Admission in research based Master's/Doctoral programme with a bachelor's from a low-ranked University in India I applied in Master's programmes in Europe / Asia (mostly Germany) this year and most of them were rejected or are still pending. My GPA in the Bachelor's is 7.19 / 10 while my TOELF iBT score is 100 / 120. Most of the Universities stated on their websites that the GRE (General or Subject) is optional, so I did not take the GRE.

After getting so many rejections and still being unable to figure out why, I am now thinking of strengthening my application to apply again in fall 2014. I have mailed universities / professors inquiring about reasons for rejection / shortcomings of my application, but none have replied. The only reply I get is that there were a lot of applications and mine just failed to compete with them.

I wish to know more about why my applications failed and how to improve? Also, as I don't know anyone around, I prepared my Statement of Purpose, Letter of Recommendations, Research Proposal, etc by going through the internet and information on website of universities (I did not copy-paste, but used the tips on how to write and stuff). I have no idea if the reason for my failed applications were because of low GPA / no GRE score or ill-prepared statement / research plan. Also, where can I get these checked and get suggestions on improving them?

I am very passionate about Artificial Intelligence, Machine Learning and Ubiquitous Computing. I am planning on quitting my job at Oracle Financial Services (where I'm working as as Associate Consultant, writing code since SEP 2011 after my Bachelor's) to prepare for my application and dedicate full time and energy. I am aiming for admission in top 20 universities for Computer Science of the world and also aiming for a good scholarship. I want to appear for GRE later this year and get very good scores to try to compensate for my low GPA. But, when I checked few top universities (like MIT), it was mentioned they don't accept GRE scores. How can I try and get into such universities?

My goal is to complete my Master's, PhD and then continue researching on my areas of interest. Furthermore, the Subject GRE for Computer Science has been discontinued as per the ETS website!

Is there any hope of getting in top universities with a Bachelor's degree from an unknown university which is practically nowhere in the rankings? What to do now and how to do it, I am pretty confused and hope that someone here can help me.

Thanks for your time.

Rahul

Focusing on test scores will not get you into MIT.

You need research experience — real, world-class, publication-quality, independent research experience.  A paper at a recognizable (from MIT) conference or workshop would be a big plus.  The top students from the various IITs have such experience.

You need a statement that clearly and compellingly describes your research interests, experience, and vision, with enough specific technical detail to be credible.  As an example: Describe a recent result (not just a paper title!) of your potential advisor, and suggest a credible strategy for applying or improving it.  Also, your statement should frame your ambition in terms of "doing great research", not in terms of "getting into MIT".  The top students from the various IITs write such statements.

You need recommendation letters from well-known (at MIT) academics that praise your research potential in personal, specific, and credible detail, with positive comparisons against other students from your home institution who have gone on to a top-10 PhD program.  Your recommenders must write the letters themselves; you should never even see them.  In particular, you should explicitly waive your right to see the letters later, if such a waiver is possible; most US schools offer such a waiver in their recommendation forms.  The top students from the various IITs have letters like this.

You need contacts.  Or more accurately, your recommenders need contacts.  Coming from "an unknown university" with a "low GPA", there is a serious risk that nobody will even open your application.  If one of your recommenders knows someone at MIT, either personally or professionally, ask them to send a quick email (or have a hallway conversation at a conference) saying "Hey, we have this great student Rahul Thakur who's applying to your department; you should take a look!"  Sending such an email yourself is unlikely to help.  CS professors get tons of emails from random students at unknown universities; we call it "spam".  The top students from the various IITs have these contacts.

You need some strategy.  All else being equal, it is harder to gain admission to top CS PhD programs to study AI than to study other areas.   AI seems to be the default areas for really smart, talented, qualified students who really have no idea what they want to do.  Machine learning is either a subset or a superset of AI, depending on your religion.  (Theory suffers from the same effect, to a smaller extent.)  In your case, you're probably better off emphasizing your interest in ubiquitous computing in your statement.  But remember, you need specific and credible technical detail.

Finally, you need luck.  Graduate admissions is an inherently random process; no one should apply to MIT expecting to be admitted.  Coming from an unknown university, your chances of admission are smaller than someone with exactly the same application coming from a highly-ranked school.  Aiming only for MIT is foolish; limiting yourself to top-20 departments may be foolish as well.  Don't rob yourself of opportunities!

After all, your real goal is to do great research, not to get into a top-20 program.  Right?


Should we do literature search in Incognito mode? I found a claim that literature search (in Google Scholar, ScienceDirect, Scopus, Web of Science, etc) should be performed in Incognito/Private Browsing mode.

According to the claim, search results may be influenced by browser cookies (presumably those about previous literature searches), and if a user account is used, they may be influenced by the scholar's information (interests, etc.) as recorded by the search engine.

If that is correct, authors of systematic reviews may need to report how they access literature databases and search engines.

Is there any evidence to support that claim?

It's probably good to resist treating any search engine as a "black box." That is, you probably should not simply accept the results without suspicion.

There are a number of factors that affect Google searches. Your search history, if you are doing the usual thing, is clearly one of them. Just a few pages explaining this.

https://www.bluecorona.com/blog/google-ranking-factors-2018

https://www.wsoaonline.com/does-your-internet-history-effect-google-search-results/

https://www.webpresencesolutions.net/7-reasons-google-search-results-vary-dramatically/

https://www.link-assistant.com/news/personalized-search.html

What it means is, private browsing would not hurt. And you probably should not stop with Google. You should probably use a bunch of search engines. Bing, Yahoo, DuckDuckGo, the archive searches on any journal archive you can get that is relevant, more if you can.

