It is true; there are too many papers out there to even read the abstracts of all of them. That is why many research papers contain phrases like "to the best of our knowledge", etc.

My approach to minimize the risk of missing out publications is as follows: I start with reading review papers. These will sum up the research up to a certain point and will show you what the seminal papers in the field are. Then I look up the latest papers that cite the reviews and/or the seminal papers. This approach works very well with Google Scholar.


Can a bad grade in a class be negated by a good grade in a more advanced class? I am an undergraduate who is expecting a mediocre grade in my optimization class this semester (roughly B-), which is in significant contrast to my near straight A transcript. Unfortunately, I want to do a PhD in machine learning and so I expect this grade to be viewed in a negative light by graduate admissions committees due to the relevance of the material and the aforementioned contrast. But I will take an advanced graduate level machine learning course this coming semester which has the optimization course as a prerequisite. Will a good performance in this  graduate level class negate my mediocre grade in my optimization class? In general, can (and will) good grades in more advanced classes negate bad grades in prerequisite classes in the context of graduate admissions? To what extent? I understand that each admissions committee will view this situation differently. I am looking for a general opinion.

In general, can (and will) good grades in more advanced classes negate bad grades in prerequisite classes in the context of graduate admissions?

Only to a very limited extent. Getting a C (or F) in calculus during Freshman year is likely to be completely ignored if you got straight As after that. Other than in such extreme examples, no, I would not expect to be able to negate past grades. But of course, each grade is only one data point, and additional data points can significantly improve your overall record.

  roughly B-, which is in significant contrast to my near straight A transcript.

So, this is an outlier. Like in any other sort of data analysis, a single outlier in an otherwise homogeneous record is unlikely to have much/any effect. Sure, getting a good grade in the more advanced course could make it even more clear that this outlier was not related to the subject. But it seems like you are already on track to get put in the highest "tier" with respect to GPA, so you may want to consider investing time on the other facets of your application.


Should I prepare a research statement or cover letter for postdoc ads. with general descriptions? I noticed 1-2 advertisements for postdoc positions in which they provided the general description of what they want as publishing and improving the state-of-the-art in a more or less big subfield of Y. The ads. were generally asking for sending the documents without specifying what exact documents they want to receive. One of them contained something similar to

  The exact subject of research depends on your personal preferences, as long as it fits this area.

So, besides sending a CV and academic transcripts, I was thinking about preparing a cover letter or a research statement (or both). The problem is that they did not specify what sort of skills they need or what specific research objectives they are interested in, so I'm afraid how to tailor my cover letter or research statement.

In fact, as the research area is of interest to me I have ideas of what sub-problems are important there and how to approach them generally. However, I do not know if they fit the group's research goals.

Also, when they did not specify, do I have to prepare both the cover letter and research statement?

BTW, I apply in Computer Science in Germany!

Nobody here can know about the documents that are required, but typically a job announcement has a contact person. Ask them about such details.

The position sounds similar to many postdoc positions in mathematics - they want someone who can do research, be useful to the university, and co-operate with locals. I would suggest taking a look at what the faculty and PhD students are doing at the moment and trying to find shared interests there. Check out the faculty website, personal webpages and Google scholar profiles - wherever you can find list of publications.

You do not need to be doing precisely the same thing as they do, as long as you can make a case that there might be cross-pollination and that you will be doing good work.

If there is a current line of research they are pursuing, mention that. If you could help them move or expand their research, also mention that. You are not setting anything in stone, but rather trying to figure out possible shared interests with the locals. The details of what you actually do will get decided once you are there, most likely.


Did MSCA supersede MCA or do both still fund new projects? According to the page About the Marie Skłodowska-Curie Actions:

  As of January 2014, with the move to Horizon 2020, the Marie Curie Actions are now called the Marie Skłodowska-Curie actions (MSCA). This change better reflects the Polish roots of this extraordinary scientist who inspired and inspires the programme.

This seems to suggest that Marie Curie Actions no longer issue new funding calls.  However, also on the website of the European Commission is About the Marie Curie Actions, which makes no mention of this action being finished/superseded.

Do both the Marie Skłodowska-Curie Actions and the Marie Curie Actions exist concurrently and do both still issue funding calls, or has MSCE simply been superseded by MCA and is the MCA page out of date¹?

¹When accessed 2015-04-04, the MCA page states it is last updated 2015-03-12.

The MCA page is indeed out of date.
See e.g. http://ec.europa.eu/research/mariecurieactions/about-mca/actions/iif/index_en.htm
where if you click on "How do we apply", there is a link to "People Work Programme 2013".

The name MCA was changed to MSCA with the end of the 7th Framework Programme (FP7), and the start of Horizon 2020.


How to respond to threats by disgruntled, powerful former collaborator I am a mid-career mathematician. I have had a long-term collaboration with a well established, influential,  and recognized senior mathematician. We wrote many papers together for the last ten years and the first papers have been the fruits of a real collaboration and exchange of ideas. However, in the last papers, there was no collaboration anymore and I have been the only one to work on the problems and solve them, even though the papers were cosigned.

