text:
Any advice about having children during grad school, from the perspective of (a) female grad students and (b) students without stay-at-home partners?
I've seen a lot of "kids-in-grad-school" advice that's geared towards male PhD students with stay-at-home wives. I'm a female MD PhD student married to a male MD PhD student, and neither of us is going to quit our career. We are both willing to put in the time needed to raise a family.
I'm interested in hearing from the following perspectives (EDITED FOR MORE DETAIL):
(a) For women who had kids while they were in graduate school -- how did you decide on when to have kids? earlier in grad school vs. later? (since pregnancy can be very difficult for some women e.g. severe morning sickness, I think optimal timing could potentially differ depending on if the grad student is male or female.)
Also, how did you approach being pregnant in an academic environment? (i.e. did anyone harass you as being 'less dedicated'? I know this is not a reason NOT to have kids, but I'm just curious about it. Men who are expecting a child can keep it a secret. Women can't keep it a secret because everyone they meet including total strangers can see that they're pregnant after a certain point.)
(b) For men or women who had kids while they were in graduate school and did NOT have a stay-at-home partner - how did you deal with childcare? Reason for asking: if you have a stay-at-home partner, childcare for the bulk of the day has already been solved. If you don't have a stay-at-home partner, it's a very big issue.
So - what approach did you take? (e.g. alternating schedules between caregivers? nanny? au pair? daycare? relatives? friends? babysitters?)
This question is different from Advice for having children during graduate school  because the vast majority of those answers are written from male perspectives and from perspectives of people with stay-at-home partners.

This question is far too broad in scope. What specific question are you asking? Also, what's lacking in the advice you've already consumed? I'm sure there are differences in the experiences of men and women in these roles, but I have no idea what specifically you find insufficient about the perspective from the opposite gender.

Possible duplicate of Advice for having children during graduate school

I guess the downvoters, whoever they might be, would welcome it if you (1) cite the research you did so far on this question, and then (2) narrow down your question.

I think How to finish PhD and get through the academic job market as a new mother and primary caregiver? is probably a better duplicate candidate. Unfortunately, it only attracted two replies (full disclosure, one is mine).

To prevent closure, perhaps it would help to ask when is a good time to have a baby in the academic life span.  Or, focus the question more on how to prepare.  (The latter's answer would include, for example, read up about breastfeeding ahead of time.)

I want to be helpful for this question, but it is currently too broad. Perhaps focus on your biggest concern or uncertainty?

Perhaps narrow by time point: Do you want advice on timing and/or preparing to get pregnant? On what you should do pre-birth? Or what to do post-birth?

Damn. gonna be a lot of pressure on your kid considering their parents have combined four doctorates

A location tag would help, as the practicalities of childcare and availability of (paid) parental leave is local and would probably (I don't have kids, so only guessing) have a large influence on any advice.

I will answer based on my experience and that of approx. 4 other women in my department who had kids (without stay-at-home spouses) during our PhD program.

For women who had kids while they were in graduate school -- how did
  you decide on when to have kids? Earlier in grad school vs. later?

There were a variety of approaches, but I think the key is to have children in a year where deadlines are flexible. So one of the students had a child very early (while taking classes) because there was no hard stop on when the classes had to be done by, and she could basically take a semester off from classes without real consequences. Three of us had children during the 3rd and 4th years when we were expected to work on our dissertations. Some were a bit ahead and didn't need to stretch the time to degree as a result of the pause, and some, like me, did. I think this was the best timing because we had a good foundation in the program/relationship with our advisors but were in a very flexible time period. I also had a fellowship for that year so it made funding easier. The person who had a child during the job market year had the hardest time, since those deadlines are non-negotiable.

Also, how did you approach being pregnant in an academic environment?
  (i.e. did anyone harass you as being 'less dedicated'?

I stressed a lot about this. My approach was to foreground my research and academic plans in all conversations, while backgrounding my pregnancy. I set meetings with my advisors to discuss the pregnancy and presented it as a scheduling challenge - I am going to have a period of decreased productivity because I am pregnant so here is my proposed plan to stay on track. Here is what you can expect from me in the next 6 months to get ahead as much as possible, etc. I found this worked really well. When people asked in the hall about how I was doing I gave them a positive research-related answer, not a pregnancy answer. The only person who gave a poor reaction was the Director of Graduate Studies, who assumed that the pregnancy meant I would be targeting lesser positions. I corrected him, of course. If he had any real sway over my life I would have made sure my committee knew about it and could discuss the issue with him. I think that others had a similar mix of reactions... mostly supportive with some "lesser expectations" attitudes that needed to be countered.

How did you deal with childcare?

With the exception of one person with nearby relatives, all of us paid for the best childcare we could afford (nanny or day care). You want peace of mind, trust, and communication--and that often means $$. We all made sure to set a consistent schedule (baby likes consistency). We differed in how soon we came back to work and how many hours per week we worked. That is a personal choice and based on your goals and work required to achieve those goals.

Thanks for your response, and especially for the combination of personal experiences + experiences from others in your department - it's very useful!

I forgot to add something about working at nights and on weekends. Basically we both took breaks during dinner time and bedtime 5-8 pm. After 8 we both would do work until we slept. We traded off on weekends depending on who had urgent deadlines. The goals was to try to be even over the long run, not within a week. With nighttime feedings, I ended up doing those because of biology of breastfeeding, but I do know that some moms pumped so their partner could do some or all of the night feedings. One way to decide is based on who functions better on low sleep.

What you end up doing is going to be very specific to your individual circumstances, but I can give you my two cents about how my wife and I handled this situation.  Currently, I'm a 4th year PhD student and my wife is 2 years into a MS degree with the aim to get a PhD.  We both hope to stay in academia.  We have two kids, ages 4 and 6 mo.
Our first kid came before either of us were in grad school, and our second came a year later than we had planned. Our decision was to have kids earlier rather than later because grad school is more flexible in terms of schedules than real jobs.  This really helpful when my wife was practically bed-ridden for a couple months of her first trimester with our second kid.
We didn't want to stick our kids in daycare full time, and we have no family around to help, so we came up with a switch-off schedule.  My wife works from 4am-noon (and some hours on weekends) and then we switch off and I work noon-6pm.  Then I work at night from home after she goes to sleep (early).  Our 4 year old does go to pre-school a few hours a week and the baby naps, so I can put in a few more hours during the day this way.  Of course, schedules like this depend on our advisors being okay with our hours, and for our work (me CS, her biochemistry), it works out. Depending on where you are and at what point (and structure) of your MD-PhDs, you might be able to do this.
One consideration is that by the time both of us are on the job market for tenure-track positions, both kids will be school age, which allows us to both work normal business hours.  Also, by the time I'm into a post-doc, our baby should be sleeping through the night.  Until that happens, caring for children is very draining and it does affect my productivity in research.
As far as I know, my wife did not experience any overt discrimination against her for being pregnant.  Her supervisor was generally supportive and understanding even when she couldn't work because she was too sick.  However, as with many medical conditions (e.g. disability, known mental health issues), you're sure to encounter at least unconscious bias for being pregnant.

Thank you!! I think your perspective is very interesting since both you and your spouse are grad students. I also think your switch-off schedule is an intriguing idea - thank you for sharing!

I fall into category (b): male who was a single parent, and primary carer, during grad-school.  In my particular case my PhD was a research degree (no coursework) in statistics, and so I did the vast majority of my study and research from home.  During the day I would look after the kids, and sneak in some research time when able, but most of the research was done after their bed-time, or at free time on the weekend.  I also found that I was constantly "mulling" over my research and ideas when I was looking after the kids, so there was also a certain amount of subconscious work going on at those times.  I had the luxury of being in a program that could almost fully be done from home, since it had no coursework, and involved research in mathematical things that can be done mostly on paper and a computer.  Consequently, my experience is probably substantially different to someone in a program that requires course-work or laboratory research.  Nevertheless, I will give my experiences for whatever they're worth.
Although I did most of my work from home, I had a monthly supervisory meeting plus time on the university computers to download a new set of papers for my research.  There were also sporadic occasions where I required attendance for some administrative matter, or some aspect of research where I needed new materials that I could only get through the university.  Naturally, attendance at the university was a big chore, since I had to get the kids ready, bring a lot of paraphernalia, and I also had quite a long bus ride each way.  For supervisor meetings I would take the kids in with me, and they would do some colouring-in, draw pictures on the white-boards, and other activities.  This was usually enough to occupy them for a short meeting, and my supervisors were nice about it.  I made use of occasional baby-sitting from family members, but I mostly relied on homework.  One thing that I found worked well was to make an effort to ensure that trips to the university were a fun activity for the kids, so that they would be in good spirits.  This meant having a routine where we would always go and get a treat after my supervisory meeting.  That meant that they had something to look forward to and I also had something to "bribe" them with to stay on their best behaviour!
I found that dealing with grad-school was largely a matter of organising my research agenda in a way that required as few attendances as possible, which meant that on each visit I needed to give myself enough material to do over a month.  The experience of full-time study plus raising children kept me busy, but it was less hectic than if I had been trying to work a full-time job plus instead of doing grad-school.  I found that this was one of the major advantages of grad-school over full-time work; the additional flexibility in attendance and time usage made it easier to spend time raising the kids.  In that respect it was perfect timing; it meant I didn't have to use child-care facilities and I could give my kids a fun childhood at home with a parent.
While I wouldn't presume to know your circumstances well enough to tell you what to do, one aspect of your post that strikes me as helpful is the fact that you and your husband are both in grad-school at the same time.  An option in that case would be to live on campus, or close by, and "juggle" the kids between you to minimise the need for outside care (e.g., one goes to class, the other cares for the kids, then swap).  Obviously this depends on the constraints of your program, so maybe it is infeasible, but it is worth considering how well this could be done.