And you should be aware of the possibility that somebody has paid to have certain search results pushed up the list. Possibly on more than one search engine.

And then you should carefully examine the results to see if what you have achieved has validity. You should try to unravel any bias or detect any gaps as far as reasonable. Look at your data the way a hostile competitor would look at it and try to detect any flaws before you send it to a journal.

For example: Is there a point of view you are aware of that has been left out? Even if you think that POV is totally wrong, having the search engines decide for you could be embarrassing. Is one point of view clearly given undue precedence? Even if you prefer that POV you should be concerned if a search engine offered you only stuff you agree with. Is one source artificially cloned into multiple sources? Is a group of sources, that you know to be independent, artificially collapsed into a single source? And so on.


Uploading an elaborated proof from a published paper on arxiv I have elaborated a proof from a paper published on arxiv to make it more intuitive. There is no new innovation in my approach nor does it review the other related proofs for the problem. Is it worthwhile uploading this to arxiv?

I do believe it will add value to the understanding for a newcomer to the field, but it doesn't really add value to anyone who is an expert in the field.

Yes, I think that's a great idea.  arXiv is a good place for expository work like this, which may be of value to the scientific community (experts or learners) but isn't novel enough to be published in a journal.


Best technique for prolonged study According to my daily schedule I need to study for long hourd each day including weekdays and weekends sometimes I find that this is just too much sometimes.

What are some methods to get the optimal efficiency while studying.

Can you suggest me some great tips for effective study or in general give me some tips and techniques which I  should follow so that I can get the maximum output for my input.

It's actually for an exam , which is after 1 year and the syllabus is vast ( 2 years of schooling worth of syllabus) and of  Maths(Basic algebra, Calculus, Co-ordinate Geometry ) Physics(mechanics electrodynamics, modern physics and optics) And Chemistry (basic organic inorganic,physical) (about 30 chapters each)

So also some methods to remember what I study for long time might be really helpful :)

Since you have tagged it exams, let me offer some hints. I don't know what subject, so I'll assume something like math or CS.

The best way to study for exams is not to have to do it at all. That is to say, make sure that you know the answers to most of the questions likely to come up in an exam long before the date of the exam.

In order to learn something deeply, you need to use repetition and feedback. The repetition means doing exercises, working problems, writing programs, etc. In other fields it might mean writing on topics of the course. The feedback part means that you have to get someone to comment on your work on the exercises. Normally that is the professor grading your work, but you can also use study groups to get feedback from peers (and give it to them as well). For some things you can use some form of automation to get feedback.

But if your main technique is memorization it will likely be ineffective. It will be ineffective for most people, at least. It would be possible to memorize something like the complete text of a calculus book, for example, while actually understanding almost nothing and also not being able to solve anything beyond the easiest problems. Practice - reinforcement - and feedback.

And you also want to give you brain a rest. You aren't a machine that works efficiently as long as it has fuel. Your brain needs periods of rest to actually allow it to synthesize the ideas that you are trying to learn. Pushing it constantly leads to less and less efficient working. Take a nap, or use physical activity to recharge.


Is it required for a supervisor to understand the technicality of his PhD student's research In my department, there are 2 styles for a supervisor to supervise student.

In the first one, a supervisor understands his PhD student's research deep enough to provide technical advices such as which algorithms to try, possible solutions for a problem, or even to be able to read and comment on the source code.

In the second one, a supervisor understands his PhD student's research just enough to comment about the feasibility and novelty of the research and its contribution, but does not understand exactly how the research is carried out.

In my opinion, the second style is easier for a supervisor to not only supervise his students but also looks for new ones, as his candidate pool is larger. It also helps a supervisor to have more diversitized research group.

On the other hand, it is harder a supervisor who has deep knowledge about the research of his students to find a new one, as he can only look for those whose research is close to his. But this makes the research of his group more focused.

So, I wonder which one is a common practice, and if a supervisor should have deep understanding, e.g. technical level, about the research of his student.

My field is computer science but answers from other fields are also welcome.

Both types of mentors can be good.  A good mentor of the second type will make sure that there is expertise somewhere that a student can go to for advice and help if called for.


Research dependent on future discovery? I work in a field of data-driven modeling of physical systems (think simulating weather patterns, particle interations, solid structures, etc.). As the name implies, producing a good model depends on access to high-quality, or "high-fidelity" data that it taken to be the truth, or a fairly accurate representation of nature or an experiment. However, the system I am trying to model is one which nobody can consistently produce simulations that exactly match experiments. This is not a huge problem for me, as I simply use the best simulations that reproduce experiments in a general, qualitative sense. I am working to develop good data-driven models which can be generalized to any variety of physical systems, not just my particularly difficult system. Hopefully there will be a point in the future where I have access to good data, but that time is not now.

However, many researchers who have been attempting to create better high-fidelity models look down on this, claiming that there is no point trying to simulate a system if the inputs don't match nature exactly. "Garbage in, garbage out" is the standard derogatory epithet. This strikes me as odd, since they are the ones tasked with producing the accurate high-fidelity models, and they cannot do it. It also strikes me as anti-intellectual, spurning an avenue of research which will have measurable benefit once they make their models better.

Am I wrong in this sentiment? Is it stupid to pursue an area of research that is essentially dependent on future discoveries and improvements in modern methods? Are there any examples out there of research that was performed under the assumption that future methods would make it useful?

