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Is mathematical aptitude the limit of how well I can do in an interdisciplinary life science field as a computer scientist?
I apologize in advance if this question is too broad, or too subjective - I couldn't think of a better place to ask it.
Summary: does mathematical aptitude impose an upper boundary on how well one can do in research areas where life sciences intersect with engineering and computer science? I.e., is an ideal researcher in such fields either an experimentalist or an applied mathematician/physicist?

I'm a computer science graduate thinking about pursuing a PhD in an interdisciplinary life science field; specifically systems biology, synthetic biology, bioinformatics, genomics or cognitive (neuro)science. Characteristic of all these disciplines is that they seem to - ideally - require one of the following two profiles:

someone with great experimental/domain skills (e.g. molecular
biology, neuroscience methods etc.),
someone with great quantitative skills (math/physics).

By virtue of my undergrad background, I'm likely closer to the second profile, even though I have some domain knowledge. However, here's where my self-doubts begin. People of this profile seem to be - in the long term at least - expected to produce new theoretical knowledge primarily by employing advanced math. Top research papers seem to be full of it. I'm concerned about this for the following reasons:

my mathematical skills and aptitude in the context of this profile are average, or a bit above average at best. Sure, I can handle ordinary differential equations and numerical integration, but once it gets to the postdoc level and above, I'm competing with people who are elite talents and have backgrounds in math or physics from top schools. I don't believe I posses anywhere near the math talent that they have, and I simply wouldn't be able to do the job as good as them - and I don't want to be producing subpar research. Furthermore, I spent a significant amount of time studying things that don't seem applicable to this type of research, like CPU architecture or OS internals. Because I'm targeting programs in Europe - where a PhD is normally 3 years - I can't in this short time develop my math skills enough to close the gap, especially considering my less-than-elite talent (funny as it may sound, I believe I have a much greater talent for the humanities/philosophy, but the amount of positions there is close to zero).
by far my strongest actual skill is coding/programming, and I could probably get some kind of position based on that. I believe I could do
well enough to produce some tools and maybe even get a (likely mediocre) PhD eventually, but
after this step - when an independent research path is expected - it
seems to me I would be at a disadvantage and heading for the
industry, because implementation skills are simply not enough, i.e.
they seem to have merely a supporting role in academia (since they alone cannot generate new knowledge, the main objective of research). Permanent faculty positions seem
to go out at much higher rates to math-inclined
individuals, who are at an advantage when it comes to formulating a
unique theoretical research statement. At least, this is my
observation.

Should I choose something else if I'm not a top math talent and thus can't evolve into any of the two profiles mentioned?
Or is such categorization of researcher profiles in fact a false dilemma and there are more options, i.e. not everything required to perform well in these fields can be reduced to mathematical aptitude?
For what it's worth, I did undergraduate research in computational biology that lead to published papers, and sure I could handle math at that level, but it just seems to me that to make it as a top full-time researcher, I would either have to become an applied mathematician or an experimentalist.

Being in Eurpoe, aren't you likely to need a master's degree in something before you move on to a PhD? Given that, couldn't you use that time to improve your mathematics training?

I have a masters degree already, sorry for the lack of clarity.

You can always collaborate with people with mathematical aptitude.

Speaking as a computer scientist who works with life sciences: there is a lot more use for computer science than just modeling.
Consider:

Who makes and maintains the instruments?
Who handles LIMS development and deployment?
Who develops automation systems and precision protocols?
Who develops the control mechanisms that actually implement biomedical intervention concepts?
Who develops taxonomies, interchange standards, and data representations?

This just scratches the surface of computer science opportunities in the biomedical
Unfortunately, the view that you hold of "you're either an experimentalist or a modeler" is far too prevalent in biomedical culture, and computer scientists often get little respect for their contributions.  That culture is starting to shift however, and especially in younger and more engineering-centric subfields like synthetic biology... and especially in some of the awesome things the younger practitioners are doing.

Thank you! To be clear, the experimentalist vs modeler view is not the view that I hold - it's the view that appears to be prevalent in the culture (or at least that's my impression as an outsider - hence this question), and the validity of this view (the need to conform to it to make it) is what I'm questioning. Many gradschool admission requirements will openly state that these are the 2 profiles they are after.

@voidptr You probably want to look more at particular faculty than at programs in general.  A good starting point for synthetic biology at least is to look at what the school's iGEM teams have been up to, which will give you some idea of how broad-minded the faculty advisors are.

From your question and comments, it seems you view “success” as being involved in original research, in a long term position where you can focus passionately on your research.
You are less concerned about success in completing the PhD program, and more concerned about “10 years down the road” from that, about the research, about being involved in compelling original research, on an ongoing basis, being in the thick of exciting things that are being worked on.
You are concerned that a wrong choice NOW would lead to a poor outcome, where you would wind up doing less-interesting research, a career, a life, of frustration, preventable by a better choice up front.  (Can’t say I blame you)
You have observed two types of profiles that succeed in this field:
1)  Someone with great experimental/domain skills (e.g. molecular biology),
2)  Someone with great quantitative skills.
Of these, it seems you pretty much write off 1), apparently due to lack of background, and focus on 2), with the observation that you have limits in this area.  So something closer to the great quantitative skills is how you feel you’d make your mark.
You feel your current advanced mathematics skills may limit you.  I also infer that you do not wish to fully give your mind over to the advanced mathematics area, as it does not excite you as much as other areas.
So you are looking for an answer that says, "Yes, you can make this work, and here's how, and here are examples of people who have done this."
You mentioned your concern about matching up to the mathematicians, competing with them.  “I'm competing with people who are elite talents and have backgrounds in math or physics from top schools.  I don't believe I possess anywhere near the math talent that they have, and I simply wouldn't be able to do the job as good as them - and I don't want to be producing subpar research.”
I challenge your assumption that you are inherently and always competing with these people.  Why don’t you focus on collaborating with them instead, certainly at least at first?  Why not see if you can provide all the key skills around this area so they can collaborate and plug in with their terrific skills, their 10%, in service of your great experiment design?  In the process, you will see how they think, your mirror neurons will get busy helping you learn rapidly, and you can decide if you want to learn to do what they do, or if you are just as happy to let them do that while you address parts of the problem that feel more creative and interesting to you.
I suggest that a good next action step is to start by looking again at some of those many papers you mentioned that contain large quantities of advanced mathematics, and then check the author list, and use your own research skills to ascertain which co-authors were responsible for which parts of the paper.
If possible, contact some of them and ask--how did they divide up the mathematics portions of the paper?  Do some of the collaborators even possibly have (gasp) a similar level of mathematical skill to what you currently possess, but great skills and creativity in other areas that were critical to success? You might also make some terrific contacts and have some amazing conversations in this process.
I think the answer is to go back to the papers that had the advanced mathematics that looked intimidating, and do some data-gathering fact-checking on which authors really did what, and use them to get a more accurate, and likely more diverse, profile of the types of people who can be successful in this field, and with any luck at all, potentially find a few models you can identify with, and inspire you to take the plunge.  (Who knows, maybe in the process you will discover other papers that are equally interesting to you, with less reliance on the advanced mathematics.)
P.S.  If, in the process, you don't find ANY models that inspire you, give you confidence, then DON'T DO IT!! Run Forrest, Run!!

Thanks for some nice ideas, further analysis of papers would be my step in any case. Just for completeness sake, I'd also fully accept "you can't realistically make this work, find something else for yourself" as a valid answer if that's how it really is.

Did I accurately reflect the part about your success criteria, and original research in a long-term position?  Yeah, it occurred to me that looking at those papers was what put you off, so more detailed scrutiny and fact checking on which contributors really did what would help clarify what "reality" is.  jakebeal had a helpful take too, but that involves negotiating backwards from what you say you truly want. (as I currently understand it)

Yes, you accurately observed that my notion of success here refers to being able to do quality research in the long term. On a deeper level, it's about not wasting time pursuing something I'd never be good at - passions can be deceiving. That is not to say that I'm not concerned about a PhD program, it's just that I've been given an impression that getting a permanent research position after PhD is another game altogether due to extreme competition for research positions.

I remember that day, 25 years ago, I realized I could never be "the best programmer in the world" as long as my colleague Scott was alive. Then I came to realize that Scott sucked at marketing, and was constantly building "products" that primarily interested him, though with great passion and skill. So I realized I didn't have to "out-program" him, in fact, he was not really a competitor, but a tremendously helpful collaborator. I learned to use my marketing and people skills to engage his skills to benefit everyone more, including myself. I still wound up doing a lot of enjoyable programming.