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Deciding between cursive and print handwriting
I was taught cursive in elementary school but was discouraged from using cursive by an English teacher in in a non English speaking country. At least I took his/her comment that “not many people use cursive these days” as a sign not to use cursive. Later I practiced and adopted a “connected print” style, because I feared there might me legibility issues for standardized tests. In college, naturally I continued the use of connected print. However, this is slow and laborious, so if you use this in handwritten exams, your mind is distracted from thinking about the question.
How can I choose which style to use? Does it depend on the professor? Is there any evidence that professors prefer either style?

Have you considered typing your work?

Most in-class exams are in written form though.

At least I took his/her comment that "not many people use cursive these days" as a sign not to use cursive. – Of course a lot depends on the tone here, but have you ever considered that you completely misinterpreted a mere expression of surprise or even compliment here? Would you think analogously about “Not many people can multiply four-digit numbers in their head nowadays”?

@guest Bring a mechanical typewriter ;) - Noise might be a problem though...

Most professors prefer handwriting that is legible.
I have seen some (asian weirdly, all other nationalities tend to a larger style and there are 90+ nationalities in the establishment) students with handwriting so small it is difficult to read but perfectly formed though.
Some write cursive others like small caps but all are fine when neat and legible.
The issue is always the “spider scrawl” that is not legible and so poor that even the author can’t read it later.

Professors are people, and people have various preferences. Ask your professor if it’s preferred to use hand writing for assignments and you will get your answer.

While there may be a very small minority of professors who has a preference here, I am quite confident that most professors do not care at all as long as it’s readable and will tell you exactly this. Moreover you risk leaving the impression of somebody who cannot make their own decisions and wastes their time. I therefore would advise asking professors. (Mind that am not accusing the asker of not being able to make their own decisions. Asking the question here is a way to find out how to make a decision.)

@Wrzlprmft I agree completely, assuming you mean I therefore would advise NOT asking professors.

@Wrzlprmft Seriously? Any professor that finds a straightforward question asking for their preferences a waste of time deserves to have their time wasted.  Just ask.

@Kimball: Indeed.

@JeffE: Everything can be overdone. Just imagine every student would ask for one such detail, let alone every detail on that level (choice of paper, choice of ink color, variant of English, …). Moreover, here the question is mostly orthogonal to what is actually important for most (readability and efficiency). If anything, you would have to present the professor two samples of handwriting.

There is a cultural component to this as well, so this may vary between countries.
In France for instance children are taught to write in cursive. When I was a kid we had calligraphy classes, now it is just the cursive.
So when someone in France thinks "handwritten document", they expect cursive.
Of course, if the document comes written the US way (print handwriting) it is fine. If it comes in ALL CAPS then it is weird.
The most important part is for it to be readable (except if you are an archeologist, or a medical doctor - which seems to be a world wide tendency. A scary one if you ask me because I cannot think of another job where WIRIWIEAICKM (What I Read Is What I Eat And It Can Kill Me - but I digress)

While there may be some odd professor who has an actual preference for a handwriting style per se, the more relevant factors are whether your writing is easily readable and whether it does not distract you too much.
I therefore suggest to do the following:

Produce samples for each of your two handwriting styles. Impose a time limit. Also, make it a mental challenge, for instance try to reproduce a piece of information from the depths of your memory or translate a text into another language. Make the challenges for each sample as similar as possible, but not identical to avoid a bias towards whatever you do second, e.g., do not recite the same poem twice, but use the odd verses for one sample and the even ones for the other. Ideally let somebody else surprise you with the challenge.
Show the samples to a friend who is not intimately familiar with your handwriting and let them judge their readability. If they consider either sample considerably more readable, choose this.
Should both samples score equally in the previous step, go by the handwriting style which you felt to be least distracting. If there is a significant difference in the number of mistakes you made for one sample, take this into account.

Whatever the outcome, stick to this style from now on to train and optimise it.

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First 6 months PhD progress presentation
I have to give a presentation about progress in my PhD after the first six months. I am not sure what is expected from a PhD student at this stage. I have done mostly literature review and a few initial experiments with the existing technology.
I am planning to divide the presentation into different sections such as background/importance of the research work, problem that needs to be addressed and possible approaches.
It would be nice to get some ideas about such presentations.

What does your advisor or program expect? I would look at see what other students in your research group or department do. The answer to your question seems to depend upon your specific situation.

Don't ask us; ask them.

Having recently gone through a 9 month review for my part-time PhD (so really 4.5 months in) I can give you an idea as to the approximate sections I had. It depends on what format your institution decides to use, and you'll have to look that up for yourself. Mine was a relatively formal presentation to my supervisors and an independent Chairperson who wasn't necessarily aware of my work (but is constant throughout the PhD process).
I discussed the following topics:

Introduction to the problem space.
Ideas about specific research questions (may not yet be defined).
The beginnings of a literature review: notable results, papers, or individuals.
Preliminary research: any results, simulations, theory, or suitable work that you may already be putting in (field dependent).
Proposed future work that will help either answer the proposed research questions or else guide their formation.
A "Project Management" perspective: plans for completion, awareness of deadlines, risks to completion. The last of these was something that was regarded as high priority.

In my opinion the key things at this stage would be to show that you a) are making solid progress and b) there aren't any major barriers to your completion. No one is expecting you to go in to this presentation as a world-leading authority in your field after 6 months. As I'm not a PhD reviewer there may be other criteria, this was what I was advised to focus on.
As said elsewhere though, there should be guidelines at your University or else ask other students or your supervisor about typical content. Depending on who is present remember to pitch your content appropriately. Your direct supervisor(s) will be relatively familiar with your work however if there are outside assessors they may not be aware of your work or even particularly knowledgeable about the problem.

Generally speaking, what your supervisors want to see is that you are not completely lost, but instead have understood the problem and know where you are going. So my suggestion is to show them exactly that and convince them that you are on the right path.
From what you are writing, it sounds like you are doing good progress. Understanding the problem is usually the first big hurdle with PhD research. The second is defining one or more research objectives that are achievable with the resources and time you have available during your PhD.
You say you have already reviewed existing literature and started running experiments, so that should have given you a sufficient understanding of the current state of the art in your research field. What I suggest you do now is to try and define realistic research objectives that you believe you can achieve within the time at your disposal.
The layout you suggested sounds good to me. Include:

introduction with description of the problem you are trying to solve
previous research and existing solutions to the problem
description of the experiments you have run and presentation of your preliminary results
plan of research and the next steps you will take

Obviously, first consult any specific guidelines your faculty / department / research group might have regarding the preparation for this review presentation. Good luck!

Sounds good. I don't think that people expect you to already have lots of results after 6 months; if you have ideas what to look into and why that is important and interesting, that is not bad at all.
Apart from that, this is a good question to ask your advisor, he/she knows the rules and regulations at your university better than random people on the Internet.

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What kind of fonts can I use for academic presentation?
Many videos and documents say that we should use Arial as the font for academic presentation. However, I think Arial is really ugly.
Certainly, there are other fonts suitable for academic presentations. How can I recognise them? Is it just every sans-serif font or what do I need to consider?

This is probably to some extent a matter of taste. But for all things concerning academic design and layout, Edward Tufte is a classical go-to reference.

If your presentation is not about fonts, any boring font is suitable.

Not Comic Sans.

One advantage of a hideously ugly font is that you will know if someone swipes your slides and posts them online! ;-)

I take it as given that you won’t use typefaces that are not suitable for an academic setting at all, like a comic or blackletter typeface, i.e., any typeface you that is not suitable for a printed poster either.
With those constraints, the main thing to consider is that your typeface must render well on a projector or via screencast.
Interestingly, those different settings lead to similar conclusions:

You have to expect that projectors have low resolutions (and no sub-pixel hinting), which causes intricate details such as most serifs look ugly.

For screencasts, you have to expect that they will be scaled on the viewer’s side, which again causes problems with detailed components such as most serifs and works bests with straight lines and similar.

For this reason, most sans-serif typefaces are well suited for presentations while serif typefaces are not. However you can find exceptions such as organic grotesques, which are sans serif but scale badly and render badly on low resolutions – or slab serifs, which work well with scaling as well as on low resolutions.

Does anyone know the name of the four example fonts in this answer? (Especially the two "good" examples)

@6005: The fonts from top to bottom are: Aakar, Ubuntu, Linux Biolinum and Zilla Slab. However, please note that I chose them for highlighting the aspects relevant to this answer, and not to endorse (or attack) these particular fonts.