About 3 years ago I sent a note to this professor with our two names on it, proposing a project and proving a result in a given framework. She/He has been sitting on the file since then, without any kind of input.

One year ago, during a discussion with other collaborators, this project resurfaced and we, the new collaborators and I, obtained a series of very interesting and deep results in another framework. We developed methods which were completely different from  what I sent to the professor. With my new collaborators, I eventually posted a paper on Arxiv in the summer 2017.

A few days ago, the professor to which I sent the file 3 years ago came back to me with insulting emails and threatens to tell the mathematical community and my new collaborators that the project originates from her/him (which is not true) and that I have been deceitful.

I  made the ethical mistake of not informing this professor of my new collaborations and my new collaborators of the existence of this file that I sent to the professor. However, the intersection between the note sent to the professor and the final paper is very small and I have often felt bullied by this professor and wanted to distance myself from her/him. Since this professor is  influential, the situation is very distressful.

What would be the best way to handle the situation now ?

Right now, given the lack of details (and maybe you don't want to add more), it's hard to say what to do.  One thing that would be good to know is: what are you actually worried about?  If you are tenured (I guess mid-career means this), you don't need to worry about that.  What sort of influence does this person actually have?  Disputes happen from time to time, and if your collaborator is a jerk and people know this, they may not pay much attention to their rantings.

That said, my suggestion is to reply with something along the lines of:

  Sorry we neglected to mention my preprint with you.  That project came about independently, and I should have told you about it earlier.  I've added an acknowledgement and a reference to that preprint.  See attached.  Other comments welcome.  By the way, what do you want to do with our preprint?

From my point of view, it makes sense to mention your preprint from 3 years ago in your newer paper, and being generous with acknowledgements costs you nothing.  (Presumably you've had discussion about related things, which, even if your colleague did not actively contribute to your understanding of things, may have been helpful in some ways.  Though again, I don't know the specifics, so you have to decide this.)

Even if you can win, no one wants to get into some big fight about who had what idea when, so if there's a reasonable way to mollify your colleague, it's probably worth it.  Admittedly, your colleague doesn't sound reasonable, but if you add an acknowledgement and reference to that preprint, I imagine most people would think you behaved ethically even if your colleague goes on a rant-page.

You should also discuss this with your present coauthors before doing anything.


Should I complain to higher authorities about the incompetence of this teacher? I am a Computer Science freshman. The instructor of one of my programming classes, where they're teaching Python, is absolutely incompetent. I have been programming since high school and I can tell.
After giving a very bad introduction to Python in the online classes, all they do now is give a list of questions to solve and sit back. The first day this happened, I solved every question and was told to explain everything to the whole class. I did and that was the end of the class. No contribution from their side, whatsoever. Basically, they are finding ways to somehow get by, and seem to have years of experience at it too.
I feel something needs to be done. My first thought was to complain to the authorities, but if nothing is done and they stay, I may have a hard time when I go to college (I was talking about the online classes, remember?).
So, what should I do?

I chose the word "incompetent" because it is an apt description of the said instructor. That is what you call a programming instructor who doesn't know what a return statement does or how to iterate over elements of a sequence (programmers will understand how basic this is).
I wonder how they even lasted this long.

At last, I figured I should just mind my own business. I talked to my classmates. Turns out everyone was having the same problem. We complained to the department head. The course is being restarted, but the instructor is the same. I don't know if it was even worth the effort.

This is more of an extended comment, placing some guesses as to what's actually happened here. As an answer to the question it is the advice to consider which parts of the following applies to your situation, and adjusting any actions you may take accordingly.

Keep in mind that computer science is not programming. This instructor likely doesn't code much Python in their main job (CS research presumably), nor did they necessarily ask to teach Python. Rather, the departement decided to teach Python as a beginner language, and somebody needs to do that teaching – somebody who knows enough about programming to help actual beginners, which will be helpful to the course's intended audience, but not necessarily an actual Python expert.
You, apparently, are a Python expert, which is great – relax, this course is going to be easy for you, and if you can even contribute to making it better for your fellow students, awesome.
But don't let your superiority in Python fool you into thinking the instructor is inferior as a teacher of a beginner's programming course. You think their introduction to the language was bad... why?

Was it hard to understand? Well, that could mean they explained stuff badly, but surely you as an already-expert wouldn't have had problems regardless?Maybe they actually explained some aspects that really are more tricky than you ever considered.
Was it too shallow? Well, that may be exactly what's right for your fellows without earlier Python background.
Did it use outdated or unidiomatic code? This happens a lot in university courses, but it's not necessarily such a bad thing. Keep in mind that anyway today's up-to-date is just tomorrows outdated and one language's unidiomatic is another's bread&butter. General concepts are more important in a beginner's course than language-specific details.