This question doesn't seem to be active anymore, but I just came across it and there's one thing that nobody has talked about: big data.
Data is everywhere in the "wet science" nowadays, and it really is changing the way people do research. I would say data analysis skills are at least as important as pure math skills, and these skills are a mixture of intuition, good programming skills, understanding of data management, statistics, machine learning, and perhaps more.
Good programming skills are also not very common in the wet sciences.
My friend who's a glaciologist struggled with that in his PhD, doing experiments over and over because he didn't trust the code he wrote, and when they hired a programmer, the programmer didn't understand the domain, so he was pretty useless.
The opportunities of applying good data analysis skills are huge, even in the humanities. There's a major international challenge called "digging into data" shared by the US, Canada, the UK and the Netherlands that really recognized that (http://diggingintodata.org/).

If you want to do something in life, you should try it. Try it for a short time defined as less than 5 years.
One of the primary indicators it isn't working out for you is that you'll probably feel great stress if you are barely keeping up with your peers.
Please realize as well that different disciplines focus on different mathematical concepts. For example, if you are interested in becoming a PhD electrical engineer, you probably won't spend any time worrying about number theory or General Relativity. In other words, you don't have to learn ALL mathematics known to mankind in order to succeed in a field that requires skill at some form of advanced mathematics.
Here's something pretty funny for you to absorb. I actually had a professor speak the following paraphrased words in my university philosophy class:
"Most of the research produced at colleges/universities is garbage."
From my own experience at a university I can tell you that there are many dissertations sitting on shelves in back rooms that are doing nothing more than collecting dust. People aren't necessarily as brilliant as you think they are.
Judging by what you've talked about here, I'm laying my money on the notion that you are going to succeed in life.

It seems to me you are making excuses and "failing yourself", i.e., declaring your own failure in advance, for reasons that may or may not even wind up being relevant.  I read in your question that you do in fact actually WANT to go for this, but you are  afraid of failing in the end.  So, the real question becomes, how do you define your own "success" or "failure" in this endeavor?  If you wind up getting a PhD at the end of the day, will that in itself constitute success?  If you pursue this path, but do not obtain a PhD, or do not obtain a permanent faculty position, will one of those unequivocally constitute "failure" in your own eyes?  Is it still a failure if you wind up obtaining well-paid employment doing work you are passionate about, with brilliant people you love working with?
Are you trying so hard to have everything "perfect" according to the limits of what you currently know, that you are keeping yourself from even pursuing something you appear to want?
It seems there are a range of possible outcomes here.
1) You don't even get selected to start in the PhD program, and the whole issue is moot.
2) You enter the PhD program, and in the course of your studies, discover some other, related area you are passionate about and particularly good at, and change your studies and degree program to focus on that previously unknown area.
3) You enter the PhD program, do not enjoy it, do not complete it, and discover other areas of life you wish to devote your energies to.
4) You enter the PhD program, and complete it, but not at the full level of distinction you wish, and at the end, wind up having less ideal choices than you would like to have, though one or two of the choices are reasonably appealing.
5) You enter the PhD program, and complete it, in the process gaining all the advanced math skills you truly need, bringing your own unique skills to bear, and completing the degree with distinction, and have numerous appealing options to choose from at the end,
This is of course an artificial, limited list of the range of possible outcomes.  Which of these would be success?  Which would be failure?  It seems to me entirely possible, almost likely, that you would have research partners with the math skills you desire, who would be interested in collaborating with you precisely because of your computer programming skills, and the ability to automate the creation of research models, and in the process, tackle even more challenging and interesting kinds of problems as a team than either could succeed at individually.  Does all the ultra-advanced math have to come from uniquely you? Or is it sufficient to come from a research collaborator, as long as you fully understand it?
So yes, I personally believe you are creating a false dilemma for yourself.  I think it would be helpful for you to consider, to the point of writing them out in much more detail than I did above, a RANGE of outcomes that could occur from pursuing this PhD program, and then decide which outcomes constitute "success", for YOU, and which outcomes would constitute "failure".  Then, estimate the chances of each outcome coming to pass, 30%, 80%, and so forth.  If there are one or more "success" outcomes with likelihood above 50%, then I believe you have your answer.  Or, at the least, you are now clear about the question.  Do you need "slam dunk" odds of success? or is 50% chance of success good enough for you to get started, confident that you can improve your own odds by hard work and passion?
The other question you musk ask yourself, is "what are the other options", and are any of them as well developed and appealing to you as this one? Because you don't mention them, I can only conclude they are not as well developed or appealing, and that you have put your energies into the option you are asking us about.
The other risk here, is having a well-developed option like you present here, choosing not to pursue it, and then later regretting your lack of action.  Picturing yourself five years from now, what will you wish you had done?

Thank you for your answer and your time. In short, "success" in the context of this question for me means being able to stay in research, ideally as a career, not only for the duration of my PhD. I've been lead to believe that competition for positions is fierce and that's why I'm trying to clear up some expectations for myself. "Does all the ultra-advanced math have to come from uniquely you?" I don't know - that's what I'm trying to find out here in a way, i.e. if I am expected to modify myself to fit one of the described profiles, or if there are multiple other viable skill sets.

I accept your characterization of the need for the level of math skills, and your self-assessment that you are not at the truly required level.  I think it is high risk to expect to play that specific game and expect to win without having the innate skills/interest you have observed are necessary.  To win, you will have to be able to change the game to one that better matches your unique strengths.  In what ways can you carve out or create a pleasing niche that better matches your unique aptitudes?


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Does becoming good at scientific research force one to become one dimensional?
I'm an individual interested in multiple academic disciplines such as neuroscience, biological engineering, computer science, history, anthropology, psychology, political theory ... to name just a few. Currently, I have a normal (40 hours/week) engineering job that leaves me enough free time to follow these topics to a moderately satisfying degree.
However, primarily due to intellectual curiosity, I'm considering doing a PhD (in Europe) and would ideally want to move to research later (discipline: something along the lines of genetic engineering, computational biology or cognitive neuroscience - not sure yet, but my background is in computer science). Given the highly specialized nature of modern scientific research that seems to demand intense working hours, one concern that I have is the fear of becoming highly one dimensional: completely failing to follow progress in other fields and in society as a whole, with publish or perish environment creating an inescapable feedback loop, where one cannot afford to read articles and books on topics not related to work, or follow public debates; yet alone write a blog about e.g. social issues.
I realize there are academics out there who seem to be prolific across multiple disciplines (e.g. Chomsky, Pinker ...), but the question still stands: in a modern research environment, can one satisfy multiple intellectual interests that transcend immediate work requirements, or has the game become too competitive and focused for that? What are the main variables?

Alas, I think that research is making me more three-dimensional. Especially around the waistline and hips.

You can do it, but you might not be a professor. I have a PhD in Aerospace Engineering, and I work in CFD, HPC clusters, and BigData/analytics when I do research. My primary job is running the HPC department at a large-ish computing center. If I were a professor, I doubt I could pull this off. My research output is much smaller that professors my age, but I still have a pretty satisfying career.
You best chance for doing lots of different kinds of research is to find a center who appreciates you for your broad interests and to help it grow its mission while pursuing your more esoteric interests when you can.

Broader skills are much more appreciated/valuable in the National Laboratories than academia, in my opinion.

Agreed. A US DoE National Lab would be one such center.

The answer may vary across field and institution and continent.  But based on my experience, in short, I would say:  Yes, a modern research environment permits and even benefits from broad intellectual interests.
But first let's draw a distinction between what I'll call your "output" and your "input".  For most researchers, research output is highly specialized.  It can take an intense focus to make progress on the hardest, most impactful problems (http://matt.might.net/articles/phd-school-in-pictures/).  Not only that, your progress is generally a super-linear function of the time you put into a project.  You invest in learning past work, concepts tools, developing ideas often over a period of multiple years -- and then connections happen faster, ideas mature, you know the software tools, and overall you produce much more quickly.  Good interdisciplinary work is possible and does allow you to use expertise in multiple areas or fields; but, in my experience, this work can be just as specialized.
Your "input", however, is an inspiration for what research to tackle.  I find that my creativity in producing good research ideas is substantially better when I explicitly take time to step back and think, interact with new people, and explore new concepts.  And the best researchers have a good understanding of society and gut feeling about what will be really impactful in the next few years.  If you completely fail to follow progress in your field, in other fields, and in society as a whole, you might produce more papers in the short run but probably have less impactful research in the long run.
As Hamming said:

Another trait, it took me a while to notice. I noticed the following facts about people who work with the door open or the door closed. I notice that if you have
  the door to your office closed, you get more work done today and tomorrow, and you are more productive than most. But 10 years later somehow you don't know quite know what problems are worth working on; all the hard work you do is sort of tangential in importance. He who works with the door open gets all kinds of interruptions, but he also occasionally gets clues as to what the world is and what might be important. Now I cannot prove the cause and effect sequence because you might say, "The closed door is symbolic of a closed mind." I don't know. But I can say there is a pretty good correlation between those who work with the doors open and those who ultimately do important things, although people who work with doors closed often work harder. Somehow they seem to work on slightly the wrong thing - not much, but enough that they miss fame.