There are research papers that are discovered 20-30 years later and new interesting research is build on it, thanks to the internet and digital indexing nowadays. So if you can (?) publish your research and live for it and can finance it, nothing speaks against following your interest and intuition (e.g. Einstein)

I will take an approach to also work on very risky, unknown, niche questions the next years, apart from working on a funded research project fulfilling some TRL levels required. This gives me some freedom of research and I think I have to risk it to yield some possible high-impact papers. Most tenured researchers always work on several topics:

you have to risk something in research (money, time, ...)
it's diversification of such risks
you are paid to find original new stuff in comparison to industry research, not just climb up the TRL ladder (although several TRL steps are not covered by industry research and developement)

But working solely on a very risky topic with unclear future outcome or likelihood of publication is like betting all your money on one stock.

No phyiscal simulation software I know matches nature exactly. How could it?! Nature is nonlinear and in complex systems with many degrees of freedom any model is imperfect if you don't simulate the H-atom. If your methods/models are original and of significance is hard to answer here without knowledge of your exact research topic.

To take up Nates comment, mathematical topology knowledge is nowadays of tremendous importance in modern solid state physics, although mathematicians work probably since centuries on it.

If your research is only "useful" in dependence of progress in other related research areas/methods (as you seem to think and qualify), than it doesn't look like fundamental research to me, because you wouldn't and don't have to think about usefulness. Rather applied research, and without any people interested in it or its results, this could be riding a dead horse.

In conclusion I think you have to make a strategic decision and risk assessment, if you want to do research on fundamental aspects/questions or move closer to the research methods/data/questions of your peers. Putting them as wrong or having a finite horizon is probably a dead end for you, also most of fundamental research ideas end like this. Currently your methodological approach and questions seem too distant for them. But doing and producing research that can be published in fundamental research vs. applied research journals is a huge career decision to make, as different requirements for significance and originality exist.


Should I request a letter of recommendation from current employers that don't want me to leave? Let me explain in more detail... I currently occupy a fixed-term temporary faculty position that is set to expire at the end of this academic year. The position I have now will go up for a national search for a tenure-track appointment starting next academic year.

My current department head and Dean both have repeatedly expressed their desire that I apply for the tenure-track position and I intend to. However, there's no guarantee that I'll keep this position and I want to be employed next Fall. I have found another position that would be a good fit in case my current position goes to someone else (a very real possibility as my field has many qualified applicants and few jobs) and as part of their application they want current letters of recommendation.

I know my department head and Dean both would recommend me highly, but I see a potential conflict of interest. I'm also unsure if asking them for recommendations could be perceived as a slight and I don't want to burn any bridges at my current position because keeping it would be my first choice.

Another complicating factor is that this is my first university position and all other potential references either worked with me as a student or professional colleague in a non-academic capacity.

Any advice on the best course of action to take in my position?

Without further information, I would assume the department head and dean will behave ethically and ignore the conflict of interest.  They should understand you want to hedge against losing the competition for the tenure track position. Therefore you could use them as references.


Literature review and originality Everyday there are hundreds of papers published worldwide in every single area of study. I am mostly interested in architecture and environmental psychology.

A question arises how to assure that we select relevant literature review? or how to assure the originality of research?

For example more recently I am conducting a research on primary school children's perception of an ideal school. I am analyzing children's' drawing. Even my primary analysis reveals statistically significant differences between girls and boys. There are some studies conducted on gender differences similarly.

So how to assure the originality of the research when there many papers written in this area and despite reading over 100 papers there might be those that we are not aware of?

It all accounts to got much effort you believe you put in to your work.

Doing a good review isn't at all easy. It involves a whole lot of work to

collect relevant studies
collate them to groups
assess originality
connect the dots
produce illustration
coherently present the information

If that isn't enough, getting permission from authors and publishers to reuse relevant figures is another hassle. To add on, it would be an ordeal to manage 100+ references without a reference management system like LaTeX/BibTeX.

The point is that as you go through this process, you'll notice that your skill would gradually improve over time. I'm actually  going through this process at the time of writing this post. I came across a couple of double publication, extensively overlapped concepts, and inconclusive studies. These sort of items are the ones I filter out.

Hope this helps.


How much delay is normal in publication of a Special Issue? I submitted a paper to a special issue of a very reputed computer science journal. Now as per the original timelines, the special issue was expected to be published by this month with two cycles of revisions. However, there was an extension for a month in submission deadline.

I submitted the paper within the extended deadline and yet to receive even the reviewer comments (4 months since submission while as per timeline the period for first review was two months). During this time, the manuscript was in peer-review. It went to "Awaiting Decision" three weeks ago, but I am still to hear on any decision.

Since this is my first submission to a reputed journal, is it normal for special issues to be delayed to such an extent?

From my experience, special issues are rarely published on the announced date. The review process for papers submitted to the special issue should be as rigorous as for any other journal article and thus, may experience all the usual delays (referees not answering, promising a review but not delivering, contradicting reports…). The only difference is that the journal has announced a time frame for the whole process which puts a little more pressure on the handling editors. However, this does not necessarily imply that the whole process is any quicker (also note that the guest editors of a special issue may not be as experienced).

I do not know too much about the usual delays for papers in computer science, but for math, the times you describe still sound pretty short.


How to cost a researcher for a funding application? When you apply for academic/research funding, how exactly do you cost someone?

For instance, you want to have a research assistant working 1 day a week. Do you just divide annual salary of standard RA by five? Do you do the same for any other type of collaborator, like a post-doc, or an assistant professor? Such is the method suggested in this site. Or is there a more elaborated mechanism to decide that?

Anyone with experience on this? It's my first time applying for funding.