Thank you! Understood yes

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A student offered me money to take one of his exams in his place. What should I do?
Briefly, I am currently offering my services as a math tutor on a dedicated website.
Recently, a university student contacted me and offered me money to help him cheat an incoming exam. The arrangement would be easy since the exam will take place online, due to COVID-19 (the student would send me the exam text and I would send it back to him, once completed).
I have refused due to ethical reasons. Now, I have identified the precise university and course, and I am wondering if I should warn the course professor that at least one anonymous student has attempted such an arrangement.
I have thought some arguments pro and against:
Against:

such kind of cheating is obvious and warning the professor would
serve no purpose. I would just annoy the professor.
It could happen that the professor will ask me to identify the student. I don't know the student's name, but I have some information
about him that could identify him. Now, in this case, I would refuse
to attempt to identify the student because 1) no actual cheating has
happened yet and 2) it is a can of worms I don't want to open 3) I
don't want to see anybody reprehended, I just would like to prevent
the cheating from happening

Pro:

there are ways to prevent the cheating from happening (browser lock +
full webcam view of the student would make this kind of cheating
quite difficult). Thus the warning is not meaningless.
Even if the professor has already considered the possibility of such
an arrangement, it is still the right thing to do, and the professor
won't be annoyed in either case.
Realistically, the professor won't ask me to identify the student.

These are my thoughts about the matter. I am open to advise. Especially, I would like to know the opinion of actual university professors, if possible.

Related https://academia.stackexchange.com/questions/151571/is-it-even-useful-to-report-cheating-anymore https://academia.stackexchange.com/questions/151416/what-are-best-practices-for-reducing-cheating-in-online-tests

My advice would be to inform the professor that "students" have contacted you with improper requests such as ...
You were correct to refuse the student, but you may have an obligation to keep them anonymous, as you suggest. That would be true if you have a client relationship with them already, I think.
But the university needs to become aware, if they aren't already, that they need better procedures in place to assure academic integrity. At this time, many are trying (and failing) to get it right and your mail might be a goad to try harder.
You can refuse to help identify the student, but you can certainly make suggestions about improving security.
If your website or other contact methods don't already say it, you might put up a notice of some kind listing what you do when asked to help with cheating.

@TheoreticalMinimum, there is also the case where the person isn't a customer, but just making an enquiry. And I agree, they need a heads up on process, not on individuals.

@Buffy, thank you for your advice. In the end, I send an email to the professor, he thanked me and didn't ask for additional information. He said that the intended way to cheat probably wouldn't have worked, but he will pay more attention nonetheless.


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Is research a viable business model?
I have had the suspicion that it may be for a while and apparently not all is a product of my mind. Let me quote from an answer:

In my experience, in UK and other European countries, the research
  funding comes from successful proposals to the relevant funding
  bodies. There are research centres that were established and keep
  going only because the staff there constantly submits project
  proposals (somebody told me that the success rate is 1 out of 5 or
  maybe even lower).

There are two questions here.

Can a company feasibly focus on obtaining funds in publicly funded research (as a business model) successfully enough to "survive"?
Can such a company be started (nearly) from scratch?

In short, the company would be exactly like a research institute (or institution) except that it would be private.
Reasons why question 1 may not be feasible:

I don't see any company doing this kind of thing, i.e. there may be some, but there are not many, which means that it may be hard. It's a bad sign.
Public funds seem to be assigned to public entities, while companies can benefit from the collaboration and synergy, but they are expected to get their funding from their work as companies (searching for customers, etc.) In this case the customers would be the partners in the projects and the society itself, but again, this seems to be an "innovative" (maybe naïve, or even plain stupid) idea.
Research is a means for something, not an end on itself, that's why the business model should be on something else (point two) and that's why such a company would raise eyebrows on the mere idea of its existence. It may even be against some kind of tacit rule or even written laws.

Reasons why question 2 may not be feasible:

No previous history of success of the company, or products or anything means zero (or negative) trustworthiness and no projects assigned to the company.
No partners would like to associate with the company in a project for the reasons in point 1.
The most similar case I can think of are spin-off companies that are created from successful research labs, not from scratch.
OMG so much communism! Go to kickstarter you hippie!

As an example, a possible scenario that could be close to this: Someone writes a paper about a software system that does something not very novel in the state of the art but in a way that is very different from an architectural point of view, leading to good results in practical terms. In short: in theory nothing is new, in practice what was just a dream is now a reality. What is done remains the same in theory, but how it is done is completely different in practice (and now it works). Unfortunately only a proof of concept (PoC) can reasonably be implemented.
Would it be feasible to request funds to continue the development of this PoC (still very far from a commercial product) as a start-up or that simply doesn't make sense?

The title question is like asking if cats are a reasonable dessert topping.  Research is not a business model at all.  Applying for research grants, on the other hand....

@JeffE well, what I want to ask if I can offer research as a product (which implies papers and in my case software, which again in this case would be open source). I have seen great funding spent on software projects that are not usable, not used, not open and it really seems a waste of money, IMHO. So I thought making something public and focusing on software quality (over publications) could be much more useful and good for everybody, a possible business, however it seems that: "this is strictly against official funding rules". Therefore it seems to me that public research is doomed by law.

@JeffE in short, the business model would be "producing research", and "research" would not be a business model but a "product" (done in a completely public and open way for the common good), does that make more sense to you?

Lucent (AKA Bell labs) made a business of research for a while, and there are any number of consulting R&D firms, some quite substantial. The trick is having the skills and tools to do the R&D that someone is willing to pay for. This generally means things of interest to some branch of government of major industry; the oil and gas industry funds quite a lot of R&D as does the automotive industry and agribusiness.

Yes, but the key component of R&D that makes it a viable business is the &D.

@JeffE outsourcing is a big trend nowadays, for 'R' and for 'D', however so far I've only seen outsourcing for 'R' going to universities. (Here) The salary for a PhD student is about 50-66% the salary for the same person in industry, therefore it makes plenty of sense, but maybe there are chances to make things in a different way (more quality, more expensive, "you get what you pay for"), hence my question. This seems to be better aligned with the philosophy in USA than EU.

As far as I am aware there are a few research focused private companies in Germany, e.g., DFKI, Max Plank Institute or Fraunhofer Society

You might look into Mathematics, Inc. sometime.

In Europe, companies exist that primarily live from FP7 or, now, H2020 funding. They rarely contribute much to projects in terms of research, but often handle tangential issues, such as project management, dissemination, marketing, or association with standardization bodies. Their model works because (1) they do things that none of the research partners actually wants to do, and (2) because they are often SMEs, which is generally politically helpful to get your funding proposals accepted. Further, as writing grant proposals is their core business, they usually also have grant writing experts that have the time to actually keep up with the various changes that the european commission is constantly applying to its programmes and rules (something that many researchers struggle to find the time for).
Formally, these companies often camouflage as either consultancies or technology spinoffs. That is, you will not find it on their web page that their core business model is actually to milk grant programmes, as this is strictly against official funding rules (as a company, you can only apply for funding if you plan to commercialise the results, and you are not supposed to make a profit from the project itself). In practice, the project officers seem to tolerate these businesses - for now.

Can such a company be started (nearly) from scratch?

You will need a reasonable amount of seed money, as the H2020 rules require proof that an organization applying for grants has enough financial stability to likely survive over the typically 3-year project duration. I know from one startup that wanted to participate in a project (for actual technology reasons) which was in fact struggling to cross this hurdle. However, if you have the required seed funding, I see no reason why you would not be able to start such a business. Whether it is a smart business idea is a different question, given that you are basically living off of a loophole in the current funding practices, and you can never tell how long this loophole will stay open.
Edit:
I just saw that I missed this question:

Would it be feasible to request funds to continue the development of this PoC (still very far from a commercial product) as a start-up or that simply doesn't make sense?

Yes, at least in Europe there are funding sources for exactly this kind of case. You should inform yourself about the concept of Technology Readiness Levels (TRLs, slide 4), and the different kinds of funding available for each TRL. If you look at this presentation and go to slide 32, there is an overview over different funding instruments in H2020 depending on the maturity of the idea.

Existence proofs in the US: RTI, SRI, Battelle, Lincoln Labs.  Also, there have been many smaller firms that were funded completely from a large number of SBIR grants ($150K to $1M), though the government has cracked down on these "SBIR-mills".

From the perspective of the US, there are many research institutes that operate as a private business entity.  These research institutes can apply for some federal funding in the same capacity as a research at an educational institution.  I see it being possible to start a private company without a lot of capital, although you will need to have a very strong skill set that is in demand.  Whether this is a sustainable model really seems to depend on the specialized skills that the business would offer and the infrastructure that would allow it to efficiently prepare grants. Research-I educational institutions in the US have an incredible infrastructure to prepare and apply for grants that would be difficult to replicate in the private sector.

It may be important to understand that grants for universities are often given to support them as teaching institutions, even if the grant itself is only about research. This means, even if grant seems focused exclusively on research, it is targeted to the educational institution of the supporting country and would not be given to the commercial company, or educational institutions of another country, event if these would be capable of delivering the comparable scientific results.
As a result, while it is not uncommon for a company to join a university on some shared grant, I have never seen a company that would make its major income on such grants. However there are many companies that make business on assisting in research (like sequencing DNA, building curated databases or the like). They major clients are other companies but some richer universities may also order such services.