Finally, as a professor, you have a great deal of freedom to steer your own research agenda; more than in most professions.  While it's hard to make progress in wildly divergent fields concurrently, over longer timescales (5-10 years) many researchers do change their focus area quite successfully.

I'd say as a tenured professor in the US, you have such freedom, but I think you'd be hard pressed to get tenure with papers in 10 different areas than 10 (or whatever) papers in one major area.

hence the 5-10 year timescale between shifts in area

I know this question was asked a long time ago, but for future reference: I think the answer is "kind of."
The best way that I know to do this professionally is to become a "method development" person. In other words, if your job is to develop new statistical or computational tools, or to develop new instrumentation to measure things that weren't previously possible to measure, and if you are very good at striking up collaborations across different disciplines, then I think it's totally possible to remain somewhat agnostic about what exact questions you want to pursue using your new methods.
(This is adapted from something a previous advisor said to me, which is that you can be a "methods" or a "problem" person. At the "problem" end of the spectrum, to contrast with the above, you would be motivated by a really specific question, would understand it better than anyone else, and would be more willing to use a wide variety of methods to study it. It can be a good exercise to look at people's careers and try to see where they fall on this spectrum.)
The caveat is that in order to do this successfully, you're still going to need to go "narrow and deep" at the PhD level in something like applied math, statistics, algorithms, etc.; otherwise it's going to be very hard to do work that is cutting-edge enough to genuinely matter across a variety of applications. Doctoral work is all about making a unique contribution; if your knowledge doesn't take you "right up to the edge" of any field, that's going to be really difficult. You will also likely have to cede a little control in terms of choosing questions, because you won't always be able to shoehorn an existing interest around your analytic specialty. But if you want a lot of variety in a tenure-track academic career, I think this is your best bet.

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Is my adviser supposed to be assigning me my research?
I have just finished my bachelor's degree in computer engineering. I am doing an REU with the professor who will be my adviser this fall when I enter grad school.
Currently my future Adviser has me working on research that involves image processing. I was hoping to head in other directions in embedded computing and security.
From our weekly research meetings it seems like my adviser will be assigning me research topics through out my grad school career. Is this normal that an adviser would insist on determining the research topic of the PhD students under them. I have not pushed back on this yet but I am not prepared to go in depth in image processing. I am not a math major or CS major and that field gives me little interest.
--ADDITIONAL INFORMATION BELOW--
As far as funding goes I am currently funded by and REU(research experience for undergraduates) and am unsure of where this funding comes from(NSF, department, professor). Here in 2 weeks though I will be funded by a Distinguished Academic Fellowship(DAF) that my university graduate school awarded me.
In order to get my DAF I had to write a research proposal. I proposed research into microprocessor, GPU, FPGA unification. As I understood it from those within my department I am not required to carry out that research as the proposal is more a way for the DAF committee to see that I can write a coherent proposal for later on in my academic career.
Concerning the union of my professors research interest and mine: He focuses on embedded system design for single specific applications. It just happens that in the current path of research he is onto it involves cameras. This then introduces the field of image processing into the project.
It seems that all his grad students are doing peripheral work on UAVs that will be coalesced into a UAV platform of some sort.

Similar (but closed) question to yours: Should professors help masters research students to find a research topic?

Something just does not feel right on your question. When you decided to have him as an advisor, didn't you discuss on what area you will focus? What is his area of expertise? If he is into image processing, it was unreasonable for you to expect him to do embedded computing or security.

I'm definitely a bit concerned as well: generally you pick an advisor because your research interests align pretty well.  In many ways, you should never choose a grad program for its program, but for the specific labs you would want to be part of (i.e., the mentors).

An adviser essentially hand-picking your research for you? Get out while you still can!

@JeffE Why to get out?

Why did you pick this person as your advisor, if you did not want to do the research that the advisor is interested in?

@EnthusiasticStudent Because an advisor handpicking your research is like an instructor doing your homework for you. You might still get the degree, if you can stand the boredom, but you'll have missed the opportunity that the degree supposedly represents. In short: It's your degree; you have to hunt it down and kill it. The hunt is the point, not the degree.

@JeffE this is still happening before starting the PhD. I think it could be salvageable if they talk things out.

@JeffE I don't see the same red flags.  How is a new student in a field supposed to know good research questions?  I think it's completely reasonable to hand-pick a couple of small topics so the student learns the ropes, while helping them learn the field well enough to pose good research questions.  If you want to develop both solving and posing questions in parallel, it's inevitable to suggest a question or two to solve while they learn how to pose a good one.  If you, as an advisor, can't think of a question they find interesting, that is the mismatch.

@Namey A new student isn't supposed to know good research questions, but just handing them a research question isn't going to help them learn how to find good research questions. A much better tactic is to work with the new student to converge on a good question.  Give the student ownership of the process from the beginning. Let them have bad ideas, and let the world not end. Suggesting a question or two is very different from hand-picking.

While I agree with the general principles, you seem to be completely rejecting modeling as a learning strategy (i.e., where you learn by observing others do something).  Particularly for people just getting started, it often makes sense to have them ride co-pilot on someone else's journey (either their advisor or a more senior grad student).  Having bad ideas isn't the end of the world, but converging on a meaningful question can take a year or more for some students.  Would you honestly propose having them sit on their hands (losing valuable practice in solving) until then?

Or, to put it a different way, research has three parallel tracks: formulating it, doing it, and reporting it.  Starting the first semester, a student should be involved in all three.  However, since for any one topic those steps happen sequentially, a student should be given tasks to practice the other two (doing and reporting) until their ideas converge during formulation.  I would consider anything less a disservice.  However, before their idea is ready, the topics to "do" and "report" would need to, you know, already exist.

This depends very much on:

How much interests and your advisor's interests align
Where your funding comes from

First, interest alignment: Starting a grad program, you find an advisor with interests that overlap with your own, do the foundational things that need to get done, then expand on it with your own ideas.  Later, when you are pitching grants, very much the same thing but with program officers: you have a great idea, and you find a way to dovetail it with their calls for proposals.  Finding the common ground between your research and others' research is a fundamental academic skill.
Second, money: if you are funded through a grant that needs image processing research done, do you think that your advisor or the funding sponsor will give you a big thumbs up when you say, "Actually, I have some great ideas for embedded security devices I would rather work on."  Nope.  If you were in their shoes, shelling out $30-60k on a student for a year, wouldn't you expect them to help get the grant completed successfully?  If you want full control over your research, become independently wealthy first.
Successfully doing your own research in academia, in grad school and beyond, involves a lot of meeting in the middle.  Given the huge disparity of research topics you mentioned (image processing versus security), I genuinely wonder about the overlap of interests.  If there really isn't much overlap, it might be worth looking for a different advisor.  You won't become an expert in one field by being mentored by a guy in another field, even if your advisor lets you run wild with any idea that comes into your head.
Update
Since more info was added about the funding and interest overlap, I can note a bit more here.  It sounds like your funding is relatively portable and not tied to a project.  In that case, you should have pretty strong control over what you want to do.  You should not be using this control to just pitch ideas and run with them.  The benefit of a PhD program (as opposed to learning how to research while living in a shack) is to apprentice with people who are experts in what you want to do.
However, having your own "batteries included" funding means you should be able to match with the best advisor for your interests. It sounds like you need to discuss the issue of overlapping interests with your current advisor.  If you don't want to go in the same direction as the lab, maybe they can suggest another group who does something that is a better fit.  Alternatively, maybe they will hit topics that you find more interesting during other phases of projects. It's not uncommon to switch advisors in the first year: I knew a professor in undergrad who actually recommended avoiding even starting in a given lab, so you could just meet with professors to find the best match.