Your institution/the institution that will host the project almost certainly has a grants office for the department/school faculty. You absolutely need to be in contact to do this costing as the institution almost certainly has policies and systems to deal with this that you MUST use if the institution is to sign off on your application.

You don't say which country you are talking about, so let me answer for the UK.

There are two ways to add the costs of a person to a grant application in the UK:

Types of cost

Directly Allocated Costs and Directly Incurred Costs.

DI costs are the easiest to explain. A DI cost is when the university has to spend money it would not otherwise have spent. So - buying equipment for the study, or travel costs etc.

DA costs are where the university allocates a fraction of a resource it already pays for to the new project. So, for example, if a professor spends 10% of there time on the grant, then 10% of the prof's salary is "Allocated" to the grant. Universities like DA costs because they attract overheads, where as DI costs don't. Of course, this counts against you because it makes your grant more expensive to the funders.

So, when you cost up a person on a grant, you need to decide DA or DI. Generally, if you are allocating a part of the time of someone already employed by the university, it will be a DA cost. If you are hiring someone new, then it is a DI cost (there are exceptions to this, but in general).

For people that are already employed by the university, the university will have on its systems a "day rate" for that person. I.e. how much the university charges to have that person allocated to a project for a day. You then multiply this by the number of days a person will spend on the project.

For new people, the university will often have a set number of salary points at which they can be appointed, with an associated pre-calculated cost.

Our university has a costing tool that does all these calculations for you (and indeed, its use is mandatory, as it ensures that you have added all the correct extras, overheads, etc).

Costing a fraction of a person

Funders generally want to know how much time a person will spend on a project. It is common to express this as either % FTE (Full Time equivalent) or hours. So one day a week would be 20% FTE, or about 340 hour a year.

If you are employing someone the university already employs, then this is easy. You say "The university will allocate 20% of Jane  Doe's time to the project."

If you are going the DI route, then this is harder, because they reviewer might well say

"You want someone who has all these super advanced skills, but you will only employ them for 20% of there time for 18 months? Where on earth are you going to find someone who will agree to that?".

The alternative is you can name someone, even if they are not already employed. So you might say "We request salary and costs for 340 hours for a Dr. Chaudhuri to be employed as a research assistant, who will perform the vital roles of x, y and z".

My experience is that the more advanced the skills you want, the more skeptical reviewers will be of small FTEs, but that naming someone can go quite a long way to offsetting that. So 50% of an unnammed pre-doctoral technician is probably fine, but 20% of an unknown advanced software engineer is not, how ever 50% of the proven software engineer Dr. Alverez is probably okay.


Proper etiquette for withdrawing from an undergraduate research lab? I am currently involved in two very different Biology research labs in two different areas at my university, as an undergraduate volunteer. Lab A has been a long-term commitment of mine, and Lab B is a newer addition to my schedule but also a valuable experience, I think, but I have a choice coming up:

Before I graduate, I must complete one (and only one) senior capstone/thesis/etc lab project, that will almost certainly take up all the time I can dedicate to research outside of my regular coursework. I originally sought out and joined Lab B because it was looking like Lab A would not be able or willing to advise a capstone project, but now that is no longer the case - so I want to complete all my senior work at Lab A.

How do I politely tell Lab B that I do not plan to complete a capstone there after all, and probably won't even remain a volunteer in future semesters? (I don't recieve any payment or grades from them, but I know it does take time and effort to train new lab members so I feel bad about leaving without contributing a paper or presentation or something.)

Just tell them, politely and with appreciation for what they've offered you. Sooner rather than later, so that they can plan for your departure and maybe have you prepare a useful contribution in your remaining time there - wrap up whatever you've been doing, document your work, train another student to continue your project, or whatever else they need.

It is understood that students are balancing a lot of competing interests and opportunities; as long as you handle yourself professionally (give plenty of notice, remain engaged and work hard during your remaining time there even though you know you won't continue, etc.), there is nothing to feel bad about.


How to make an MD more appealing for a PhD program in basic research (neuroscience)? 1 year and a half away from completing my integrated MS in Medicine, I have decided that, once complete, I won't be pursuing life as a clinician and want to do research in Neuroscience instead.

Now, I already have a paper published (jointly) and two more almost ready to be submitted, after having worked in both the genetics and pharmacology labs, where my tasks ranged from data gathering ("pen and paper research") to Western Blotting and micro surgery in mice.

My grades are not very good though, and I'm looking for ways of making my CV more appealing, besides asking for a summer intership in one the groups I like (all in Germany by the way).

Would having a specialization (Neurology, Psych, etc) be a plus? On which skills should I work?

PhD programs are wanting to recruit people who are capable of doing advanced research. Grades are a proxy that people use to try to estimate which members of a population (almost none of whom have publications) will be able to acquire the skill set necessary to publish in the future. And, grades aren't a terribly good proxy. Therefore, the best thing you can do to get into a good grad program is going to be to keep publishing, and ideally in the best places possible.

If you publish research, then you'll be able to get letters of reference that talk about your skills as a writer and scientist that should offset any difficulty with your grades.

You'll need to tell some kind of story to tell in your cover letter about why your grades are bad, and how they don't represent the work you will do in your phd program. (ideally a letter writer should address this fact too).

Good luck!


Are there ethics concerns when students conduct human subjects research? It is common for faculty and graduate students to conduct human subjects research on undergraduate students.  Typically precautions are made to ensure that faculty do not use the teacher/student relationship to harm students.  For example, the faculty member may be required to finalise their grades before they find out which students consented to participate in the research.  This prevents the faculty member from incentivising students to participate by changing their grades.

Let's suppose that the researcher is an undergraduate student instead of a faculty member.  Are there risks associated with the student-student relationship?  Let's suppose it is a small university where students often know each other.