Thank you for your answer, this is also my impression. Now I'm wondering what does it take to create a university that offers exclusively one PhD program, but there's more trolling than business there...

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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Should I disclose my mental illness and medication in a PhD position interview?
While I was doing my PhD in my previous position I was diagnosed with a mental illness. I started medication however as a result I could not concentrate very well and it made me quit my previous position. I continued my medication and recently have reduced it. Now I think I am able to concentrate again.
Soon I will have an interview for a new PhD position. I was wondering if I should bring up the matter. On one hand, I think I should be honest to my future supervisor. On the other hand, I don't want to lose the chance by scaring them.
Would you please help me with your opinions?
If I shouldn't bring it up myself, what if they asked me about my previous position? Should I tell everything then?

There is an intermediate option that tells them what they need to know: "I had to quit because of a medical condition that is now under control."

There is no requirement to disclose and given the current climate around mental health, I would not suggest disclosing.
I would say that you had health problems that resulted in your having to leave your former school, but that these issues are under control and you are confident you will succeed at your new program.
I would be sure you tell your letter writers to also use the vague rubric of "health problems" as some may inadvertently disclose without thinking about how you want to be framed.

I don't think being vague is a good idea, since anyone with a partially working BS detector can find weasel words and will not only assume the worst, but also doubt the communication is sincere.

Medical issues are none of our business. We cannot and should not ask to violate the medical privacy of our students.

Medical conditions that affect ability to study are the school's business, for a start both sides ought to want to make sure that appropriate support is provided so that the student is able to study.  I agree that the School cannot ask for medical information, but that doesn't mean that it is not in the student's best interests to provide it.

My answer to this question borrows heavily from my answer to this question about discussing a life-threatening illness:

If you think it helps explain a work or productivity gap in your career, I would mention it and I would do so in writing rather than let your prospective employers speculate. Because overcoming a major mental health challenge can help you align your priorities and strengthen you in other ways, doing so can definitely be done in a way that leads one to conclude that it is a strength, not a weakness. If they ask about it, answer clearly and in a way that describes this a strength.
If your previous condition is not relevant in these ways, I don't think you have any obligation to bring it up. Reminding prospective employers of mental health issues can open to the door to (illegal) discrimination based on your medical history and I don't think you are helping either yourself or your prospective employers by bringing it up.

My personal opinion is that I'd rather you tell me right away. It doesn't scare me to know that there is an issue, but it scares me if there are issues I don't know and that I don't know how to handle.
In the end, you and your adviser are going to spend a lot of time together, and you need to be able to work as a team. As an adviser, I'm going to find out one way or the other at one point, either because you're going to tell me once we have built up a relationship of trust, or because we come upon issues where you find yourself not being able to work at the level you are supposed to and where I will start to suspect something. Better to talk about it up front so that both sides know that there are constraints within which the adviser-advisee relationship will have to operate.
(As a postscript: I don't expect to get a complete description of your illness. It is sufficient if you say something of the form "I would also like to mention one issue that I believe is important for you to know: I have some medical issues that I think I have under control now with medication. However, they do impose some constraints on me; in particular, I cannot do X and I will need accommodations for Y.)

If you have a list of specific academic concerns that are relevant to your mental health on an ongoing basis, e.g. about working hours, various pressures related to research and publication, the hours-per-week availability of this potential advisor, etc., you should definitely ask about those.  You'll likely impress the interview panel sufficiently with your forthrightness just with that.  No need to get into your previous degree program and personal life at all, unless they ask, and they probably won't.  If the university ends up making you an offer, HR will probably be oblidged to ask you about your medical history in a form.
If you're curious whether the university has counselling support, or what other outside options for mental health support there are locally, there will certainly be someone who can answer that, but your future advisor might not have a clue what the options are.
And if you have doubts about whether you can actually make it through the programme, then I wouldn't dump those in the lap of your advisor, but talk with a mental health professional.  By the way, lots of academics have moderate mental health issues, according to this series in the Guardian.  Like for people in any field, a lot of this is "manageable" but for some it is devastating, it all depends on the specifics.  In any case one does well to put health first, though that's not always easy.

I’d strongly suggest that you not disclose your former problems, as it doesn’t help at all to reveal them.
Remember, that, like any other recruiter, the professor hires the single person of which he expects the best performance in the job. “Mental problems” have the potential to draw doubts on your ability in doing so.
Moreover, you are not obliged to reveal any informations you don’t want to reveal, even not when asked (particularly regarding your health). That is not only yours, but also the recruiters’ privilege (and they usually exploit it – you’d be surprised how many unmanageable bullshit topics are assigned, which lead to years of headaches and finally often to the cancellation of the PhD).
If it is obvious, say from your CV, that there must have been some problems, call them “private reasons”.


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How to make good use of a small startup fund?
I'm starting a tenure track position (in the US, computer science) in fall and the position comes with a startup fund that is insufficient to employ any (postdoc) staff and PhD students are funded directly by the department. Also, my conference travel is taken care of by other funds.
How can I use the (limited) funds that I have to benefit my career?
Edit: I'm mostly working in theoretical research (algorithms).

How limited? What country? What kind of CS? Do you need computers?

In the US. Mostly theoretical research so I don't really need lab equipment.

Any limitations imposed by your Chair or Dean? Do you have to spend it in a certain time frame, etc.?

2 years. Otherwise no limitations.

So essentially all expenses except postdocs are covered by the department? What is startup money usually used for?

You haven't mentioned summer salary for yourself.  Are you already funded for summers?  Would your department willing to consider a "buy-out" of some of your teaching load?

What (if anything) are your colleagues in a similar position using it for?

Informed guess: what about computers for you or your students? Is there any office equipment that you need? (Whiteboards, tables for standing while working, etc.) - these may the things that can be covered by the fund.

Many options.  Pay for your students' conference travel.  Get your office, and your students' office, improved so you will look important.  Hire an artist to illustrate your work and get the illustration on the cover of a journal.  Get a nice research group website made.  Hire an undergraduate research or office assistant (much cheaper than a postdoc).  Bring in outside seminar speakers.

@AnonymousPhysicist Why not make your comment an answer?

For those not familiar, Theoretical Computer Science is mostly formal mathematics. Thus the success patterns for research professors are nearly the same as those in Mathematics. In particular, research collaborations are critical.

How can I use the (limited) funds that I have to benefit my career?

There are ideas in two categories that can benefit your career: 1) build fruitful, productive research collaboration relationships; and 2) professional service in areas of critical need. (Nearly all tenure committees and funding agencies consider "service" or "broader impacts" as one of the major criteria for tenure or funding.)

EDIT: These ideas are unconventional and represent a particular set of values.  They value long-term benefits over short-term.  They value making a difference in the academic community over immediate personal benefit.  If you have different values, then you'd make different choices.

For the first category, you could use the funds to sponsor or host activities that will expand your research opportunities, especially build new collaborations.
For example, you could host a series of workshops that bring together researchers that don't normally work together.  These researchers could come from your department (if large), from other departments at your university, or from other universities.  Because you host the workshops, you can organize them to meet your objectives.  Maybe they are oriented toward a "challenge" (a la "hackathon"), or maybe oriented toward writing interdisciplinary research grant proposals,  or maybe you give each other tutorials on your specialties, hoping to find fruitful intersections.  For a good source of topic ideas, read the "Dear Colleague" letters from Program Mangers at NSF, and also the NSF program solicitations.
It may be there is already some workshop or conference that is close to your interests.  You could use your funds to host an add-on event.
For the category of professional service, you might consider these two ideas:

Host a series of workshops for CS majors at your university who are in under-represented groups (women, minorities). The goal of the workshop would be  help them with the personal, professional, and practical challenges they might face at your university.  If you don't know much about this topic, then you should recruit experts as presenters and facilitators.
Find your nearest Historically Black College (HBC) and co-host a Theoretical Computer Science workshop with someone in their CS department, aimed at students from both institutions.  You'd have to spend time to learn about the HBC, what their students are like, and how to usefully engage them in this topic.  In addition to benefits for the students, this could lead to an unexpected research collaboration for you.

I know CS is often different, but they seem like awful ways of spending startup.

@StrongBad - you are entitled to your opinion, but you do not provide any reasons why you think these are "awful".

I applogize for not adding more detail. Again CS and Math maybe be different, but I think that anything that does not lead to publications and funding prior to the tenure clock running out seems like a bad use of time and resources. I do not know any new TT faculty that have time to organize a workshop, let alone a series of workshops. Finally, workshops seems like something you could extra money for later.

@StrongBad Thanks for clarifying. I understand those values.  The question OP might consider is: Do I want to be just an average researcher, or do I want to be extraordinary in some way? If the latter, then some novel approach is called for. If he/she is not already closely connected to top researchers, then building new collab. relationships will have high ROI via high impact publications.

@StrongBad Put another way: why is Computer Science (and academia, in general) in the state it's in? Partly because too many junior professors put all their attention on getting published and minimize attention to everything else. By the time they are tenured, their habits and values are formed, perpetuating the status quo.