The funding situation is unfortunate. Imho, finding a good problem and doing independent research is a hallmark feature of a PhD. "Here's a problem, solve it" can degenerate into a string of master theses. (Of course, if you want to work on problems completely orthogonal you your advisor's interests, you have a problem.)

@Raphael: Do you really think so? In my field (mathematics), I think it's extremely rare for students to successfully find their own thesis problems. A major role of the advisor is to have a sufficient sense of the field to know about problems that are interesting and significant yet at an appropriate level for a student.

@NateEldredge I think it has to be a combination of both. The initiative should come from the "student" with the advisor controlling for scope. Imho, general interest ("significance" or "relevance") are not at all important for a PhD; it's about learning how to do (good) research, not the results themselves. (It's nice if both coincide, of course.)

@NateEldredge There is a very broad spectrum between "Here's a problem, solve it." and "Find your own problem."

@Raphael: for students in math who want to continue in academia and be competitive for postdocs and/or positions at top schools, the significance of their thesis research is quite important. Here "significance" is measured by the other researchers in their area not at their institution. Perhaps it is different in other fields.

I have heard it termed partly based on the quality and initiative of the student making the ideas, ranging from brilliant students at the top end (constantly raising great ideas, you nudge them toward the one that seems best) down to the least creative (needs to be given a problem, still might not be able to solve it).  Almost all students who get a PhD fall somewhere in the middle, meaning that their topics may need revision/redirection/rejection.  Even for a brilliant student, it usually takes a lot of time, reading, and networking to know what is significant in their field.

I also don't think that having to compromise on topics due to funding is necessarily a bad thing.  It is a fundamental skill in science and any field: identifying who will benefit from your labor.  If you are choosing topics and can't find a lab that does funded research on them, you are either: A) A tremendous visionary or B) Working on problems no one finds important.  The former are usually so brilliant they can hunt up their own money if needed (e.g., win scholarships or department funding).  The latter should be discouraged, at least in my opinion.

In many fields, it is common for the advisor to "suggest" research projects to graduate students (including PhD students). In my own area of mathematics, for example, this is the case.
Of course, there is give and take between the student and the advisor about exactly what project the student will work on, and one can never know the outcome of a research project before it is done.
It is a well known phenomenon in math that some advisors have a vision for a long-term research program with many required intermediate results, each of which they will assign to a different PhD student as a thesis project. Depending on how many students they advise, not all the students may work on these results, but many of them will.
On the other hand, there are some advisors who give students more flexibility to choose a thesis project. But the project will always need to be in an area where the advisor has real expertise - otherwise, the advisor is not a good choice for the project.
It is also worth keeping in mind that the goal of graduate education is to get students to a point where, at the end, they are able to select their own research projects and carry them out independently. This does not mean that the majority of students are already able to do so when they enter graduate school.  It is easy for a graduate student to take on more than they expect, if they choose a thesis project unwisely.
Ideally, you will find an advisor (1) who is very good at advising; (2) who  you can work with successfully; (3) who works on topics you are very interested in; and (4) whose students have a history of good jobs after graduation. But sometimes it is not possible to achieve all of (1)-(4), in which case you have to compromise. For some students I have known, giving up on (3) was easy - after all, working on something long enough often makes it interesting. For others, not having (3) would be a deal breaker.

"This does not mean that the majority of students are already able to do so when they enter graduate school."  +1 on this.  Judiciously selecting topics is one of the most advanced academic skills.

I think the short answer should be "NO", but there are a lot of stuff which have to be taken in consideration.
Is it clear on what type of project you will contribute with your research, or is it a research that is not on the frames of any project?
If it is a research within the frames of a project which has got funding based on its documentation, you will have to work on what that research asks you to. And it is up to you to decide if you want to work on that topic or not.
In both cases, I think that the field of research and the expected outcome of your research should be defined even before the research starts. Of course along the path you might hit obstacles and look at different stuff, but not to the extend of completely switching fields.
Looking at your description it seems that you are working on completely off-topic stuff.
Bear in mind that the Adviser might be testing you, and see your reaction. Maybe if you don't react and accept to do everything that he asks you to, then he will continue with the same later on. Also, he might be testing your patience.
In any case, I strongly recommend that you have a very thorough and mature discussion with your adviser before starting to work on the research. And make sure that this discussion will result in "clearly" defined research goals, at least a well defined topic to focus on!
In general, you are supposed to know the fields of interest of your adviser and expect that he will ask you to do work on those fields.
image processing, security, and embedded are very broad definitions and (at least to me) look very unrelated especially when the granularity of a phd research is considered.

"[T]he expected outcome of your research should be defined even before the research starts": if you know what the expected outcome should be, it's not research!

@aeismail I can not understand. Specially in MSc thesis, students/professors do not expect a new theorem to be reached. They work on one application of a theorem and try to solve a problem. They know what they want to solve and they almost know where they are going. For instance, if we are solving a differential equation, we know the problem and we know the solution should be a function, but the process to find that solution is unknown... I think research is not defined by where researcher is going. It is the process that researcher works on to connect a problem to its solution.

@aeismail maybe I've done a poor choice of words there, but by saying that sentence I did not allude to knowing beforehand the final result of the research, but rather considering the possible outcome(s).

@aeismail: won't that depend on the field? In math, if everyone expects a certain result to hold, but I am the first to prove it, that still counts as research. For example, everyone expects the "Riemann Hypothesis" to be true, but nobody can prove it, and if someone proves it they will be famous.

I am also confused by aesimail's comment.  In most experimental fields, you make a hypothesis before you do the research, which is exactly that: proposing what you think will happen.  Then you see if it did happen and report it.  Often, the ones that don't match what you expected are the most interesting.

No, it isn't normal or desirable. The point of getting a PhD is to learn how to conduct research, and part of that is learning how to choose research topics. Your advisor should suggest topics and steer you away from bad ones and toward good ones, but summarily giving you research topics for the entirety of your time in grad school is doing you a disservice. Find a different advisor. (In case it helps, my advisor did the same thing: He presented me with a list of topics he found in a paper somewhere, told me to choose one from them, and refused to even entertain my suggestions when I asked for something else to work on. It was one of many reasons why I got nothing out of my time in grad school, and I don't want you to have to go through something similar.)

The answer is YES, sadly. If you do not like it, you got to talk to him/her, or get another advisor if no agreement can be reached.

This comment gives me a sadface.  I would definitely not give an emphatic "YES" to an advisor assigning research topics ad infinitum.  Students doing research should be gaining skills from it (and skills that they will find useful for their goals).  A student shouldn't be forced to do research that doesn't match their path: if the mismatch is really bad, the student should mention it and the advisor should support them in finding a better match.

You're right. It is not a good idea to enforce slavery research. But it is common practice. Just talk to the advisor about your plans and weather he/she supports you.

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Do graduate schools have more courses & less of a student-teacher ratio than undergraduate?
On average do grad schools offer more distinct courses than undergraduate schools?
If that is the case, then it must mean there are more professors teaching in graduate schools. And common sense tells me that there are less students in grad school than undergraduate.
Does that mean there a disparity in the student-teacher ratio in grad and undergrad schools?

I don't understand the distinction you make between "grad schools" and "undergrad schools".  At least in most US universities, the same faculty teach both graduate and undergraduate courses.

I don't know much about that, which is why I asked the question for clarification.

I will limit my answer to American universities.
Do you mean more courses per semester, or more distinct courses that are listed in the course catalog and offered with some regularity?
If you mean the former: in any given semester, most departments offer many more undergraduate courses than graduate courses.  This must be the case for the reason you suggest: the number of students taking undergraduate courses in that department is usually far in excess of the number of students taking graduate courses in that department.
But most departments offer largely the same undergraduate courses every year (or sometimes, on a two-year cycle).  Many undergraduate courses at a large university have multiple sections running concurrently.  The most popular courses -- e.g. freshman level courses for non-majors -- are in some departments run in ten, twenty or more sections each semester.
If you mean the latter: yes, many -- perhaps most? -- departments with large graduate programs offer a larger number of distinct graduate courses over the years than undergraduate courses.  Each course is populated by a smaller number of graduate students, but graduate students stick around for at least as long as undergraduates and, unlike undergraduate students -- recall that I am talking about American universities -- take the vast majority or the entirety of their courses in a single department.  Sometimes graduate students repeat courses or stop taking courses at a certain point, but in many PhD programs -- including the one at my university -- graduate students are required to take a minimum (positive!) number of courses every semester, some of which are unrepeatable.
In fact, most departments devote much more thought to which graduate courses they are going to offer in the next year or two years, both in order to make sure to offer enough courses for their students to take, and conversely to ensure that enough of their current students will want to take any given proposed course in order for that course "to make", i.e., to meet minimum enrollment requirements and be run.