Regarding your concrete statements,

doesn't know what a return statement does

I plainly refuse to believe that. I mean, if it's really that bad then forget all I wrote above... but almost sure there has just been a misunderstanding here.

or how to iterate over elements of a sequence

That too should certainly not be a problem to anybody teaching anything programming-related, however I would still remark that Python's iterators are somewhat idiosyncratic. It's true that for a Python course, they should have read up on this properly, but again make sure you're actually interpreting this properly. First teaching loops with indices before going to range- / iteratee based ones is a valid pedagogic decision, even if it doesn't make much sense as far as Python programming in particular is concerned.


Why might a journal editor reject a submission, but suggest submission to a sister journal? We (I with my co-authors) recently had done a high-quality work and submitted to a Journal A (with high impact factor and reputed). A belongs to Wiley Publishers. In its' own site, it displays a set of Associated Journals (which are possibly its sister or new journals).

We had submitted a work which achieved far better results than a recent work published by the journal A. We were hoping about a green signal on acceptance. However, to our surprise, the editor rejected the paper and suggested to submit the work to one of its sister journal, which are new and not having any impact.

It is bit strange, though. Is is just a strategy to promote their sister/new journals? Why would a journal possibly reject a high-quality work just like that?

Note: The present status of the paper in submission system displays recommended for other journals.

That's pretty common, a lot of journals offer to move your submission to other journals of the same publishers.

Why do they do it? Well, if they think that publication is worth anything (will get cited...) they can indirectly make money with that, so the publisher wants to have it.

Now why wouldn't they just accept it then?
There are two reasons. One would be it's not good enough for that journal but it's good enough for another, which doesn't seem to be the case here. The second one would be that it doesn't fit into that journal for whatever reason (likely here). In both cases they will offer you the possibility of that other journal.

For Wiley an example would be Angewandte Chemie and Chemistry - A European Journal. The latter is somehow a collecting tank for rejected publications in Angewandte Chemie and it's also the journal for Full Papers, as Angewandte Chemie does only accept Communications. (And well, all the editors there are in a certain field of chemistry, so nowadays submissions which were in scope some years ago now get rejected with "not in scope"...)


Taylor and Francis Manuscript Status "Under Review" Does this status mean it has been sent to referees? Or is could it still be desk rejected?

Under review implies it has been sent out for peer review and has passed the initial check. T & F primarily uses ScholarOne Manuscripts but also have their own electronic submission system. There may be slight differences between these but I would think they are set up similar to each other. I am familiar with the ScholarOne system.


How to respond to an editor's post-review comments suggesting major changes I'm not willing to make? I submitted a paper (in applied mathematics) to a journal about a year and a half ago. I received the first feedback from the Editor in Chief about a year later (the reviewing process for this journal is usually long): the two reviewers were positive and suggest minor revisions (clarification, typos, etc.). At this point, the EIC wrote me that he would keep his comments for the next round of reviewing.

The second feedback came 6 months later. The two reviewers replied very shortly, saying that their requests had been satisfied and one of them recommended publication overtly.
At this point, the EIC wrote a lengthy set of comments on the paper which can be roughly divided in two categories:

On one hand, revision of typos, clarification of some paragraphs, etc., that the reviewers had missed.
On the other hand, he commented on the theoretical framework used in the paper, saying that it was unnecessarily complicated and hoping there would be a simpler way to achieve the same goal. He suggested to cut most of the parts where this theory would be used and to rewrite the paper accordingly.

I feel being in a delicate situation, where I'd like to have this paper published, but not sacrifice its background and the main ideas it implies. For me, the theory which is proposed provides a very simple way to deal with the examples. I am considering writing to the EIC to essentially ask him if he's ok to keep the theoretical background (with justifications from parts of the paper) in which case I'm willing to make the revisions he requested for clarification (I'm considering withdrawing the submission in the other case).

What do you think would be the best way to handle this situation ?

I would suggest the following thought experiment. Take a day (or at least a couple of hours), and fully embrace the editor's suggestions. Think about why h/she made them, and think about how you would revise your paper to fully incorporate his/her suggestions, and in what aspects it would make the paper better.
Sleep on it a couple of days. Then, if you decide you prefer not to take the editor's suggestions, you will be in an excellent state of mind to write a reply.

I carefully considered suggestion X. As pointed out by the editor, this would have advantages Y and Z, and W. [It is especially helpful to not just say the same thing word-for-word, to show that you thought about the editor's suggestions carefully.]
Nevertheless, I feel that for the most part the paper is better as is, for the following reasons: ...


My adviser is hesistant about letting me graduate. How should I handle it? I have seen the work of previous and current students and I have done a lot more than them, and my dissertations is about 60% written already, however, my adviser seems to not be comfortable with the idea of me graduating in May (Is January now). I have asked him several times up front and he keeps evading the topic and goes around it and never confirms it. He is always on travel and is not even at my same institution anymore, so that makes things worse. I have a job lined up and he knows about it, but he seems to be holding me back. I have talked to fellow students and they feel he is being unfair to me. What should I do?

Most departments have a faculty member who serves as the director of graduate studies. Talk to this person about the situation. He or she will have much more contextual information than any of us here, and it is this person's job to resolve such conflicts between students and advisors.