You can find a list of IRB Exemptions online. If the research falls under one of the exceptions then IRB consent won't be needed.

But otherwise, who does the research would be immaterial.

However, I think that special care should be taken here since undergraduate students might not be deeply aware of the ethical principles behind assuring the safety and privacy of human subjects. A naive approach could result in great harm.

So, at a minimum, even if the research falls into one of the exceptions, I would advice that a knowledgeable faculty member oversee any such research, both to educate the student researcher and to assure safety and privacy of subjects.

The other concerns you express are also valid, of course.

But, for the topline question, yes, there are always ethical concerns when humans are the subject of research. The concerns always need to be addressed, even in simple cases where it is clear no harm will result. How formally they need to be addressed is a function of the potential for harm as long as the formal rules are followed.


What is the "initial screen" for displaying a journal's copyright? I submitted my first journal paper to IEEE today, and when I considered posting it on ArXiv just to be safe from scooping, I noticed that IEEE has a policy for submitted content, which does not mention anything about the paper being allowed on ArXiv after it has been submitted to IEEE.

But, since IEEE allows posting a submitted paper on institutional repositories etc. as long as the copyright notice is displayed, I'm assuming I can publish it on ArXiv too, since they may have accidentally ommitted mentioning it, thinking that everyone would first put their pre-print on ArXiv and only then submit to IEEE. They didn't expect someone like me to submit to IEEE and then put it on ArXiv. Even TechRxiv's FAQ is ambiguous. Although IEEE's manual on page 88 states:

  IEEE does not restrict the rights of authors to use their
  IEEEcopyrighted articles in their own teaching, training, or work
  responsibilities, or those of their institutions or employers. In any
  preprint version archived by the author after submission, IEEE
  requires that IEEE will be credited as copyright holder. Upon
  publication of the work, authors are asked to include the article’s
  Digital Object Identifier (DOI).

To put my paper on ArXiv or TechRxiv now, I'll have to follow IEEE's policy of "IEEE must be credited as the copyright holder with the following statement included on the initial screen displaying IEEE-copyrighted material:". I don't understand what this "initial screen" is. Should I mention the copyright below the title of my paper or anywhere on the paper, as long as it is on the first page of the paper?

ps: TechRxiv mentions "Includes permission to reuse previously published or copyrighted material, if applicable". Again, I'm assuming I can submit to TechRxiv if I mention the copyright on the first page?

IEEE support mentioned that the paper can be uploaded to arXiv even after submitting to IEEE as long as this information is added to the first page of the article:

“© 20XX IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

By "initial screen" they meant for it to appear on the first page someplace. They didn't want to require it to appear "bottom of the left column" or "under the byline" because different repositories can have different displays. They just need it to be at the beginning of the article.


How can I get a postdoctoral position in neuroscience after completing my PhD in Mechanical Engineering? I recently completed my PhD in mechanical engineering and have been applying for postdocs in neuroscience for the past 5 months.
My field is dynamical systems theory and statistics, so I look up professors working in neuroscience who use those techniques and send them emails.  I have sent 3 dozen emails since February but I barely get any responses.
I got two interview requests in February. One of them rejected me. The other professor stopped replying to my emails after the first interview and he did not pay my interview travelling expenses either.
Sometimes it feels very hopeless. Please, please any recommendations, help or advice is very appreciated; especially from people who have changed their research area post-PhD.
This is my Cover letter.

Hi Dr. F,
I am writing apply for the postdoctoral position in your lab at Columbia. My training is in the domain of dynamical and nonlinear systems theory (primarily in mechanical systems) and I am interested in bridging to Neuroscience for my postdoctoral research.
My interest in the brain goes back almost a decade to my undergraduate
years when I took up a regular meditation practice. I am very
interested in the broad and mechanistic aspects of neural computation.
I am fascinated by the application of concepts such as dynamical
systems, stochastic modelling and network theory to the study of the
brain.
I completed my PhD in Mechanical Engineering at the Some University
under the advisement of Dr. Advisor (June 2018
Conferral). I have worked on a wide variety of problems so far -
powering micro-implants in brain using arterial blood pressure,
stochastic analysis of nonlinear vibration energy harvesters, the
spontaneous spinning of a rattleback on a vibrating surface, sound
wave manipulation in fluids, tunable mechanical metamaterials and
nonlinear metamaterials. I currently have 3 published manuscripts, 2
journal papers in peer review and 1 manuscript in preparation. I have
published 9  peer-reviewed conference papers. During my PhD, I have
worked on collaborative research projects with senior faculty and also
as a mentor to several undergraduate students. I previously earned a
Bachelors and Masters in Aerospace Engineering from Indian Institute
of Technology (IIT), Kharagpur (Class of 2013).
I am fascinated by > your recent research contributions. I really liked the paper titled "  Abstract Context Representations in Primate Amygdala and Prefrontal >Cortex" that used neural population decoders to show that
representations of task contexts appeared in the Amygdala in addition
to the PFC. Also intriguing was the preferential weakening of the
signal in the Amygdala when an error was committed.  I also liked you
paper titled "Energy efficient Neuromorphic classifiers" that
implemented a basic image classifier on a novel neuromorphic processor
and demonstrated significantly lesser energy and computational cost.
During my postdoc, I intend to apply for fellowships and possible
avenues of funding. I am interested in using my training in dynamical
systems and stochastic analysis to current research problems in
neuroscience and hone my technical skill-set to succeed in my future
independent research. My CV is attached. Please do not hesitate to
reach out to me for further inquiries.