Thanks for the explanation. I meant larger number of distinct courses.

For the UK and EU universities I am familiar with, your logic is a little off.
That is, I believe you are saying more courses require more teachers. However, graduate course and undergraduate courses are not the same at all.
An undergraduate course would typically include 4 to 6 hours per week for a single subject. This would continue for somewhere between 9 and 16 weeks.
A graduate course would typically include 3-4 hours per day, for 5-10 days.
So you can see, graduate courses are more compressed as far as contact hours, mainly because the students are expected to do significantly more independent study. Because a graduate module is compressed into 5-10 days, one teacher could teach more of those in the same time as one could teach a single undergraduate module (considering only classroom hours).

I see your point, I thought grad courses being more specialized would require different teachers for different courses.


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Panic Attacks during an exam - Can the student be re-tested?
I am a student who is currently undergoing therapy for mental health issues and I seem to be making good progress towards normalcy according to my therapist. Recently, I took an exam for a co-ordinated course and I completely panicked on the exam. I made a brave attempt to remain calm and answer the question to the best of my abilities and could only manage to earn 5 points overall.
Based on my predicament, can I approach my professor and department chairperson with a request to re-take the exam? I can of course ask my therapist to provide documentation detailing my case. Do universities make allowances for students who can demonstrate a genuine case for  a panic attack?
EDIT:
I do realize that I should contact the counselling center beforehand to make arrangements to take the test there but unfortunately, I was doing quite well and my therapist did not see a need to supply me with a note documenting my need. I completely blacked out when I saw the questions as they were quite long and bore no semblance to the practice exams or the homework questions.

It's generally advisable to talk to teachers and/or administration before you take exams. Your position is much weaker after you failed, because then it's not clear whether the reason for failure was your illness or your preparation.

But do ask yourself: do you really want to be treated any differently? Is it so bad to retake the class?

@PatrickT: This isn't necessarily going to be a one-time problem.

@PatrickT Yea, you don't really want that on your transcript. If you don't have to do an entire semesters worth of work over by showing that you had a legitimate barrier, and just have to take one or even two exams over, then that's worth it. People shouldn't feel ashamed for getting what they need.

If you are in the US, your school is required by law (the Americans with Disabilities Act, often abbreviated ADA) to make reasonable academic accommodations for students with disabilities. This includes mental illness.
In the US, schools have a formal ADA policy that describes the procedure for requesting accommodations. This includes a description of who to contact to make these arrangements. This person is trained in dealing with these issues.
Your next step should be to contact this person, find out what can be done about this exam, and find out what accommodations they can offer for future exams. (For example, they may help you arrange to take future exams in a separate room with no other students and/or with extended time, which may help you stay calm.)

Yes, I am in a US school. I did not know about the ADA, I will contact the counselling center to see what can be done. Thank you for reply.

@cherrywheat My university has a disability services office. You have to register with them, proving your disability and requesting accommodations. You can be given access to the testing center (a sound-proof room with a bunch of cubicles, basically) and alternative test taking times. In some cases, you can get other amenities such as proctored bathroom breaks or the ability to record lecture with your professors' permission. Check with your university.

Based on my predicament, can I approach my professor and department chairperson with a request to re-take the exam? I can of course ask my therapist to provide documentation detailing my case.

Approach only the professor first. If you are already escalating to the department head in your first mail, the professor may not take it well. That being said, I see no reason why you should not contact her/him.

Do universities make allowances for students who can demonstrate a genuine case for a panic attack?

Most universities have a contact person responsible for accessibility and non-discrimination of students with disabilities. I am not sure whether they are in general also responsible for documented cases of mental health issues, but it would not surprise me. In the future, it makes sense to get in touch with the responsible contact person before the exam, so as to clarify whether something can be done in advance to make taking the exam easier for you.

I did see the professor first and because they are an adjunct, they did not want to make any policy statements and so I was directed to get in touch with the department head. Thanks for your answer.

Unless the professor has the wrong end up entirely, the only thing he can do is tell the student to go to the department head or CAPS. Their job is to educate and do research; the psychological needs of students  are not their area of expertise. It's probably good to let the professor know first, but there is little the professor can do.

@JFA: I don't completely agree.  "Psychological needs" are not the professor's responsibility, but offering makeup exams or other accommodation for student emergencies certainly is.

@NateEldredge: The professor can, as cherrywheat suggests, basically "kick the problem upward" by saying that somebody else needs to determine that the student is eligible for a new exam.

@NateEldredge I must have been unclear. I was saying that you have to go through whatever structure your school provides. The professor cannot make the call on whether or not you deserve extra time; they are not qualified to do so. They are required to make whatever accommodations are necessary, or if they can't, send the exam to the testing center who can.

@JFA: This is dependent on your school. In most schools I know, the professor could easily make the call if they want to - a formal way would take years.

@JFA To contrast, in Sweden it goes the other way. We have a disabilities office which the students are supposed to get in touch with, but they are by law only allowed to make recommendations to the teachers. The ultimate decision and responsibility lies with the teacher, and only the teacher.


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How much weight is given to letters of recommentation from developing country for Dphil at Oxford University?
If one graduate at a developing country which lack highly ranked professors, how much weight should be expected to be given from Oxford University to recommendation letters for a Dphil? Do they weight it as much as letters of students with famous letters from famous professors? Are students with letters from famous professors preferred or they just access the content?

Without knowing the content of the letter or the letter-writer's standing in their academic community, this question is impossible to answer. Economic development is a crude indicator of academic excellence, you would expect the admission committees to look for more direct evidence when making their decisions.

I doubt there are any statistics to support this, so this is my opinion plus some limited experience in selecting applicants to graduate programs.  A famous professor's letter is likely to have somewhat more weight, but not purely because they are famous; more because the fact that they are famous implies that they have more experience judging people.  If someone who has mentored two students says "This is the best student I have ever had", their ranking has less weight than the same claim from someone who has mentored two hundred.
On the other hand, a strong recommendation from someone who knows the applicant well will have much more weight than a vague and impersonal recommendation from someone who clearly doesn't know the person as an individual.  Remember that committees already have much information about the applicant as a student -- grades, C.V., courses taken, extracurricular activities should all be present in the application elsewhere. A recommendation that merely says, for example, "This student received a good grade in my course" is useless; we already can see that, it's redundant information.
A useful recommendation letter adds new information that the committee can't get elsewhere. A student may have received an "A" because they are slow, but diligent; or they may be brilliant but lazy. The student has published a paper -- Did they perform a technical but unimaginative role, or did they conceive of the idea and push it to a conclusion? The outcome will look the same on the other documentation, but the recommendation letter can tell the committee what actually happened. Similarly, committees look to recommendation letters to try to understand the applicants' personalities. Are they cooperative, argumentative, shy, stubborn, agreeable? There is wide latitude for personalities in graduate studies, but there are certainly some people who are unlikely to do well because of their personality, and a recommendation letter can help flag those who are likely to be great fits.
If that new information comes from a famous person who has had the opportunity to compare to many other students, so much the better.  If it comes from an obscure person, it is still far more useful than a mere recitation of the same information that's already present in the CV; and it's far more useful than unhelpful information, no matter how famous the person.
(I have seen cases where applicants included personal recommendations from senators and in one case the US president.  These letters not only did not help, they reduced the ranking of the applicants, because they were inappropriate and reflected poorly on the applicants' judgement and understanding of the field.)

Well from my personal experience, I worked in an office where we were sending students to world top ten universities from Pakistan. We sent some to Stanford USA, and Oxford UK beside others. What I saw was that indeed weight is given if you are from a reputable university or not in a bad one at least. And that most of the weight is given to grades but most important is the research proposal that you write and your personal statement.
Also, a letter of recommendation not only states about you, but also the writing expresses the professor himself, how good he writes it.
Then if there is some research that has to be related to a developing country, then they will prefer you, especially if it's related to your country or like wise.
I myself got a scholarship in a good university under top 100, though lot of my friends with excellent grades didn't succeed. So keep trying is the key.


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What is an FTE and what are its variations?
What is an FTE, how is it used, and what are the varieties of FTE calculation that you might see in academia?