How much effort does it take to modify a reference letter for different applications? I am in my early PhD years and encouraged to apply for scholarships/fellowships that would boost my funding. All of these applications ask for recommendation letters from previous supervisors, and while I had a good relationship with my supervisors, I am no longer doing work for them, so feel guilty asking the same people several times a year to submit letters for me (this is after all of my grad school applications have asked for letters from them). Especially (I presume) when some of these awards may be asking for specific qualities/information about me that might require some updating of both the letter's content and format each time.

Since I have never written a recommendation letter or seen what requests specifically ask for before, I was wondering:

How much variation is 'typically' encountered between different fellowships/scholarships? Do referees need to make major edits between different applications or is it possible to mostly copy-paste the same letter once you have it written for the same applicant? How long does it take to adapt a pre-written letter for each new application? How much effort is it comparable to? Sending a regular email? Holding an office hour? Grading a problem set? Putting together a final exam?
Is it reasonable for students you have supervised in the past to keep asking for recommendation letters? Does this become tiresome?

If these people believe you are deserving of an award and have already written you a letter, they certainly won't mind modifying it for this purpose.  If they don't think you're deserving of an award then of course you don't want them to write you a letter for this purpose.

The answer to #1 depends on the letter writer and the specific applications/awards involved.  But it is a much smaller effort than writing the initial letter.

The answer to #2 is that yes, this is reasonable. Remember that your letter writers were once in your shoes, and asked people to write letters for them.  One day you will pay it forward.


Should a programming Instructor urge students to use more efficient practices? I teach programming, and it is painful to watch my students slowly arrow around the screen, backspace over something, then retype it. It would take less than a second for him to have grabbed his mouse, double-clicked the word and started typing the new word, all without looking down.

I taught them about editing and keyboard shortcuts at the beginning of the curriculum, yet they do not all take everything on board (who does?). So now months later I am left with the question of whether to urge improvement on them like a mother bird, or just let it go. As programmers, their time will be valuable, and their enjoyment of work improved by the ease of getting work done. But is it up to me to reinforce this after having made it thoroughly clear early on? This is not just about editing, but all sorts of practices like naming conventions, coding standards and so on, which I did in fact present already and have said that the industry expects these things. Editing is simply one obvious example.

Addition: It is not for me to dictate how students should work, but I would be remiss if I did not point out better ways to accomplish things. The question is: to know if I have made the point or when to stop trying to make it. "A word to the wise is enough", but how many of us are wise, especially while learning many new things at once? An example of coding standards is a student who doesn't like Properties. Well... They are useful or they would not have been invented. I couldn't convince this person.

I'm not a coder but I am familiar with learning something for the first time. As a teacher, you have reached a level of mastery that allows you to do things automatically. As such, you are able to monitor your learning and catch mistakes that you make.

Students on the other hand, are completely overwhelmed with learning the basics of your field. We all remember learning to tie our shoes and or driving a car. There were many things that were not done in the most efficient manner when we learned these skills. Now however, these skills come second nature and we all have are own shortcuts to do them that we expect are children to acquire the first time we teach them, which of course they don't to our frustration.

In short, your students are experiencing cognitive overload just learning the basics and cannot process doing more than what they are doing now. Once the learn it the hard way they will start looking for ways to be efficient and fast. At this point, you can stretch them by showing them the faster way. To expect industry standard from a rookie is perhaps asking for too much from cognitive perspective.


What factors should I consider when deciding between a general MBA vs. a specialized MBA? I'm currently in the process of applying to business schools and I notice that nearly all of them have general MBA degrees and MBA degrees with different areas of concentration or specialization. I currently work in the IT industry doing some project management and customer support, though I'm on the fence about whether the IT industry is where I'd like to stay.

I'm going back and forth between the general MBA and something like an MBA in IT Management, but I'm having trouble deciding. What are some things I can consider during this process so that I can make a good decision and not get a degree that's either too general to be useful or too specific to give me options?

Because you already have real world experience in IT but are unsure it is where you want to stay, a general MBA should be fine.

If you want to stay in IT, what most companies care about is actual experience - and it seems you have that. Having an MBA and experience in IT is a great combination and having experience in IT is far more useful than having a specialist MBA in IT.

Another issue is that IT management is usually not a challenging place to get to if you are interested. I've worked with quite a few people in IT and it was the rare one who wanted to be in management. Most wanted to keep their hands in the technology. For this reason, IT management is different from many other fields in business.


How can my organisation's published reports get indexed by Google Scholar? My organisation (i.e. my employer) publishes peer-reviewed research reports in the form of a journal series via its website.  The organisation alone publishes the reports and they are not published in conjunction with any publishing agency or academic body.  The research reports are written and peer reviewed by academics and the research activity funding is managed by my organisation.

The research reports are in PDF form (with metadata attached), and are listed on a web page containing metadata in the form of the fields required by Google Scholar.  The Google Scholar submission process was completed ten months ago in March 2016.  There was one issue identified: there is not a volume/issue listing of the reports, they are discoverable via the website search engine.