I have the same issue, I recently completed my Ph.D. in computer science. Accordingly, I have applied several times for post-doc positions around the world and I was able to get only three interviews. Unfortunately, none of them was willing to give me the post-doc position.

Based on my short experience, it will be better to submit your application for a Fellowship with peer review process such as Marie Skłodowska-Curie programme. Open up to the world (China!).

Best wishes.


Legality of downloading books from websites such as Library Genesis I am an international student who will be joining a graduate program at a US university starting Fall '18. In my home country, I have used such websites as Library Genesis and BookFi to download textbooks, from such publishers as Springer etc., which are otherwise either not available or available at exorbitantly high prices in my home country.

Is it legal or illegal for graduate students to download books from such websites? Would I get into any trouble if I download textbooks from such websites either from my personal computer or from a university-owned computer?

The legality of possession of pirated content varies across countries. In many countries, it is perfectly legal to have copies of copyrighted content as long as you don't share it with others. In the US, downloading such content is illegal, but you are unlikely to get into trouble by having illegally copied content on your hard drive. I found a great answer on Quora by an attorney, parts of which I'm going to quote:

  Yes, it is illegal to download ("make copies") of material that is protected by copyright.  However, all that is illegal is not criminal.  Copyright for the most part is a civil statute, with civil remedies (i.e. the copyright holder sues you for money).

  Criminal copyright infringement is much more limited than civil copyright infringement.  The criminal portion of the Copyright Act (17 USC § 506) states that it is a criminal act to willfully infringe copyright 1) for the purposes of commercial advantage or private gain; 2) by reproducing or distributing within 180 days one or more copies of works with a retail value of more than $1,000; or 3) by distributing a work being prepared for commercial distribution (i.e. a work that has not yet been released for sale to the public by a copyright holder, but that will be made available or a movie that is currently playing in a theater).

It would be very difficult to classify what you describe as criminal. As long as you only download (and not share) publications for your private use, you are unlikely to have issues.

  For the average person, generally there won't be any criminal consequences under copyright law from having pirated items on your computer.  That isn't to say that a creative prosecutor couldn't make a case (particularly if you have file sharing software installed, in which case you could possibly be looking at a violation of the second prong of the statute).  But in the real world, this is not the type of crime that most police go snooping for when they decide to rummage through your laptop.

There are some cases where students are getting into trouble by using school equipment or connection to pirate content (mostly audio and video), so it is probably a good idea to keep this business on your private computer. You can further decrease the chances of any legal trouble by using TOR, VPN and keeping the pirated content in an encrypted container with a strong password.

tl;dr: It's illegal. As long as you don't get caught downloading the files, you are unlikely to get in trouble. It's more about your own views on the ethics of scientific publishing and copyright.


I have an accepted conference paper with a major error in it, should I ask for it to be changed? I have submitted a paper to a conference with a scientific error in it.

Essentially I have a concept and I have claimed it works in two conditions. Actually it only works in one of them. Technically, my experimental results are correct, but its only a small test and when extrapolated to full scale the error can be found and also actually predicted theoretically. The overall concept is still correct however for the other condition and I am still working on it in future research.

Should I ask for the paper to be changed? The conference isn't until 25th August but the submission deadline has passed.

I don't want a public document where people will repeat my experiments and find that some of what I have claimed is incorrect.

Yes!

Better to get it corrected than to be questioned/rejected later.


Should an Editorial be considered as a regular paper in CV, or should it be put in another section? Me an other colleagues organized an Special Issue of some Journal (indexed by ISI) and after having accepted some of the submitted papers (10 in total), we wrote an editorial, which will also appear in the Journal. Do you think such effortless papers can be considered or cited in a CV as a regular paper or should be put into another section?

I am editing an ISI listed journal and have also noticed that the editorials I or others write end up as if they were regular publications and obtain citations. I do not think they should be considered as such but believe it simply is a flaw in the system. The persons entering data or who made the system that scans published papers simply cannot distinguish between editorials and papers, despite the word "Editorial:" occurring in the title of such contributions in "my" journal. Since these editorials are not reviewed by others than the editors-in chief (in my case) they are not fully peer reviewed and would definitely not pass a regular review since they were never intended as journal articles.

So, do one want to put an editorial "paper" in the CV? I do not think it belongs under the heading of papers published in refereed journals. But, having written an editorial means you have been instrumental to produce a thematic journal issue and so you can list it in conjunction with "meriting academic missions" (or whatever you might call it). It will represent the journal issue and the work done there which, in my opinion, is probably worth more than a paper. The fact that it might also be cited can be taken as indicating interest in the jorunal issue that you have summarized in the editorial, but should be kept separate from regular papers.

I should add as a final note that the key for me is whether or not the contribution has been properly peer reviewed. I doubt many editorial receive proper peer review.


DBA vs. PhD Perception within Academia In my field (business administration) there are two main terminal degrees. One is a DBA (doctorate of business administration) and one is a PhD (business admin, economics, etc.). A DBA is focused on the application of theories (within a business) as opposed to the generation of new theories.

Is there any published research on the perception between these two terminal degrees? I'm concerned that a DBA is viewed as a "poor-man's PhD." While I am interested in what hiring committees think I am also concerned about the perceptions across academia.

While the experience that individual has gained throughout the course of their career is the best indicator of whether an individual has earned the respect of their peers, my impression is that the PhD title is generally more recognized with the public at large (basically those unfamiliar with how advanced degrees are awarded within academic institutions). This is purely a social construct that isn't germane to the field of advanced study.