Per the FAQ, "if you believe your post should be converted to a community wiki, you may flag it for moderator attention." Generally more efficient than writing something in the question itself and hoping one of the four diamond moderators happens to read it, although this time it worked :) (Why did you want this to be community wiki?)

I think community wiki is better as I was thinking about this question while walking the dog and realized that FTE practice varies wildly across the various universities I've been at, so an authoritative answer by an individual is difficult to impossible.

That's the other reason I community wiki'd. I think the community can fill in a better answer.

An FTE stands for Full-Time Equivalent and is the unit of calculation for counting faculty positions or student enrollment at a university.
For faculty positions
A 1.0 FTE position is nominally a full-time position for one faculty member. If a department has 4 FTE, then you can expect that it has four full-time faculty at minimum (see adjunct FTEs below).
Split FTEs
Someone may have a split FTE such that for example, half of their FTE belongs to one department and half belongs to another -- e.g., Prof. Alice could be 0.5 Math and 0.5 Computer Science.
The ratio can vary so that Prof. Bob could be 0.25 Physics and 0.75 Geology.
Some spousal hires are structured so that Profs. Alice and Bob are both 0.5 in the same department (or even separate units).
Zero FTEs
Some universities have "zero FTE" positions. This is often used to indicate affiliate faculty. For example, Prof. Alice could be 0.5 FTE in Math, 0.5 FTE in CompSci, but also have a 0.0 FTE slot in Physics.
Adjunct FTE
Adjuncts are occasionally included in FTE but the exact calculation of an adjunct to a regular FTE varies considerably by university.

Other Variations
Bifurcated FTE Ranks: Some universities have separate "senior faculty (tenured)" FTE and "junior faculty (untenured)" FTE calculations, so that a 4 unit program may have 2 senior FTE and 2 junior FTE.
More than 1.0 FTE: Some universities also allow for someone to have more than 1.0 FTE. Since 1.0 FTE is calculated on a 9 month term (in the United States), one could conceivably have up to a 1.33 FTE by working through the summer. The NSF and others often restrict summer salary to .25 so the max under those grants is 1.25 FTE.
For student enrollment
Student enrollment can also be measured in FTE. "FTE enrollment" is computed as the sum of credits carried by all enrolled students, divided by the number of credits in a full-time load at that institution, school, or department.
For example, at the University of Colorado, a full-time undergraduate load is 30 credits a year, and a full-time graduate load is 24 credits per year, therefore

Student Full-Time Equivalent Enrollment (SFTE) = total undergraduate student credit hours in a fiscal year divided by 30 plus total graduate student credit hours in a fiscal year divided by 24

This measure may be used for budgeting, resource allocation between departments or within a department, facilities planning, faculty hiring, and other similar considerations.

(since you went with the community wiki approach, I edited this answer to include student FTE rather than posting a new answer, hope that's OK)


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Google Scholar duplicate entries
It's been a couple of days now since my Google Scholar profile has duplicated all my article entries. Indeed, it is listing all my papers in chronological order as it used to, but now if I push the button "show others" at the end of the page, a whole new bunch of duplicate papers appear. I tried to manually merge those duplicates together,  but  this function doesn't work. How can I solve this issue?

Looks like a bug. I can see this in profiles which I am sure did not show this behaviour before. I just saw one paper that is duplicated five times in a single profile. But the duplication seems to be in the listing on the profile, the entries themselves appear to be identical.

This was indeed a bug. After a few days, the problem is gone.

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

Not a verified solution but it probably helps: on arXiv the function "Journal ref" allows you to add a DOI or similar qualifier (once available) to your pre-print to associate it with the actual publication. This probably helps Google with the association; and it's anyway a good thing to do for completeness (and possibly copyright).

Google Scholar will eventually find the IEEE version of the paper. Just give it some time.
See the last item of the "coverage" page of the Google scholar FAQ and the second item of the "search tips" page.

It's almost 6 months that the IEEE version isn't indexed in Scholar. Is it normal?

What has been 6 months? Has it taken 6 months for the article to be published on IEEE Xplore, or has it been published on IEEE Xplore for 6 months and has google still not found it?

The second one. It's almost six months that the article has appeared in IEEE Xplore, but still Scholar couldn't find it.

I agree with this answer. It sometimes takes up to a year for records in Google Scholar to update. I've checked that other papers presented at the same workshop are available from IEEE Xplore, which means Google Scholar is aware of the workshop. Chances are the record for your paper will reflect the IEEE Xplore version when they roll out the next major update (as it says in the FAQ, they do this roughly once a year). This issue is sometimes referred to as "Google Scholar preprint bug" http://serialmentor.com/blog/2014/11/1/the-google-scholar-preprint-bug

In such a case the best way to make Google scholar give more intention to your paper is by adding it manually using My Citation (scholar.google.com/citations) section in your Goole scholar account (you can create one if you don't have using your institution email).
Press on Add button.

Click on "Add article manually". Fill the form and press Save.

After you add the paper details successfully, wait for about month until Google index your work.
Can I know if your IEEE paper appears in Google.com?

No, it does not appear on Google.com. Only its arXiv version shows up. Do you know why?

Can you mention your paper title?

Actually I have almost four papers experiencing the same issue (both published in arXiv and Xplore but not correctly indexed by Scholar). One is, for example, Multi-Connectivity in 5G mmWave Cellular Networks.

if you search using ("Multi-connectivity in 5G mmWave cellular networks" IEEE) you will find your paper was indexed by google. However, I think it does not appear on google scholar because Google alg find arXiv version is better because it has a full text, unlike IEEE that has abstract only.

Can I know why you are worried about the unavailability of IEEE version on Google scholar? The citation will go to you form any version

Unfortunately not. As I asked in another question (http://academia.stackexchange.com/questions/79859/new-references-of-a-second-version-arxiv-paper-dont-added-in-google-scholar) Scholar is not able to retrieve all the new references added in a second version arXiv paper. If it were able to point to the IEEE version, it would recognize the missing references.

Try to add manually as mention in my answer. Maybe after mention IEEE journal in "Publisher" field it becomes recognized.

Whatever you do manually only changes the way you personal GS page looks like. So that is not a solution for the question

@mgiordi The paper "Multi-connectivity in 5G mmWave cellular networks" still points to the arXiv version. This worries me too. I use Google Scholar button to do referencing. The problem is that if there are others like me if IEEE version does not come up then I might lose important citation count for my paper. The OP could be worried about the same problem.


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An invitation to join the editorial board of a newly launched journal
I am in the first months of my postdoctoral research, where I work in a highly reputed laboratory.
Recently, I got an invitation to join the editorial board of a newly engaged journal. They invited me because of one paper I published during my PhD, which perfectly fits within the scope of the journal. Now, I am wondering whether I should accept or not. I do not know the criteria, based on which I should take my decision. Any suggestion!

I get plenty of those mails, most of the time, the journal name is rather odd ("Journal of Research"), or doesn't fit to my work. I tend to delete them, thinking they are some kind of scam - similar to those asking to submit a paper within two weeks in order to save the journals reputation.

Do you know the editor or anyone else involved? (That's a good sign.) Is their website high quality? (Again, a good sign.)

Check the list of predatory Open Access journals, it this one or its publisher is there, you do not want to be associated with them. It seems that some predatory publishers also send emails in name of their editors/editors-in-chief/whatever without their approval.

@Mark I also receive these kinds of scams, but this one does not seem so, at least because of their description of my paper. I am wondering about the quality and reputation of this journal and how it will affect my academic career (positive or negative)

Such invitations are spam 95% of the time. I suggest you treat the invitation as such until you are convinced otherwise - i.e. by talking to the existing editors, looking up the publisher, etc.

Is it even possible in your field to have a journal editor which just started a postdoc? I have never heard of something like this in my own field.

There are two types of "new" journals:

A genuinely new journal
A predatory/semi-predatory spam journal

Deciding whether to join an editorial board is largely about trying to figure out which category your invitation falls into. The first step is the email itself - is it written in clear, professional language that suggests actual editors? Stop by the journal/publisher's website - does it look legitimate? Check into the publisher's other journals if they have them - do they look like actual journals, or junk journals?
The next step is looking at the existing editorial board/editors-in-chief. Are these people you recognize in your field, and would make sense as the people to be on board? Are many of the "big names" in your field conspicuously missing?
The final step, if it passes these checks, is to actually email the editor-in-chief to talk about the journal. This serves two purposes:

It's possible for a scam journal to list someone as an editor without them knowing - contacting them directly should confirm they are indeed the editor.
It lets you talk about the journal's goals, the expected workload, etc. to make an informed choice about whether or not you have time.