The term "small startup" is rather vague. As you say it will not cover a post doc, I will assume it is less than 50k USD. It also sounds like your equipment and research costs are negligible. The goal of a startup package, as the name implies is to help you start up. One expensive aspect of getting started is covering your summer salary. With 50k you could cover your summer salary for 2 years while you get started and apply for grants.
In addition, or as an alternative to, covering summer salary, I would want to invest in technology. I could image dropping 10k+ on "computers" for myself and future staff (maybe 3 desktops, a laptop, and a tablet). A scanner and printer in your office is also super helpful. A backup system (e.g., external hard drives or a NAS) depending on how IT at your university works is also important.
Depending on your field, you want to make sure you have enough for page charges, article processing fees, and open access fees. In my field see fees can hit 2k an article.
An RA can be super helpful. Having someone who can help you prep lectures can be a huge time saver. They can go to the library for text books, scan images, proof read slides, and deal with the book store for your reading list. Similarly, they can help with research by proof reading manuscripts prior to submission and page proofs, make figures look nice, get articles from the library, do literature searches, and help you put together conference presentations. They might even be able to do some real research. My guess is, in a theory based field, you could keep an RA busy for 10-20 hours a week. Cost would depend on the qualifications, but the cheapest would be an undergraduate work study student and more expensive would be someone with a MS who want to do a PhD at some point.
You will want to be able to attend some conferences, but realistically, you are likely to be swamped.


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I am so tired and un-focused in my postdoc. Is quitting my position a good choice?
About 6 months ago I finished my PhD and started a new postdoc at a prestigious lab at a prestigious university. I was very burned out as I completed my PhD, but I hoped starting fresh I'd find renewed enthusiasm.
However, things started bad and have just gotten worse. I like the university and city and would prefer to keep on for at least a full year, but I'm having a very difficult time concentrating on my work.
My poor performance stresses me almost more than anything else - after 6 months with little to show for myself, I'm afraid of leaving a bad track record. I feel that my postdoctoral advisers just think I'm confused or stupid, but in truth I'm having a terrible time making myself work.
I have trouble keeping my focus on journal articles and it takes me hours to write short to-do lists just because I keep getting distracted. During research related discussions I tend to "zone-out" and start questioning why I'm even there, totally losing the thread of the conversation.
I know that I am actually a capable mathematician and researcher. I'm not sure what's happened to me, but I know things can't continue like this.

Counseling can help a lot with issues like this.  See if your institution has an employee counseling program.

Somewhat related: How should I deal with discouragement as a graduate student?

Is the university you got you PhD from also a prestigious university?

Maybe you should take a short vacantion

Nobody here can tell you if quitting is a good choice. Voting to close the question.

6 months with little show - this is pretty common for a postdoc in some fields, where it can take as much as a year to get on the right track.

@CapeCode despite the titular question, I think the OP is asking is this common and what has happens to him/her.

It takes years to get over getting a PhD. It sounds like you are having a more difficult time than some. A therapist might be able to help with the issues. At a minimum, tell your supervisor what is going on. You talk only about your work, but you need to think about how the change of city is effecting you personally. Are you living in the lab, or do you have new friends? Often during the PhD process we drop social activities that we enjoy, it might be time to start these up again.
Now that you have a PhD and a Postdoc, it sounds like you are in it for the long haul. The key is to make sure you balance the personal and work aspects of life.


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Reproducible and exact calculations vs. approximate and slightly random results in experiment
When experiments are performed and reported in an academic article, I learned that reproducibility is important. I am implementing a system where I stand between the choices to use GPU acceleration to perform certain calculations, where reproducibility can not be guaranteed, or to perform the calculations on the CPU, whereupon the calculations are exactly the same. The problem with using the CPU is that it is much much slower. However, it seems that the calculations on the GPU are about the same at each run.
I have the perception that researchers sometimes have to choose between qualitative or quantitative measurements. This may seem obvious to experienced researchers, but what I am asking is if a possible solution would be to perform a number of measurements on the GPU that provide estimates, and then calculate an average of the results? Is this "scientifically accepted", although calculations depend to some extent on randomness?
I should add that the results are only going to be part of a project at bachelor level, but I'm also interested in how it works in "real life".

@Saturnus you mean when presenting the results? The thing is that running on the CPU will probably take many hours, if not days. I could do a few runs, but as I have very many parameters to adjust, doing all combinations of parameter setups would not allow me to present a complete set of data for the CPU runs.. So basically I am asking if I will be "failed" for not showing the exact calculations. I know that is probably hard to answer as it is completely up to my examiner (this is a thesis work).. But besides my specific thesis case, I am still interesting in how these things usually are done.

So, what exactly is the problem with using GPU acceleration?

@101010111100 to be specific, I am implementing a neural network model using Keras API which runs on top of TensorFlow which uses GPU acceleration. The exact reason for the randomness is maybe a bit off-topic in this question, and to be honest I do not exactly know the reason. There are many threads or topics on other websites where people discuss the problem, and the vanilla solutions such as seeding consistently won't work for anyone. Another solution is to switch backend to Theano which I am about to try out now. However, this is probably questions for some other stack-site..

@StephenJohnson, by "the exact reason for the randomness is maybe a bit off-topic in this question" do you mean your process non-deterministic? If so, then surely runs may not be alike, regardless of the environment (CPU, GPU, ...)?

@user2768 thanks for your reply, I am sorry I do not exactly understand your question. The thing is like this: CPU: Computations will be serial, and hence they will result in the same answer. GPU: Computations may be executed in different order, so results may differ. Also the architectures treats floating points differently. As I have understood, the GPU rounds floating points to a higher degree (now I am almost guessing)... But anyway, I don't want this topic to become too technical. I am mostly curious about the academic point of view and the "liability" of results.

Can't you provide a confidence interval aroung GPU computations? Something like bootstrapping? I think that's what would be academically expected of measures that varies...

I would recommend that you pull up ~3 computer science journal articles that depend on GPU processing and see what they do. As an undergraduate you should have (possibly digital) access through your school library.

It's probably best to answer a generalised form of your question first before getting to specifics.

Reproducibility is a tricky issue in applied Computer Science but the principles are the same.
The first thing you need to consider is what, precisely, the results of your experiment depends on:

Does it depend on hardware? (e.g., performance experiments)
Does it depend on data?
Does it depend on software? (e.g., an implementation of an algorithm)
Does it depend on configurations? (e.g., amount of memory set)
...

For whatever your experiment depends on, in an ideal case, reproducibility should make those materials available to third parties, either through links from the paper, or as details in the paper itself. However, hardware in particular is often a tricky issue in that you're probably not going to make the  machine you ran the experiments on available. For this, it is typical to try use conventional hardware insofar as possible and to provide details in the paper.
And sometimes there are practical obstables for even sharing data or software, such as commerical interests, patents, licencing of the software used, and so forth.

In terms of reproducing your results, another aspect to consider is the stability of those results. When someone reruns the experiments, you would like them to see the same (or "negligibly different") results as you published. This means that, for example, if your results vary in each run, you should publish some bound or confidence interval on each run to give an idea of the distribution of results over each run, or you should take a measure like the average of multiple runs to ensure a stable enough result from which to draw stable conclusions.

However, what does "negligibly different" mean? Well while results should be "as reproducible as possible" (one will never get the exact same runtimes, for example, in a performance experiment), what is more important to the scientific method is that conclusions are reproducible. For example, if a bunch of doctors produce a study of 1000 patients showing a significant and strong correlation between eating popcorn and cancer, it is not necessary that the details of the study be reproducible but rather it is even preferable that the correlation be reproducible (and perhaps strengthened in a further study to look for causation by isolating the bad part of the popcorn and injecting it into some unfortunate mice or something).
So if you have general conclusions, then you might want to think about how reproducible they would be on different hardware, on different data, on different software, with different configurations, etc. If you don't know how the results would change when a particular variable changes, then you need to include that variable in your conclusion. That is to say, if you don't know how the result would change for different data, for example, then all you can conclude about is the data you've experimented with and maybe propose a stronger result.

Of course, almost all applied CS papers I've seen (including my own) don't stick to these rules because peer-reviewers don't hold them to such standards, other than in the most blatant of cases.
And it is exceptionally difficult to account for all variables in a thorough conclusion since in applied CS there's so much to take into account, particularly for performance: the machine(s), the programming language(s), the compiler(s), how good the programmer was, possible bugs, the data, other things running in the background, caching, ... hence reviewers tend to be a little more relaxed (perhaps sometimes too relaxed).

Summary: Publish both results if you think they are interesting. Publish as much material as you can to allow the results to be reproduced. If you're worried that the GPU results are too variable in each run to be reproduced, take the average of multiple runs to get a more stable result, or provide an estimated upper and lower bound, or something to characterise the variance.
But all of that is just the icing on the cake. The real goal of reproducibility is to be able to reproduce conclusions. Be careful to craft conclusions that do not overgeneralise the data they are drawn from.

I'm no computer scientist. But it seems to me that you have two methods,
Method A is fast but has some random error.
Method B is slower but more (totally?) accurate.
One approach, then, would be to determine what level of error is acceptable in your outputs, run a small experiment with both, and look at the differences between the results of each to find the level of error that is present in method A. If the level of error that you find is less than that which you decided was acceptable, then you can go with A for the speed.


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Does everyone who is doing a PhD has to dabble in philosophy to a certain extent?
Does everyone who is doing a PhD has to dabble in philosophy to a certain extent?
The question is irrespective of the field of research.