I see the issue as someone calling a chiropractor a "Doctor" even though there is no award of an MD, or not understanding that a D.O. and an M.D. are basically the same thing.

Now, some universities in Europe do not traditionally award a "PhD" because they have a different three letter acronym for their doctorates. That does not mean that the individual is any less accomplished, its just a different system than the one in the US.

Perhaps one way to explain it to your students is to note what other fields have a similar award. In law, there are Juris Doctorates and PhDs; and in art there are MFAs and PhDs. The primary distinction appears to be what you have already recognized, that one is more about application than research.

To be a bit snarky, there are some fields of study altogether that do not get much appreciation, education being the main one with the award of the D.Ed. I do see some eye rolling when that one comes up, but I've also seen eye rolling from guys in the so called "pure" or "hard" sciences and their opinions of anyone in the humanities or "soft" sciences.

As to directly answer your question, Yes, there are published articles discussing the "perception" of one degree over another. I took a quick stroll on Google Scholar and found a number of published, peer-reviewed articles discussing this very question.

Here is one titled, "Doctoral Differences: Professional doctorates and PhDs compared".


What is a right way to criticize a published method in my paper? I am writing a research paper, and am fairly new to writing. I am working on a research topic that has not been touched too much. There has only been one other paper published regarding the same topic.

In this other paper, they have a fairly strange methodological approach that almost doesn't make use of the method at hand. My paper is an improvement of their approach; I am wondering what would be the best way to criticize their approach to present my own approach.

As Bob et al. failed to notice, we can actually do this...

There's no need to harshly criticize the authors of the first paper, however strange it seems, even if their approach is plainly wrong. After all, as you say, it appears that they are the only ones who actively worked on that research topic before you.

So, be constructive and build upon what they've done. For instance, you might write something like:

  Bob et al. [1] developed an algorithm to square the circle. This algorithm can square the circle in 198 steps. Here we present a modification of the original algorithm which can square the circle in just 87 steps. This modification is based on the observation that blah blah...


The initial hump of a master's program I started an MS in Computer Science program this Fall at a super top-tier university and I'm worried that I'm a bit in over my head. The program is extremely tough, and I'm nervous that as the semester goes on, the difficult courses I'm in are only going to get harder.

My questions are:

Is it normal for new graduate students to feel very overwhelmed and discouraged when they first start their program?
What happens when a graduate program realizes they've made a mistake in admission? What would qualify as a "mistake"?
If I'm feeling discouraged and/or overwhelmed by my courses, would it reflect poorly on my reputation in the program to speak to my advisor about it?

Is it normal for new graduate students to feel very overwhelmed and discouraged when they first start their program?

Yes, absolutely. 1000000x yes.

  What happens when a graduate program realizes they've made a mistake in admission? What would qualify as a "mistake"?

A "mistake" is admitting a student who is not capable of meeting minimum standards in the department (or at least, not now), and is
therefore dismissed from the program
for academic reasons. This is an unfortunate mistake for both the student and the department (as it represents quite a bit of wasted time, money, effort, and emotional energy on both sides), and so we try very hard to help students who are in the "danger zone" to recover and avoid dismissal.

Generally, a graduate program has very specific regulations describing how and under what circumstances a student is dismissed from the program for academics.  In my program, this starts with a semester of academic probation, so students have some warning that they're in danger of dismissal and have a chance to bring their grades up. Many students do manage to bring their grades up after a probation semester and successfully complete the program.

  If I'm feeling discouraged and/or overwhelmed by my courses, would it reflect poorly on my reputation in the program to speak to my advisor about it?

In my department, it would reflect well on you. It would show a maturity, self-awareness, and sense of responsiblity that your advisor probably wishes every student in the program had.


I need help with my potential PhD Supervisor who showed interest So I went to a University in Canada to speak with Graduate studies coordinator to learn more about the program. While visiting, I bumped into the Chair of the department who is one of the Supervisors that I would love to work with. When he realized I was there for a visit, he invited me to his office to discuss this further. I told him about my future plans and about me wanting to go into academia, and he suggested I skip Masters and roll into PhD instead (because I had 4 years of wet lab experience). He also mentioned that he is recruiting students for fall, and that he isnt guaranteeing anything now but does think I would be an excellent candidate. He asked about my GPA and when I told him he said it sounds good. Bottom line, he asked me to send him my CV and Transcript so he can check if I can fast track into PHD and insisted he would get back to me soon to advice me further. I emailed him on Thursday, (he checked my linkedin profile two hours after I emailed him). Today is Tuesday and he hasn't responded.

I know they can be very busy and I completely understand, but how should I follow up without sounding too annoying|? Should I do it through phone or email? And does him offering such on our initial non planned meeting sound promising? Would love to hear your feedbacks!

This is end of term, with classes to finish, assignments to return, exams to prepare, and if this person is the Chair all the non-sense that comes with the end of term: students complaining, special accommodation, etc.

If you have not heard in one month, start to worry.


Is it OK to send email to conference chairs asking for resubmission of the manuscript? I have submitted a messy manuscript to a conference due to the urgent deadline.
After a period of revision, I corrected some mistakes and tidied the manuscript.
Is it okay to send an email to the conference chair or somebody else asking to resubmit the manuscript? Or are there any other ways to resubmit?

I might have a slightly different take than @PsySp in his answer on this issue, but I think fundamentally we agree.

In my view, it's probably fair to email and ask the chair whether you can submit an updated version. But it's also fair for the chair to say no: like @PsySp says, deadlines exist for a reason and you can't assume that you're exempt from them. Get your house in order and build your paper in publishable form before the deadline comes up.