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Master Thesis for electrical engineering project
My master thesis is about doing an an upgrade/update of a previously created circuit board. I need to basically redo the whole thing because the new upgrades complete changed the board.
Now I know that there are different way to write a master thesis. As ususal most people at my university do it like this.

Introduction
Basics
Main Part
Conclusion

But some people told me that for a project like mine which is less theortical and more pratical it is better to write it "like a technical datasheet/user guide - so it doesn't just look like only academic" but I can't really understand what is meant by that ?
If I take look at a user guide like this: ESP32 should I build my master thesis around the same "layout" and split it something like this:

Overview
Schematic
PCB
Programming

But these User Guides are mainly written for people with technological background. So there is no "basics". Do I have to put this into aswell?
I hope you can help me there and get me some guidance.

Did the people who told you about the different structure include your thesis advisor? If not - have you considered asking them (as in - give a proposal of how you'd structure it and see what they think)?

My advisor said he 'doesn't really care, just that it needs to be done' - So I am free to do what I want there.

Some people? what kind of some people? the secretary of the department? the liberal students association?
These people opinion has a value only if they are or they were part of the commission reviewing master thesis. Are they?
And, how do you evaluate the opinion of these people against random people on their internet, where attendibility is given only by the upvotes AKA a biased, echo-chamber reinforced point of view?

Does your thesis have an 'audience'? For example, I've done a more practical Bachelor's thesis a few years back where the manager of the company that provided the project needed to understand the thesis (technical appendices were okay). Is there anything specified in your case?

In the United States, the institutions I know about have a prescribed form for organizing theses.  You don't say where you're from, but that may be true where you are as well.  So, the very first thing to do is find out whether there is a prescribed form at your institution..

Please put your comment:

My advisor said he 'doesn't really care, just that it needs to be
done' - So I am free to do what I want there

in the question. Note: you could not be more wrong about being free.
Based on your advisor's answer, this means that however you will do the thesis, your advisor will consider it done only if it respects the only way he thinks it must done.
So if you prepare the thesis in a different way from the way they expect it, the feedback you will receive will be "this is a userguide, not a thesis!" and you will have to rewrite it.
It is very simple how to proceed: during the weekend prepare a draft of the thesis, exactly as the numbered bullet points you provided, fill each chapter with 2-3 pages or general claims and some figures, send it next Monday morning to the thesis advisor and ask him/her if it would do the job.
Be sure to have a feedback before Thursday evening.


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Is a gold medalist at 2.96/4 GPA considered Summa cum laude or magna cum laude or none?
Indian university(IIT BHU) CGPA of 7.4/10 but highest in the class, hence gold medalist. Can anyone please guide how the translation to US academic system will look like in terms of the label?
Note: No idea if this matters but my 5 year course had 1.5 years of absolute marking scheme and 3.5 years of relative grading.

This is up to your university. "Honors" can only be assigned by the university, not assumed. And, numeric GPA means different things in different systems. In the US, Summa Cum Laude might require 3.9/4, for example. Magna = 3.7, perhaps.

The Latin-named honors (e..g, summa cum laude) would be granted by graduating school. If your school doesn't have them, then you you would not get the honor.

I don't think it is a good idea to convert your grade like that. And why can't you just say "gold medalist" and "highest in class" where you need to, e.g. in your CV?

@GoodDeeds This is specifically for forms where they ask if you have graduated normally or with some distinction/cum laudes etc. If I choose graduated normally, there is no opportunity to show the meaning of my (low) GPA.

Unless your university specifically confers an honor, you don't hold it.The three typical Latin honors have different meaning in different universities, if they have any meaning at all. And, 2.96/4.0 would not be considered very high if earned in a US university.
But that last bit means nothing as the systems are very different and grades are assigned very differently. I think it might be very difficult to impossible to achieve 9.something/10 in India, but don't have any experience. Getting 4.0/4.0 in the US is fairly common, actually and most folks bound for graduate study have something like 3.5 or better (but it varies and lots of other things "count").
If you apply for a graduate program in the US, the university is very likely to be able to do a fair translation of your India-earned grades into something that a US faculty member could evaluate. They have a lot of experience with it.
But, in general, don't claim honors that haven't be officially awarded by some organization that has the authority to do so.

At my old university, the breakout was 3.5/4.0 for Cum Laude, 3.7 for Magna, and 3.9 for Summa. My diploma shows Cum Laude, and putting it on the diploma would be typical if it is earned. I think those numbers are common, but I'm pretty sure they aren't universal.

Graduating "first" in your class has little actual meaning in the US other than something nice to tell your mom. It can be given meaning by a faculty member who writes a letter of recommendation, but there is no real official "honor". The Valedictorian at a US university might be awarded to the highest performing student overall, but that is across all majors (specialties). The valedictorian typically gives a short speech at the graduation ceremony. But even that is mostly just a "bragging point".

Thanks for explaining so well. My university had a low scoring methodology for first 3 semesters and they also changed the grading system for last 2 semesters (total soup!)
So even being top of the class I have a 'low' GPA. Most of the application forms just ask your GPA and then any additional honor - with the options never having a "top of class" field. I don't claim distinction or any of the cum-laude-s as you said it wouldn't be right to claim what isn't conferred.
To your point of translation of grades, is there any content on this for more info?


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Page numbers in cumulative dissertation
I am writing a cumulative dissertation. In the main file I have an introduction and summaries of the publications. The pages all include page numbers. The publications I include into the main file however already have page numbers. What is the correct way to handle this? Right now I'm not showing the pager numbers of the main file when a publication is shown.

In case you write your thesis with LaTeX, you may comfortably include external .pdf files (e.g., the .pdf of the publisher's version of your publication, preprints, etc.) with the usepackage pdfpages.  From there, you may reference them easily, e.g., in the table of contents, because if not set to fitpaper the outer page counting of your thesis still will be intelligible on these pages. A gentle discern between the "normal pages" and these including your publication is to enable a fine frame on the later.  Test it with other packages already in use, and once you have a minimal example in hand ask your supervisor if s/he is fine with it.
For papers submitted but not yet "in print", you may use a template like this of those by the journal as a preview.


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Can FERPA or privacy laws be used to censor medical information on my college transcript?
I had to medically withdraw from one semester at an American university due to documented illness. My transcripts indicate that the withdrawal is due to a medical reason. Can I use FERPA or other American privacy laws to censor this information from my transcripts? The withdrawal was during the COVID-19 pandemic but the illness is unrelated to it.

Perhaps better asked of a lawyer.

https://studentprivacy.ed.gov/node/548/#0.1_se34.1.99_120 May be a starting point

It is better to have a withdrawal with a reason than a withdrawal without a reason on your transcript.  I see no possibility of the withdrawal being removed, as the point of transcripts is to record such things.

@JonCuster: You'd have to argue that the mere phrase "medical reasons" violated your privacy, which I don't think the university (or for that matter a court) is likely to agree with.

FERPA already gives you privacy by forbidding the university from releasing your transcript to anyone without permission from you.  It doesn't give you the right to dictate what goes or doesn't go on your transcript (obviously!) though it does give you rights to have errors corrected.  There are medical privacy laws, but I don't think "withdrew for medical reasons" is enough detail to violate those.

@NateEldredge - they might get it reduced to ‘withdrew’ without the fact it was medical. Whether that is the best thing for the future is their concern.

Perhaps you can simply ask the university to remove the reason for the withdrawal from the transcript. Whether or not it violates any laws to include the reason, personally I think it’s a reasonable request and can’t think of a reason why from the institution’s point of view writing “medical reasons” is of any more use or educational relevance to anyone than “personal reasons” or simply “withdrew”. So they may simply end up agreeing to your request.

Just to be sure, when you say "due to a medical reason" does the transcript indeed say just "withdrawn for medical reasons" or does it actually mention the specific condition, as in "withdrawn due to colon cancer treatment". That makes a huge difference.

@TooTea They don't specify the actual medical condition. Just a general statement that states that the withdrawal was due to a medical condition.
I was hoping that the whole semester could be censored from my transcripts. If not, then I actually would prefer to have the statement in my transcript because it explains why I withdrew.