Does everyone who is doing a PhD has to dabble in philosophy to a certain extent? -- Not that I'm familiar with, but the world we live in is large and diverse; can you clarify where in the world you are?

I can say no, but doing that would help you in building your logical thinking.

@Mahran - Do you mean would not help you?

Depends on what you mean by "dabble in philosophy to a certain extent". All educated human beings "dabble in philosophy" to at least some extent, whether they realize it or not.

Philosophy comes from the greek for love of wisdom. In that sense, yes; doing a PhD should require a love of wisdom. In the modern sense of what the department of philosophy does, no; doing a PhD in computer science will not require you to have anything to do with the philosophy department.

@Thomas I agree except of what the department of philosophy does... that is quite misleading and depends of your country, in the USA and Western Europe maybe half of the world, there is the only analytical approach of research at philosophy departments. Continental Europe have also their own method.

@SSimon I have absolutely no idea what the philosophy department does and I have a PhD in Computer Science. That is the point of second half of my earlier comment.

The meaning of "philosophy" has changed since Newton kicked of what is now called "Newtonian physics" by publishing "Philosophiæ Naturalis Principia Mathematica", "The Mathematical Principles of Natural Philosophy".

No. This is a misinterpretation of what “Ph.D.” means. The full title of the degree is Philosophiae doctor, technically a doctor “of philosophy.” However, this does not mean "philosophy" in the modern sense, but rather someone who pursues knowledge (“lover of wisdom”—the source of "philosophy"), not necessarily someone who studies philosophy.

+1. You could add that the more modern meaning use of the word "philosophy" to mean "what the philosophy department at your university does" is quite new, 100 years or so. Just about everything that isn't medicine, theology, or law would have been considered philosophy, hence the separate academic degree titles for those fields (not that there couldn't be some overlap, of course).

For a long time, what we now call natural science was called natural philosophy.  For example, Newton's great book on physics was titled "Philosophiae Naturalis Principia Mathematica".

I find it difficult to see how you could do a Ph.D and avoid philosophy altogether. You're a scientist? Cool, you need to study scientific ethics and the philosophy of science. A mathematician? Mathematics and philosophy are conjoined at the hip. Law or political science? Again, ethics, but also political philosophy. Theology? Philosophy of religion. And so on.

@ubadub “You're a scientist? Cool, you need to study scientific ethics and the philosophy of science.” -- No, I didn't. Neither did any of my colleagues, as far as I know.

@Pont OMG, really? what is the name of your institution? It is strange if they didnt teach you about plagiarism, ethics, research methodology, logic, history, social implications, etc

@SSimon: I went to and worked at multiple schools, none of which offered such training.

@SSimon The University of Otago, since you ask. There was no required taught component whatsoever to my PhD, which I believe is a fairly common state of affairs at non-American universities.

@aeismail math?

@Pont curriculum available on their website defer with your statement

@SSimon I'm unsure why you seem to think I'm lying about my own PhD, but feel free to consult the university's PhD handbook, which states: ‘There is no course work… Candidates are not permitted to take additional courses… The degree of Doctor of Philosophy at the University of Otago is acquired solely by the submission of a thesis…’. In other words: not only did I not study philosophy during my PhD -- I was in fact forbidden from enrolling in philosophy (or any other) courses during my doctoral studies.

@Pont so why they put explanation that thesis suppose to be original, novel, and logical?

question was if dabble, the link you provide is full with rules that confirm OP questions

@SSimon I think you've forgotten what we're discussing: ubadub and you claim that "you need to study scientific ethics and the philosophy of science" to do a science PhD. I've disproved this claim.

@Pont actually, you proved it. I am shocked you think we need a special course for it to be counted as learning.

@SSimon I've offered personal attestation and documentary evidence. If at this point if you'd like to go on imagining that I sneakily self-studied philosophy (or for that matter eschatology, campanology, or hierographology) during my science PhD, and that I'm trying for some reason to conceal this fact, then I can't really add much except to wish you much joy in your imaginings and a happy New Year :).

@SSimon: Understanding what’s ethical behavior is not the same as “dabbling” in philosophy. You don’t need to read Kant or Aristotle or Hobbes to get the basics of what you need as a researcher, when by and large the Golden Rule tends to be enough to steer you in the right direction.

@aeismail understanding or knowing? we are required to know all processes and points of it, plus methodology, plus there is not only science PhD.

@SSimon “We are required to know all processes and points of it.” Say what now? This is a joke, right? We’re not expected, let alone required, to know everything. That’s kind of the whole point of research. Now we are expected to act ethically, but as I mentioned, most of the time in academia, it doesn’t require specific learning to figure out what that is. As for the issue of different disciplines, somehow I suspect a French lit PhD candidate is much less likely to study ethics than a bioengineering PhD.

@aeismail but how you can act ethically if you don't know etic? but French lit going to study more philosophy than any other student, I mean OP question is not clear

No.  In fact, the vast majority of PhDs do not study philosophy in any reasonable sense.

Hmm, I never met PhD student that never study ethics or any sort of ethics, it is strong emphasis now on following ethical concerns. I am surprised by your answer bcs it is rather an exception.

Well now you know me. I am a PhD student in pure mathematics, I read the Wikipedia article on the Trolley Problem once, and that's about the extent of my studies on ethics. I think this is typical of a PhD student in an unrelated area.

@SSimon: I also did not study ethics as a PhD student, and there is no ethical requirement in the PhD program in my department (of which I am the graduate coordinator).  But while students in certain fields do get instruction on "following ethical concerns," this need not be studying philosophy in any reasonable sense.  To me, this sounds a little bit like saying that someone who learns how to use a spreadsheet is studying computer science.

@SolveIt That seems spurious; the field of mathematics (both pure and applied) is heavily informed by philosophy. Some of the greatest mathematicians of the last 400 years, such as Gödel, Frege, Pascal, Descartes, Bertrand Russell (just off the top of my head) are as well known for their mathematical contributions as their philosophical contributions. Most of set theory and a good deal of number theory originates in philosophy, ultimately.

@ubadub Be that as it may, the fact remains that philosophy is not a serious academic interest of most people pursuing a graduate degree in mathematics. A great number of fields have their origins in philosophy. But mathematicians using Cartesian coordinates aren't doing philosophy any more than a software engineer using Lisp (they exist!) is doing philosophy, the influence of Alonzo Church notwithstanding.

@SolveIt we should distinguish between "doing" philosophy as philosophy Ph.Ds do (i.e. producing new research) vs. studying existing philosophy. A software engineer isn't a Ph.D student in mathematics; while a software engineer is just applying programming rules, presumably the math Ph.D is furthering the field of mathematics in a way that generally requires understanding of some of the philosophical background of his chosen field. Similarly, a computer science Ph.D working on Lisp would require a fairly deep understanding of λ-calculus, which is of course a philosophical matter

@ubadub Both perspectives make sense: Philosophy was involved in shaping the framework of modern Mathematics. But nowadays, to do research in Math, you simply apply this readily-available framework. There is no necessity to understand its philosophical influences.

@ubadub My point is that there seems to be little need to understand the philosophical background of a subject to be able to contribute to its modern form.

It depends on exactly what your contribution is; for certain areas, that's valid, but a basic understanding of the philosophy of science and of statistics would probably improve the work done by any scientist. To cite a contemporary example, abuse of p-values is fundamentally rooted in  philosophical misunderstandings and disagreements of what p-values entail.

@ubadub I find this statement more agreeable when the focus is on empirical sciences, in which methodological questions are tied to philosophical discussions, such as the relationship between theory and reality. Math has been the subject of such discussions as well, but the actual methodology is decoupled from them.

@SolveIt field of mathematics is not science, it is much closer to philosophy or it is philosophy entirely (imaginary numbers, quantum mathematics, etc )

@PeteL.Clark you are mathematics? well, you have two, applied and pure. I think your field don't need ethics bcs it is the philosophy for itself. I mean actually, my department have Logic as subject and professors in that field, why your department doesn't have is strange to me.

also, I wonder why in the etical board of university are people from the mathematic field also @ubadub ?

From the Greek, "philosophy" literally means the "love of wisdom".  If we define philosophy as a study that encompasses knowledge, language, and reason, then everything we study touches upon philosophy.  So in this particular sense, the answer to your question is "yes".
However, for the vast majority of PhDs (other than in philosophy, theology, and other related fields) there is no requirement to take any philosophy courses or even to know how to spell Plato.  So, in this particular sense, the answer to your question is "no".

It depends on what is your definition of philosophy.
In my view philosophy is a discussion of 5 elements 1) Yourself 2) The nature 3) God 4) Life 5) Death
If we go by above definition P.hd is studying on at least one aspect. If one can study and understand all above aspects then he is a philosopher.
To answer your question. No most of the phd students don’t study philosophy.


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Is publishing papers with many co-authors detrimental to one's academic career?
I’m looking at some friends’ works, at good labs, in good schools, but some of their publications have 10 co-authors – I even found one with 15 co-authors.
I’m sure the lab and its PI(s) are doing well from such collaborative efforts, but at the individual level, are the PhD students being harmed, because the authorship is spread among so many people?  I wonder if this kills their chances of securing post-docs later on, because they published with a big team of people, and I wonder if this signals that they have not done enough ‘independent’ work.
FWIW, those papers are in medical machine learning.