The website has been submitted to Google Scholar with example URLs, but to date, the body of research that is made available via the organisation's website is not included in the Google Scholar index.

Where the research reports are also stored and published by university databases, these do appear in the index.

Additionally, citations to the research reports do often appear in the index without any link to the location of the report.  Ideally, we would like to enable these citations to also show links to the online reports.

I had thought that the form and structure of the research report publication was suitable, but our organisation's website has not been included in Google Scholar indexing.

Some suggestions on the Google Scholar website are to use a journal publishing service (established journal hosting services) or recommended software such as Open Journal Systems.

What process should I follow to investigate or progress this issue further?

I suspect that I'm not looking in the right place in my investigations, so I need some direction.

We found that by submitting our content to SSRN we were able to see the content (once approved and distributed by SSRN) subsequently indexed by Google Scholar.  This method is, therefore, an appropriate solution in our situation for this problem, without the need to restructure our website.


I have defended my PhD thesis yesterday. Can I ask a committee member for his feedback on my answers during question-answer session? My PhD is in computational Materials science. I successfully defended my thesis yesterday. However, I felt that one of the committee members was starting to get angry with my answers. I was trying to answer his questions, but his questions were very vague indicating that he clearly did not go through my thesis. Thus I had to answer his questions a bit elaborately, so that he could understand the reasoning behind my answers. I could sense that he was dissatisfied with my answers.

For example: He asked me, how confident are you about your theoretical model when comparing with the real world experimental results?

My answer: Since my model has A, B, C assumptions. It can never accurately predict the experimental/real world results.

His question: What would be your confidence level? What percentage?

My answer: It would be hard to put an exact percentage. But I would go with 90%.

He followed with an "okay".

Can I ask him directly about his feedback on my answers during the session?

This would depend somewhat on your general relationship with him. If he is relatively anonymous to you then it probably isn't worth the effort and you won't get the feedback you want.

But if you know one another well, through coursework or other research (etc.) then it might well be worth a sit-down. You may have some misunderstandings and he may be able to help you clear them up. He may be able to point to directions for study or research. There are a lot of things.

But if you approach it right, you also show respect for him and his ideas and that can lead to a better long-term relationship that might be profitable.

And, it isn't especially uncommon that a committee member (even several) haven't read your thesis. A common question from committee members to advisors just before or after the defense is "You're sure this is ok, Jack/Jill?". The advisor nods affirmatively and all is well.


Is there a professional etiquette regarding jackets in academia? So, I’m sure we all know about the stereotype of the professor in the tweed jacket. Based on a cursory web search, it looks like the stereotype started because tweed was a relatively cheap but warm material, and professors were a relatively poorly paid class of professionals, so they kept wearing them until the elbows wore out and they patched them.

I’m aware that these sorts of things can get a degree of momentum of their own, though, so I was wondering if there was any etiquette in modern academia regarding jackets? I’m a master’s student who is planning on doing a PhD afterwards with the intention of getting into academia; would buying a tweed jacket to try to look professional be viewed as presumptuous or anything?

I don't know if I'd call it an etiquette, but there are certainly different ways to dress in different subfields of disciplines. If you attend an academic conference and notice such things you will see the variety by clique. As for tweed, my partner and I wore it as students (bought second-hand in Edinburgh) and we were mostly viewed as the eccentrics we are, as far as I know. Dressing decently generally shows respect for others, though a few people find it an affront to their class consciousness. Dressing expensively can be seen as distancing from those who can't afford it. The main thing is to be confident that you are presenting yourself as who you really are, so then if there are any concerns you can hopefully laugh them off or explain your dress as a matter of personal taste and/or a concern for general aesthetics.


Is it rude to sign off mails with a shorthand This may seem a bit mundane or silly to many but I figured it might be useful for others besides me, hence the question.

My boss (postdoc mentor) is a very kind person, who pretty much exclusively writes in grammatically correct, well articulated sentences and ALWAYS have a nice but relatively formal greeting at the end of the mail. No matter how many times we mail each other in a given day. Even though we are not formal at all when we talk to each other.

As per usual in Scandinavia, we have a very flat hierarchy here, so everyone (from project students to professors and indeed the dean) is on a first name basis with each other, and there are little formalities that may be commonplace elsewhere.

We have been working very closely on this project, with almost daily meetings and near 10-15 mails exchanged throughout the day. My previous experience has always been so that once the formalities have been observed, the communication defaults to shorter, more direct mails.

Given the high-paced exchange between us, I was wondering if it would be rude to write shorter mails that are straight to the point. Specifically I often find myself signing off a mail with a shorthand greeting, e.g. "mvh" instead of "(med) vänliga hälsningar" (which is significantly more formal) or just by writing my name. [The Swedish expressions roughly correspond to "BR" - "Best Regards", respectively].

I thought of asking him if he prefers a more formal tone in our written communication but I don't wanna come across as a pedantic person. Suggestions?