I shared my question on avvo.com, which is a website that connects individuals with experienced lawyers amongst other things. Two education law attornies from Colorado and Massachusetts responded to my question on avvo.com:

No, FERPA does not give you any authority to control what appears in your educational records. It limits who the school can release your records to, but it does not direct what information the school keeps in your records.

No. A medical withdraw is not, in and of itself, a type of confidential information as that status is generic in nature. The school would be prevented from disclosing the specific nature of the medical issue (that is more a [HIPAA] issue). As stated in the other answer, FERPA control who can see your educational records, it doesn't necessarily control the content. The issue is like credit reporting. A person's credit report can contain medical debt that is in collection. The mere fact that a person sought medical treatment or has medical issues is not confidential.

Reference:
https://web.archive.org/web/20200819212608/https://www.avvo.com/legal-answers/can-ferpa-privacy-laws-be-used-to-censor-informati-4958767.html

Note that in the answer on another site you received, the person answering has incorrectly written "HIPPA" rather than "HIPAA". Could be an honest mistake, but I would doubt that someone who doesn't know the acronym for the single most important medical privacy law in the US is an expert in that area, regardless of their star rating  and regardless of whether it turns out they are correct. Also importantly: HIPAA doesn't apply to educational institutions. So that's strike 2 for them.

https://www.hhs.gov/hipaa/for-professionals/faq/518/does-ferpa-or-hipaa-apply-to-records-on-students-at-health-clinics/index.html

@BryanKrause Thank you for the remark. I agree that the first typo was probably an honest mistake. Since HIPAA doesn't apply to educational institutions, that doesn't detract from the essence of the attorneys' answer, which is that the transcripts cannot be modified.

The answers don't say the transcripts cannot be modified, they say that FERPA does not mandate that they be modified.

@BryanKrause So there is still a possibility that some privacy laws can be used to mandate that my transcripts be modified. That's definitely an interesting research topic. However, since the attornies didn't recommend anything, I personally wouldn't pursue the question any further.


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Professor obligated to take the lab of the course whilst having the course
In our university, the professor has obliged the students to take the lab and the course together. In this university the laboratory courses cannot be emergency dropped from a semester.
The laboratory has to be taken after or while having the course itself.  The course itself is three  credits and the lab course is one credit.  The professor uses the lab class for doing the assignments which were done using a simulation at home.
He claimed that the course together is complex enough to merit four credits.
There are some problems:

Those who have passed the course before and got the laboratory course this semester have to take the pressure of a four credit course while this is formally one of our rights in this university.
Those who need to do the emergency removal of the course cannot do it, because the lab course is required.

The professor is not argumentative and doesn't take steps to make the situation more tolerable.
He claims that if he didn't make the obligation to take the course a complex with its lab it wasn't something good for you and the current situation is a good point for you for being less under pressure due to these two being a complex. This is against what he claimed at the start of the course.
Who's wrong here? Should we start having talks with authorities?

You need to solve this with your university, we cannot help. Talk to the dean or the person responsible for the content of the programme.

Would you think about this differently if there was only one course in the registration system, a 4-credit lab+lecture course?

Hi Parsa, welcome to Ac.SE. I edited your post for English mostly, however, there are some things I cannot understand that I think will help people understand your problems better. Namely, "while this is formally one of our rights in this university" I don't understand as well as what is now the second-to-last paragraph.

For example, why are you bringing up the emergency drop ("remove")? Do you have a personal emergency that you believe merits this?

It is not uncommon to have a lab section attached to the course and separate credit given for the lab section.  Indeed, in many cases it doesn't make much sense to register in the lab section without taking the course as the labs are quasi-dependent on the material covered in the course.
At least where I work, students who repeat a course with a lab section can get permission from the instructor to use their own lab marks in the current enrolment year.  This is at the discretion of the instructor and there are various situations where this permission is not granted.  Administration is not involved: the instructor just looks up their spreadsheet and copy-paste the marks from the previous year to the current year.  It is certainly not possible to do the lab separately from the course as a stand-alone credit, and credit for the lab is given concurrently with credit for the theory part of the course, and you cannot get credit for the lab without getting credit for the course.
There is nothing to do if you have an uncooperative instructor, except possibly plead your case to the administration, although this is unlikely to solve your problem in the short term unless the instructor is clearly in violation of university policy.

I have had exactly this problem when teaching introductory physics classes. In my case, my concern was that desperate students were getting turned away from lecture because there were no spots in lab. Then a few weeks later when students were dropping the class, there were empty seats in both lecture and lab. Seemed like such a simple fix, but I banged on the pipes a little and was unable to fix it.
So on one hand, I agree this is a very annoying situation -- everything from the policy itself to your professor's attitude seem annoying. On the other hand, I seriously doubt you will be able to change this policy. By all means, write to the dean or department chair if you want to; they cannot fix problems that they don't know about. But unfortunately, I predict they will defer to your professor's judgment. And, be aware that if you complain about your professor before the class ends, that could lead to an awkward situation for the next few months.


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Declining PhD offer after accepting
I’ve been in the process of deciding on a PhD program for a while now and last week I thought I had made the right decision, so I went through with it and accepted the offer. For background, the institution I accepted is the same one I did my undergrad with and the advisor I would be working with is someone I’ve done research with and have gotten close to. They had been pushing for me to continue working with them and once I had accepted the offer I told them and they were really happy to hear.
Now I worry that I betrayed the choice my gut was telling me to pick, which was another institution that is smaller but very friendly with a lot of people working on things I might be more interested in. I declined that offer as soon as I accepted the other one, but I’ve since talked with them and was put back on a waiting list.
I just need to know before I go through with anything else: how should I proceed without making things messy? I really think I’d like to change my decision (of course I’m not totally sure if it’s possible yet). But how would I tell my current advisor? Would it be totally wrong and unethical to do this? I feel as though this is a huge decision for my life and I want to make sure I’m in the right program for me. But I also don’t want to lose the connection I have with my current advisor who i really respect and look up to…

https://academia.stackexchange.com/questions/41105/rejecting-a-phd-offer-after-having-accepted-it-advice Does this answer your quetion?

I can't give you advice on how to tell someone you're going back on a decision, that's an interpersonal skill that depends heavily on the personalities and the relationship between the people involved, but to answer the academia question:

Would it be totally wrong and unethical to do this?

Absolutely not. You should not make a decision about the next 5-7 years of your life based on making your advisor feel bad. It sounds like you have a good relationship with them, and most people can understand that sometimes things change.
The earlier, the better of course, so your department can go to their waitlist (if they have one), and your advisor can begin making alternate plans.

How should I proceed without making things messy?

Thank them for their excellent supervision, apologize for making your decision after the "deadline" and express interest in seeing out existing projects and collaborating in the future (if applicable).
This answer is a long winded way of saying "just be polite about it."


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Submitting two articles to the same journal at the same time similar ideas but different surgeries?
I am part of two different labs that are studying very similar things. One is the impact of smoking on elbow or shoulder replacement, and the other is the impact of smoking on wrist replacement.
They both want to submit to the same journal within the same month, and I am afraid since I'm going to be an author on both papers (first on one, third on another) that I am putting both in jeopardy.

Related: https://academia.stackexchange.com/questions/178135/can-i-communicate-two-separate-articles-that-use-identical-experimental-test-pro

Not an answer, not even close. But I think worth noting that Einstein published four papers in the same journal in 1905, his annus mirabilus: https://guides.loc.gov/einstein-annus-mirabilis/1905-papers

I doubt that being the author on both papers will, in itself, have any effect. If you remove yourself from either, in other words, I'd expect the decision of the publisher to be unchanged.
But the issue is that they seem awfully similar, though it isn't my field. Unless you have some reason why the effect should be different for one joint rather than another, I'd worry that the publisher won't want both of them.
However, if the methodologies (surgical and/or research) of the papers are sufficiently different, which you haven't suggested, then a publisher might be interested in both.
Is is possible that you combine the two papers in to one? As an outsider in the field, this would seem like a more interesting paper to a publisher, even if there are some differences in outcomes. It surprises me that you haven't suggested this already, since you know of the similarities.
FWIW, there are no ethical issues in submitting both papers, whether at the same time or not and no matter the authorship.

re combining into one, the OP is 1st auth on one and someone else is 1st auth on the second. So which academic is it who doesn't get 1st authorship? I can see Alice looking up at us from the bottom of that hole.

Medical research can be surprisingly specialized; that said, to me this sounds like fairly low-impact research on both studies. I presume these are retrospective correlational analyses, a dime-a-dozen in the medical field, but still useful as a collective whole.