Highly field-dependent. In my field (linguistics), a paper with 5 or more authors looks atypical and strange. In other fields (I'm thinking especially of genetics and biology and other areas of the hard sciences), one paper might have a gazillion authors.

In high energy physics, papers with up to 3000 co-authors are normal.

@FuzzyLeapfrog Indeed, I stumbled across a paper where the list of authors was as along as the main text!

Bioengineering bounces all over the place. I've seen plenty of solo papers and those with a dozen or so, alike. (3k? Seriously? Yeesh.)

@TheNate look at any paper from CERN.

In some other question, a guy was worried that there was only one person who could write a recommendation for him.  But guess what, that CERN paper means there are 2999 guys who can write a recommendation for you!

As mentioned in comments, the normal number of authors on a paper depends heavily on the field.
The issue with getting a postdoc is that you need to demonstrate your ability to do research. That doesn't necessarily mean you need to be the PI, as in some fields as a postdoc you would still be working on projects driven by someone else.
Having one or more individual papers would be one method of doing that. Being lead author on a paper in a field where order denotes role would be another. But for a PhD student applying for postdoc positions, their references will still play a big part in whether they are hired. Their supervisor should be able to include in the reference what part the student contributed to the paper.

Apart from the fields, in your CV you need evidence of being able to do your own research, and to collaborate successfully. Papers with a high number of authors, especially if interdisciplinary, are evidence of the latter.

As others have said, this is highly field dependent. In my subfield of computer science (called human computer interaction), having multiple authors could actually be helpful. It gives more exposure to your work; for example, the paper would appear on each of the authors' web pages resulting in more researchers seeing your work. The Co-authors are likely to advertise for the paper to give it even more exposure. More exposure means that more people will build over your work and hence this contributes positively to the field in general.
What you should care about is your position in the authors list. This is also field dependent, but in most areas the first author gets the highest credit, the last one or two are seen as the supervisors, and the ones in between are seen as contributors (with contributions of different sizes).


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How do I cite a screenshot from a paper?
There is an image in a paper that I want to use in my master’s thesis. I have the PDF file of this paper and I cant save the image from the file. So I have to take a screen shot. How should I cite the image?

I cant save the Image from the file – unless the paper is profoundly garbled, there are several (free) tools which make this a very easy thing to do, e.g., PDFImages or Inkscape.

I don't understand your question. You cite the paper you got the image from in the same way that you cite any other paper. Are you asking how to actually include that image in your thesis? If so, that's a software support question, which is off-topic, here. Try [su] but they'll need full details of what software you're using.

If you are reusing the image in a document you are writing, don't forget to ask permission to the publisher, who owns the copyright.

You don't cite the screenshot, you cite the paper. If your readers want to look up the source, they don't care how you technically copied the image into your word processor. They want to know where they can find the paper you copied the image from.

It is very much possible and easy to extract the image from the PDF document.
Please use: http://www.pdfaid.com/ExtractImages.aspx
or: https://www.pdf-online.com/osa/extract.aspx
or any other tool you can find online by searching for: 'extract images from pdf'.
Please cite the extracted image in APA style (or other applicable style) as follows:

Figure 2. Male holotye of Hypsiboas gladiator (Kholer et al., 2010, p. 584).
Reference
Kohler, J., Koscinski, D., Padial, J. M., Chaparro, J. C., Handford, P., Lougheed, S. C., & Riva, I. (2010). Systematics of Andean gladiator frogs of the Hypsiboas pulchellus species groug (Annuar, Hylidae). Zoologica Scripta, 39(6), 572-590. doi:10.111/j.1463-6409.2010.00448.x


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How should I mention my affiliation while sending a paper to a journal?
This is my first experience in sending a paper to a journal and I'm not sure how I should mention my affiliation.
In the guide for authors of the journal, it is stated that:

Please clearly indicate the given name(s) and family name(s) of each author and check that all names are accurately spelled. Present the authors' affiliation addresses (where the actual work was done) below the names. Indicate all affiliations with a lowercase superscript letter immediately after the author's name and in front of the appropriate address. Provide the full postal address of each affiliation, including the country name and, if available, the e-mail address of each author.

Can someone write an example please?

What's unclear about those (actually very detailed) instructions? You can probably find examples in other papers published by that journal.

The affiliation is simply the name of your research group, department, and university. Usually, the address is included too. In some countries, laboratories have a unique identification number and they always want to make sure it is mentioned so they can do their own statistics on the number of published papers. This is also the reason why some PIs want the name of the lab to be written in a certain pre-defined format. To make a long story short: (1) ask your PI how he / his university want it. If for some reason this is not an option, simply (2) look at other papers published in the journal you are submitting to and do the same.


text:
How many academic STEM PIs are there in the United States?
Are there statistics that are more specific than the NSF Science and Engineering Indicators that can tell me how many PIs doing STEM research there are in the United States?

u need to request data from funding agencies

STEM includes biology and medicine, right?

Science (broadly), yes, including the life sciences,physical sciences and biomedical.  thanks for asking GEdgar.


text:
Scientific research paper – how broad should the introduction be?
My research answered a very specific question. But the hypothesis I was testing will also likely have very broad application. I want to make sure to convey that importance in my paper. Is the first line of the introduction an acceptable place to do that?
I am thinking the first line of the introduction might be something like:

For decades our knowledge of myTopic has been insufficient to answer questions like A, B, and C. I considered scenario C₁ to test my hypothesis, which now shown to be correct in this case, will likely play a key role in answering these other questions going forward. Some background on scenario C₁ is...

Or should the introduction only mention background info which is directly relevant to the scenario I actually investigated? And then I can suggest the larger importance of this discovery elsewhere in the paper?

Depends on the journal where you want to submit your manuscript. Some want you to be short and specific, others want you to tell a long story, starting broad and then zooming in.

I would pull it off the other way round: Basically you have solved c1, but the implications of it make a huge impact on whole yourTopic. But, as Mark said, it depends on the venue.

The answer to your question entirely depends on your field and the venue to which you will submit your paper. Software Engineering papers, for example, tend to have much longer and broader introductions than Math papers. Papers at smaller and more focused conferences and journals have shorter and more focused introductions that those at broad venues, since they address a more specific readership.

Within the field of mathematics research, there is a bit of a tradition (almost a competition really) to create useful but extremely short papers, with minimal context.  In some cases the introduction is non-existent and the reader is expected to put the result in context through the statement in the title of the paper, and their own knowledge of the field.  This is somewhat tongue-in-cheek, and is a way of demonstrating that valuable results can be given without padding them out with literature.
For example, there is a famous mathematical paper that refuted Euler's sum-of-powers conjecture by providing a short counter-example.  This paper states its objective in the title, and then presents the counter-example in two sentences, without any further context.  This is regarded as a useful paper that establishes the falsity of a major mathematical conjecture.
Another mathematical paper (dubbed the shortest ever) states its question as a single sentence, and then has an answer that consists of two words and two diagrams.  In this latter case, the authors refused to add an introduction to their paper despite requests by the reviewers, since they wanted it to be as short as possible.  (Although this has been dubbed the shortest paper ever, my view is that it is effectively longer than the above paper, since it includes two large diagrams.  Also, the article describing the article is inconsistent with how it was actually published; the editors put the title sentence into the body and gave it a simpiler title.)

For what it's worth, I've noticed a general tendency in mathematics papers published in the last 20 years or so to have much longer introductions about previous and related work that had been the case for the several decades before this. My guess is that this is due to the availability of digital searches using Mathematical Reviews (used to be you had to go to the library and flip through the yearly indexes), JSTOR, google scholar, etc. The effect is cumulative also, in the sense that after one paper digs up lots of background stuff, later papers can build on it.


text:
What do they mean when say “the French equivalent of a Ph.D.”?
I read the biography of a French-born scientist-turned-entrepreneur Philippe Kahn. It says that Philippe Kahn received the “French equivalent of a Ph.D. certified by the French Academy of Sciences”.
I discovered an article about Kahn which says that he earned the equivalent of a doctorate, but not the degree. In yet another article, I read that he holds an agregation de mathematiques, and this is the French equivalent of a doctorate. I am rather baffled at all this, since Wikipedia clearly indicates that agregation has nothing to do with the equivalent of a doctorate. Can you explain what Kahn's biographers mean by “the French equivalent of a Ph.D.”? And if this is the degree then why should it be certified by the academy? So far I have come to conclusion that by the equivalent they mean the D.E.A. degree

Is this question about Khan's biography specifically or about the French education system at the relevant time?

After reading about Kahn, I became interested in French educational system as well.

Victor Wortman's article about Kahn says that after completing masters program in Nice, Philippe Kahn studied to get the equivalent of a doctorate, but not the degree, because to get the doctorate would require more years to get. Maybe I should edit my question to add this info too?

Could you add link to Victor Wortman's article?  I can't find the one you're referring to.

I have a PDF copy of that article. Can I attach it to comment? I got it some time ago at web.archive.org

I got it: http://archive.li/q2xY7

Are you sure that that's the right link?  It says: "Pastorale completed, Kahn went to Nice, where he completed a masters program in mathematics. He continued to teach, to study, and to work on university-related projects, in the process accumulating the equivalent of a doctorate, but not the degree.  To earn the doctorate would have required four or five years of serious research, he explains."