(Am also currently working in Scandinavia, have previously been in universities in the UK, US, and Canada.)  Abbreviations are almost certainly fine; but look at what others in your department do.

In most departments, you should be able to see a wide range of colleagues’ emails (thanks to admin lists/announcements, etc).  Look at what they do, and the range of ways they write.  Additionally, note that emails between close colleagues (e.g. within a research group) may tend to be slightly less formal than emails to wider audiences.

You will probably see a fair range of styles.  So long as you are within that range, you are probably fine; you don’t have to exactly match every individual correspondent.  In case everyone at your department writes particularly formally, then it may be worth doing so yourself — but even then, I would be pretty surprised to hear of anyone in Sweden taking offence at use of “Mvh” as a signoff. I’ve received it in emails from students, professors, and administrators, so at least in my department, it’s considered fine for a wide range of professional relationships (though definitely towards the more informal end of the spectrum).


Difference between postdoc and researcher in Sweden? At Uppsala universitet there are currently open positions as mathematics postdoc and as researchers. The announcement texts are identical, aside from this part (and clarification on it) that is missing from the researcher position:

  To be eligible for a position as postdoctoral researcher the applicant's PhD degree must have been obtained no more than three years prior to the application date; however, for example periods of sick leave or parental leave are deducted from the three-year period.

What is the difference between researcher and postdoc in the Swedish system in general, or Uppsala university in specific?

The difference is that a postdoc's PhD degree must have been obtained no more than three years prior to the application date.  For a researcher, there is no such limitation.

It means they want a postdoc, but if it's been more than three years, they can't call her/him a postdoc and will call her/him a researcher.  They'll probably pay more for the researcher but they probably would also pay someone with 8 years of postdoc experience more than someone with 2, even if they were allowed to call both a postdoc (like they would in, for example, the UK).

It's common in Sweden.  See this question.


PhD application cover letter closing formula(e) A friend has asked me to proofread their cover letter and CV for applying to a PhD position. I've done such proofreading when it was about more-or-less unskilled labour, or for friends who'd done a Bachelor's or Master's degree and were applying somewhere at some company. Never for a PhD, and I'm generally wondering what differences there are.
Specifically, the cover letter has the "thank you for your consideration" phrase at the end, followed by an "appreciate the opportunity to meet" phrase. A PhD is not a very common thing, so my question is: how appropriate (or not) is it to use such omnipresent formulae at the end of a cover letter seeking admission to one?

It doesn't matter. I'd probably suggest editing it to just one of those phrases, but it doesn't matter.


Can I cite almost total literature survey from a textbook unit? Suppose I'm writing a research paper on topic T.

Additionally, suppose there is a textbook or research paper on topic T that covers all the progress of the topic from its initial time to 2018 December.

Since I'm writing a paper during April 2019. Can I cite the research paper or textbook for literature from early days to 2018 December and only explicitly cite the remaining literature from January 2019 to April 2019 or do I need to also write a total literature survey for my research paper? If yes, what is the need to write again if I'm citing a credible source for literature?

Your intended audience should be able to read your paper without referencing other papers. So, unless your entire target audience will already have read the survey in question, you should summarize it for them. Saying "go read this survey, then come back" is a dereliction of duty. Note my reference to "your intended audience" -- a publication in Nature has a wider audience than J. of Machine Learning, and so your Nature paper must explain past work that the latter journal's readers would certainly already know about.

Further, the survey in question is unlikely to be suitable for your specific purposes. Yes, it may contain all relevant information, but it is likely addresses all the major results for the field as a whole. In contrast, your paper is offering a specific advance on a specific problem -- so, you need to explain which aspects of which results are relevant, and which avenues have not been addressed. Further, it is typical for survey to omit results that are unimportant for the field as a whole, but important for the topic of your paper.

Either way, the survey sounds like a great resource -- you should definitely cite it.


How to deal with this type of rejection without review report? After being in "Under Review" status for 4.5 months (before that it stayed in "Reviewing" status for 3 weeks), I get the following cold rejection without any review report or review comments. How to deal with this cold rejection? If it had come much early, without going into "Under Review", I would have saved time (valuable for an independent researcher. I am not disheartened by rejection but the lack of review report or comments.

  Dear Professor XXXXX,

  This message concerns the manuscript

  XXXXX A XXXXX(XX) XXXXX XX XXXXX    by XXXXX XXXXX

  submitted to the Journal of XXXXX & XXXXX.

  We regret that we cannot consider it, in part because at present we
  have a large backlog of excellent articles awaiting publication. We
  are thus forced to return articles that might otherwise be considered.

  Thank you for considering the Journal of XXXXX & XXXXX.

  Sincerely,

  XXXXX XXX     University of XXXXX, XXXXX Editor - XXXXX & XXXXX

Educated guess of what happened: they invited reviewers (which automatically updates the status even if the reviewers don't agree to review). Some/many of the reviewers then declined to review, giving reasons that made the editor decide to desk reject your paper.

I'm not a mathematician, but from what I've heard, 4.5 months is not a particularly long wait for mathematics papers. If so, it's not really fair to say the journal treated your manuscript in a subpar manner.

There's nothing you can do about this except submit to a lower-tier journal.


Advice on conclusion of a purpose statement I am currently applying to PhD programs in mathematics and need to complete a purpose statement as part of the application. There are several things I'd appreciate any advice you can give me on the following:

What is a good way to end the letter in a strong way? I wanted to say something along the lines of "I greatly look forward to further understanding the intricate theory of XYZ" but this seems a bit cliché.
I wanted to mention my specific  interest in school XYZ/professor XYZ, but I don't know enough about his/her research to say something intelligent or insightful about it. What should I do? Is it better to have some indication I did my research for this school than to say nothing at all? To be clear, I am interested in the field of these professors but my knowledge is too shallow to fully understand the impact of their work. How can I add something substantive but not sound like I'm making things up to sound smart?
For one of the schools I am applying to, a big reason I want to go there is due to their well funded program. Should I mention this or will it seem tacky?
What is a "smooth" way of mentioning I want to work with a professor? It seems too abrupt to just say "I want to work with professor XYZ". What if this person doesn't have any current students (or at least doesn't have them listed in his/her Web page). Should I take it that this person is not currently taking students?

Any and all advice would be helpful. Thanks in advance!

What is a good way to end the letter in a strong way?

It doesn't really matter too much as long as it's not too cliched (although even that's probably fine) or overly memorable.  An example is to say something nice like "Given my background and the excellent research faculty at University of State, I look forward to making a contribution to the research program at University of State."

  What should I do? Is it better to have some indication I did my research for this school than to say nothing at all?

It's definitely better to have some indication that you did your homework.  You don't have to have any particularly insightful things to say, just explain why you found their work interesting and why you want to work with them.  Those are questions you should answer for yourself anyways!  Definitely don't make things up to sound smart.

  For one of the schools I am applying to, a big reason I want to go there is due to their well funded program. Should I mention this or will it seem tacky?

Mention it tactfully.  Say something like you appreciate the commitment they make to their graduate students and that it speaks to their commitment to good scholarship.

  What is a "smooth" way of mentioning I want to work with a professor? ... What if this person doesn't have any current students.

There's nothing wrong with mentioning that you want to work with specific faculty; it's expected that you have some ideas of what you want to work on before you get in.  So say who you want to work with, but make sure you list several faculty members who work on things you're interested in.  This way, should it happen that the person is not taking students, your application will still get a fair shake.

This next piece of advice is maybe controversial given how many emails professors get, but after you have applied, you can send a short email to the faculty you mention in your statement of purpose telling them that you've applied, you are interested in their work, and if they're looking for students to keep your application in mind.

  Should I take it that this person is not currently taking students?

Not necessarily but it is strange for an active research professor to have no students.  Ask a graduate student in the department why they have no current students.


Isn't the PhD supervisor required to teach the student the research subject and prerequisites, in order to save time? My friend is completing her PhD comprehensive test and is going to start research.

Her supervisor is emphasising the importance of self-learning. He is saying that "I will provide the necessary resources, books, etc., I am not going to teach you anything, it is your responsibility to complete prerequisites. There are several resources over the internet to accomplish all your required tasks".

My doubt is that why can't the supervisor teach at least the prerequisites and the subject of research to some extent?

Anyway, the literature survey and the publishing will be done by the student only. In this context, my doubt is to know whether the supervisor is bound to teach or not?

Supervisors train; they don't teach. (Albeit the distinction between terms is rather subtle.)

  why can't the supervisor teach at least the prerequisites and the subject of research to some extent?

A PhD is like an apprenticeship, rather than a taught degree (such as an undergraduate degree). Hence, supervisors are expected to train, not teach.

  the literature survey and the publishing will be done by the student only.

Actually, the supervisor will guide the student in both activities and will (likely) be a co-author of any publications.

  is...the supervisor [likely] to teach or not?

No: The supervisor has said they won't teach nor is it their job to do so.

The supervisor is quoted as saying, "I am not going to teach...it is your responsibility to complete prerequisites," which might reference (especially in the US) taught courses that PhD students are required to take. Given such context, the supervisor may merely be explaining that it isn't their responsibility to provide any help for taught courses.


Link IEEE Xplore article with its arXiv version in Google Scholar After submitting a paper, I uploaded it on arXiv, to give it immediate visibility.
After a few months (more than six months), the article has been accepted and finally published on IEEE Xplore. However, Google Scholar only shows the arXiv version, without pointing to the IEEE one.

How can I manually make Scholar recognize the presence of the published paper?

Google Scholar will eventually find the IEEE version of the paper. Just give it some time.

See the last item of the "coverage" page of the Google scholar FAQ and the second item of the "search tips" page.