This Wired article from 2000 has a claim like what you described: In the 1970s, after receiving the equivalent of a PhD in mathematics, in France, Kahn worked on Pascal under Niklaus Wirth in Zurich and was a programmer for the Intel-based Micral, one of the first personal computers..

Victor Wortman's article was what made me initially  think that by "the equivalent" they mean D.E.A.. That is, from the text I deduced that the equivalent must be sth higher than masters and lower than Ph.D., so it had to be DEA. I knew nothing about  Doctorat du 3ème cycle.

According to a 1985 biography in PC Magazine:

During his college days, Kahn played saxophone in Paris jazz clubs while earning an Agrégation de mathématique, equivalent to a Ph.D. in math.

Another 1985 PC Magazine biography states:

Kahn, who received the French equivalent of a Ph.D. in mathematics from the French Academy of Sciences, taught mathematics at the university level in Nice and Grenoble before coming to the United States.

Both Wikipedia and Kahn's LinkedIn page state only that he received a master's degree in mathematics from Université Nice Sophia Antipolis in 1975.  This is not the equivalent of a Ph.D., and Sophia Antipolis is nowhere near Paris.
The agrégation de mathématiques is a competitive civil service exam used to recruit high school and university mathematics teachers.  While the exam is extremely rigorous, and agrégés are qualified to teach at universities, the agrégation is not a research degree.  French doctorates underwent a major reform in 1974 and again in 1984, but I believe the closest French equivalent of a Ph.D that Kahn could have earned in the late 1970s was the Doctorat du 3ème cycle.

Yes, I think that's the only possible explanation.

I also know of top french researchers who didn't enrolled in any doctoral course but are in fact doctors and directors of research. I was told this is (was?) possible in light of an initial exception made for M. Curie. Obviously the people I know did demonstrate their scientific research competence in a non classical parcour.

@Alchimista: You may want to add a comment, or maybe even an answer, to this question: Has anyone, based on great performance, ever been awarded a higher degree than the one they enrolled for?

@O. R. Mapper. Unfortunately I don't know details. I am just sure about it as  I worked in a group lead by one of those scientist but I am not willing to ask her(him). S(he) has not university curriculum at all. I also think that in my country - in principle!!! - an university could appoint a professorship on the sole basis of achievements. I said in principle, and in this case I am not sure.

But yes, I can add a comment..


text:
Does the name of the college you attend matter to your potential employer?
Please don't close, I'm just asking for research purposes.
I don't care if your answer is biased.

But this is opinion-based and hence off topic.

I'm voting to close this question as off-topic because "This is not a question at all."

I don't care if your answer is biased. – But we do care and don’t like questions which invite biased answers. Also: 1) Are you talking about the actual name or the institution behind it? 2) What exactly do you mean by matter?

Ivy League diploma may hurt you if your interviewer is a graduate of a state school and you act arrogant (or perceived as such). You have to fit into the culture of the place you are applying to.

Yes, it matters.  A degree from an elite university won't get you the job if you can't pass the interviews but it will pop your resume to somewhere near the top of the pile for a closer look.


text:
How do I deal with my mentor giving first authorship of my project to a graduate student?
I’m a senior undergraduate student who has been working in the same lab for over three years now.  Approximately two years ago, my mentor sat me down in his office and described a project to me.  He asked if I would want to put forth the work to be first author on the project.  I said yes and adopted the project as my primary focus for the next one year and more.
This was never solely my project; there were a few graduate students who would provide guidance and some help with assays.  However, I unequivocally did the most work on the project.  I played a major role in the writing process and created six of the seven figures. I also presented a poster of this work (on which I was listed as first author) at an international conference.
Now, as we are getting close to submitting, I have found out that my mentor plans to put one of the graduate students on the project in the first author position.  He is unaware that I know this.  I feel that I can say rather objectively that this student by no means deserves first authorship.  In fact, he is well known for his laziness and probably doesn’t even deserve second authorship.  The reason this is happening is because he and my mentor are very good friends outside of the lab.  The student is frequently granted benefits and immunities because of this.
Please, I would appreciate any advice. I want to confront my boss but I feel this will only injure our relationship which I need intact.  My mentor is by far my strongest letter of recommendation for graduate school and I need his compliance to graduate with honors from my university.

Could you describe what you mean by "I played a major role in the writing process"?

Have you tried meeting with your advisor to discuss your contributions to the paper, the plans of where to submit it, and the authorship ordering?

He is unaware that I know this. – The proposed first author or your mentor? In general, reading your question is made quite tedious by ambiguous or almost ambiguous pronouns. (Please [edit] your question to clarify)

I am afraid that we cannot provide help you much with your question as it stands. You correctly identified the pros and cons and now it all depends on how much you value your career, ethics, this paper, etc. as well how reasonable your advisor is – all of which are things we cannot tell you. If you have a specific goal, e.g. how you can let your advisor know what he’s doing without risking repercussions. Please also see this FAQ.

It is unclear how you learned about this plan, and this ambiguity makes it hard to give sufficient advice on how you might handle this. Regardless, it is reasonable to bring up your earlier discussion with your mentor, and pro-actively argue why you positively deserve first authorship based on your work and prior agreement to this effect. Not being willing to attempt direct, respectful communication about a topic of great importance is not generally a good method to get a good recommendation.

I realize the answer depends largely how much I value various aspects of research.  I am just having a hard time allocating this value given that this is such a major decision.  Anyway, I understand the criticisms with my question and greatly appreciate everyone who gave input.

First and foremost, students should always get in writing the agreement that the project and subsequent papers will include the student's name. Second, breach of this agreement should be arbitrated by formal authorship guidelines, such as: http://www.apa.org/science/leadership/students/authorship-paper.pdf Finally, a faculty member who violates the original agreement should be reported to the department chair and Dean of Students office for ethical violations. If the Dean does not respond, escalate to the Vice President of Research and/or Provost. You can call a lawyer too.


text:
Is it possible to find out which author got the most citations in a specific scientific discipline?
I'm currently trying to find out which authors get the most citations in specific fields, like
Astrophysics
Condensed Matter
High Energy Physics - Experiment
...
(These are all arXiv categories)
Especially great would be to do such a search for specific year. Is any paper search engine capable of this?

Are you aware that arXiv is not a journal nor a conference? Why does citation has much to do with arXiv? By the way, there is no "e" at the end of "arXiv". This is the second time I saw you write "arXive" today.

@scaaahu yes I'm aware of that. Citation isn't only interesting for arXiv papers, but I simply like the way they organize things by fields

You can use google scholar and filter by subject area, but this approach will only pick up researchers that have a google scholar account. Astrophysics for example http://scholar.google.com.au/citations?mauthors=label%3Aastrophysics&hl=en&view_op=search_authors

@user49483 ... and you will have to cope with the noise in Google Scholar citation count due to fake/manipulated citations and citations to and from non-scholarly works.

Sure, but it is the quickest and easiest method I know of. I can't imagine that self citations, etc. would have much effect when a researcher has  > 100k citations and I wouldn't think that non-scholarly citations are that biased towards certain researchers (although they definitely inflate the citation count). The biggest problem with google scholar, I would imagine, is some of the most productive researchers don't seem to bother setting up an account

Have you tried to search for the topic in researchgate.net?

@theMarceloR 'researchgate' is everything but comprehensive. Plus it's full of 'citations' to 'publications' that really aren't publications.

"Most cited papers" in a given field/period is fairly easy through something like Web of Knowledge; it's a few clicks to find out that both Scopus and Web of Knowledge list this as the most cited paper in chemistry in 2014, for example. (Tellingly, they only agree on three of the top five...)
Doing this for authors is more challenging, though - the Google Scholar registered authors method suggested above is effectively an opt-in database and so there's no way of telling who's not in it. Scopus has fairly good author-citation indexing but I'm not sure if it's set up to answer this specific question.
A couple of studies with similar questions:
Abramo et al looks at a defined set of researchers (all Italian academics) and shows a way to identify the most highly cited authors within them - basically just WoK citation counts. Robust but tedious, and you probably don't want to start with a list of "all astrophysicists"...
Another approach is to pick the most highly cited articles in your field (assuming that the bulk of citations are in these, not the long tail) and look at the authors of those papers. See, eg, Choi et al, which is "the most cited authors of the 250 top papers in the field", or Uthman et al, which looks at the authors of the top hundred medical reviews.
You could combine these - pull out, say, the fifty most cited papers, look at their authors, and do full citation counts on these using WoK. It seems likely that the most cited authors overall will be an author on one or more of the top papers.

Web of Knowledge is the right tool (if the field is covered by it).  Why would you want to know about most cited papers in a field?  One reason: in tenure and promotion cases, when they reach the higher levels of the university.  If papers in medicine typically have thousands of citations in the first two years, but papers in mathematics only dozens, we don't want the math papers turned down as "insignificant" by comparison.

Web of Knowledge or Web of Science are probably the best tools for this, but if they are not available to you there is a free software called Publish or Perish that can help make sense of the Google Scholar citation measures.