Should I contact my advisor again about a meeting? If so, how? I finished the next step of my project and sent it along to my advisor last Friday. In my email I said "When would be the best time to meet to discuss these results?". I do have access to her calendar so I know when she is free, but I wanted to ask her when would work for her as I want to give her enough time to review what I sent her. My field is quite busy at the moment since there's some major occurrences in the world right now, and she is dealing quite a bit with it so is quite busy. Also, there has been an instance in the past where her work calendar was not up to date. Plus, I didn't want to seem too forward by just sending her the project and then immediately sending out a meeting invite.

Anyways, I haven't heard back from her at all. Should I send her a follow-up email? Or should I just go ahead and send out a meeting invite?

If you have an "action item" that requires her okay then send an email (or other accepted communication). If you are just anxious and can proceed for now on your own then it might be better to show patience.

As comments to your question suggest, and even the question itself, the calendar may be inaccurate. Things might have come up. Perhaps she just trusts you to carry on while she is busy. While you are dealing with only one professor, she may be dealing with several students and other obligations.

But don't panic until it becomes necessary and don't be a pest. Half a week isn't a long time unless deadlines loom.

But don't get yourself blocked up for the lack of a meeting. There are plenty to things you can do speculatively to keep momentum.


Are there any new(er) models of publishing/reviewing and if so how will they address the problems that we have today? I was reading this article on The Guardian about scientific publishing and peer-review process. The author raises a fair number of concerns with the existing model, most of which I agree with. The article ends with the following statement:

  ... but the need for reform is profound.

I ended up thinking about this idea, a reform in the way we do science. By doing science I mean the whole process of writing, submitting, reviewing, publishing and measuring the results of our work (and not the actual work itself).

While I agree with the author about the current system being faulty, sick, or corrupt (depending on the shade of glasses you look at it), I cannot really come up with a system that would magically solve the existing problems just like that.

The Arxiv idea is named in the article and from what I understand people in physics and math quite enjoy the benefits of that site (whatever it is) however with the amount of money and prestige involved, I cannot imagine how it would be implemented in fields like biology, chemistry and medicine.

To sum things up, my question is whether or not there are/have been alternative models to the existing one: blind, peer-review, hundred of journals, and metrics of "quality" flying left and right. If so which shortcomings of the existing model were amended?

As I see it, the issue is not actually how publishing and reviewing work.  There are lots of alternative models out there, including modifications of blinding (e.g., Frontiers names reviewers when a paper is published), alternative approaches to peer review (e.g., IETF RFCs, math and physics use of arXiv), and decreased need for additional journals by removal of artificial "throttling" of publication rate (e.g., PLOS ONE).

Instead, my belief is that the problems we face lie more in the way in which quantification of publications is used as a proxy for evaluating significance and impact of work.  Peer review is a reasonable system, and many of the tweaks on it look like fine systems as well.  Making peer review high stakes, however, turns it into a system that people need to try to game and distort because it directly impacts their ability to remain employed and to fund their research.

Because of this, I think that any attempt to "fix publishing" will not actually fix the problem: at best, it will simply shift the focus of high-stakes distortion to a different area.  This is something that we see already, with the emergence of this great diversity of different "quality metrics," each of which is gameable in various different ways.

At the end of the day, however, all decisions about scientific funding boil down to some mixture of personal judgement and some sort of metrics.  The more that we have metrics (publication or otherwise), the more that the system can be gamed; the more that we rely on personal judgement, the more subject the system is to bias, prejudice, and cronyism.  I don't have any clear notions on how best to go about improving the balance in order to improve things, but I think it's important to have a clear identification of the actual locus of the problem that needs to be addressed.


Should I include reference section on a conference poster? I believe that including references is important, especially for a chemistry conference poster. However, I have more than two dozens of citations so it is way too lengthy.

Should I still include the reference section or should I simply explain when asked?

Biologist here.

I tend to be more careful to cite methodology on a poster rather than things that belong in an introduction or discussion section, and especially anything derived directly from a particular paper, such as an equation that is on the poster.

Sometimes there is a particular key reference - either a review or highly relevant original paper - to cite for background. Otherwise, if you find yourself citing a lot of things you probably have too much text on the poster.

(to be clear: if it needs to be cited, it should be cited; it just turns out that the type of content that needs to be cited should be at a minimum on a poster)


What should I do if I have specialized in a useless research area? I am a PhD student in computer science, and chose to specialize in a research area that was interesting to me personally, but not interesting to most tech companies.  I am approaching graduation and I am not sure where to find a job.  What do I do now?

The specialised research area of your PhD topic probably has a wider range of related fields which are relevant to prospective employers.  I suggest identify those fields and use them to build your own resume, and also to identify prospective employers.  Search those terms in job sites and identify employers that way.

Unless committed to specifically continue research in a focused line of investigation, then in most cases, I believe that job seekers in your position are really looking for work which utilises the broader skills that they have generated through their post-graduate degree.  Try to take a step back to think of the skills you have gained.

The more generalised skills such as general subject knowledge, investigation, research community networking and research are more likely to be of value to your prospective employer than your expertise in your own specific topic.