Cite NumPy in BibTex How to cite NumPy in BibTex?
The Scipy citing page recommends:

Travis E, Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).

Is it correct to use:
@Misc{numpy,
  author =    {Travis Oliphant},
  title =     {{NumPy}: A guide to {NumPy}},
  year =      {2006--},
  howpublished = {USA: Trelgol Publishing},
  url = "http://www.numpy.org/",
  note = {[Online; accessed <today>]}
 }

Or should I cite just SciPy?
Research Gate
On Research Gate, the citation suggested is:
@book{book,
author = {Oliphant, Travis},
year = {2006},
month = {01},
pages = {},
title = {Guide to NumPy}
}

Or cite as a book?

Looks right to me. That's how they ask to be cited, and it seems reasonable. Indeed, this discussion also agrees that citing the user manual is the right choice.


As a TA, I had sex with someone who turned out to be one of my students, what do I do? I'm a grad student and TA.

I was playing pool on campus and met some people who happened to be in a frat. We played together and they invited me to their frat party. Long story short, I got really drunk and ended up having sex with someone. I didn't realize that they were in my class until the morning (I have a lot of students).

What do I do? How do I make this right? I'm sure this is bad, but just how bad?

Note: I'm a department chair at a US university. The following represents my thoughts about your question assuming you are in the US. I will stick to comments pertaining to university policy. I am not a lawyer and am unqualified to offer any legal advice of any sort.

  What do I do? How do I make this right? I'm sure this is bad, but just how bad?

This is awkward, but if indeed you are telling the truth and you didn't realize the person you had sex with was your student at the time it happened, and assuming it was consensual and both of you are of legal age, I don't think it's that bad, if you now proceed to handle the situation correctly and with maturity.

The important thing (and I mean really, really, really important) is that you must immediately act to remove yourself from any position of authority over the student to avoid ending up in hot water over what is certain to be (if you fail to act as I am suggesting) a pretty bad violation of university policy, and potentially even legal trouble. That means speaking to the instructor for the class, telling them honestly exactly what happened (yeah awkward I know), and asking for their guidance about what needs to be done. (It's a good idea for that request to be documented in writing/email.) The department chair will likely need to become informed of the situation as well. My guess is they will either have to remove you from your role as TA for the class, or arrange for the student to switch to another TA if that is a practical option, and find ways to ensure you are not involved in grading or other assessments related to the student in question.

If the instructor and chair are sensible people, I don't expect that there will be any disciplinary action or other formal repercussions to what happened, although you should certainly expect some unpleasant discussions, possibly having to be interviewed by campus officials who handle sexual harassment and discrimination, receiving unpleasantly-worded memos counseling you about university sexual harassment policies, and similar headaches. It's also quite possible that the incident will cause the instructor for the course and/or the department chair (hopefully no one else in your department will need to learn about what happened) to form negative opinions about you. As I said, if they are reasonable and professional people they will keep those opinions to themselves and move on.

Finally, if the people who handle the incident  are not reasonable people, well, all sorts of things may happen, so you'd better make sure you protect yourself against unfair treatment by not committing any missteps that could end up making your situation worse. Such missteps may include trying to keep the incident secret from your department; telling about it but lying about some details (out of embarrassment or because you think those details make you look bad) or omitting important details; or any other immature/unethical/foolish behavior. Ultimately, as I said, you have a reasonable case to argue that you essentially didn't do anything (at least not knowingly, and not so far) that violates any university policies, so if you handle this with maturity chances are you should be fine.


Making your code publicly available: Does it have to undergo review? In cases when the authors would like to make their code available online after it is published, is it recommended for authors to make their code available for review when they submit technical papers for review and possible publication?

Side Note: The author may not necessarily choose to include his code for review because he is "hiding" something. The author may have questions like: (1) Is it the responsibility of the reviewer to review code? (2) What if one of the reviewers proves treacherous with the code? Even if he doesn't replicate the idea, he could add a few things to it and publish it without approving the initial submission for acceptance. For instance it had happened that a reviewer rejected a paper and now wants to publish an extension of such work. The rights of the author has to be respected to the letter especially for example a PhD contribution. The author must be confident that all these are addressed. Also, it is usually assumed that a good research is reproducible even when the code is not made available. Besides, several papers have earned the "respect" of researchers far and wide - and their source codes were not published.

For computer science conferences recently ACM introduced Artifact Review and Badging which incorporates code review in the usual publication review process. As far as I know currently it is not mandatory to submit your code for review but it is recommended and their future direction is to make code review mandatory.

From the ACM website:

  ... there remain many circumstances in which such enhanced review will be either infeasible or not possible. As a result, such review processes are encouraged, but remain completely optional for ACM journals and conferences, and when they are made available, it is recommended that participation by authors also be made optional.

If the venue you are interested in publishing at has the option of code review I would highly recommend it. Having your code reviewed by the conference reviewers will give your work more credibility if it passes the review process as your experiments are reproducible. Also the code review will potentially prevent any missed logical errors if any in your code, its always a good idea to have someone revise your work.

From the ACM website:

  A variety of recent studies, primarily in the biomedical field, have revealed that an uncomfortably large number of research results found in the literature fail this test, because of sloppy experimental methods, flawed statistical analyses, or in rare cases, fraud.

In response to your addendum side note: the best you can do is posting your code to your website or a public code repository such as GitHub which gives you the option of choosing from several copyright licenses you can publicize your code under, the list includes but is not limited to (GNU v3.0, MIT, BSD). These licenses will not prevent someone malicious from stealing your code or work and claiming that it is theirs, but it will give you the bases to claim that someone tried to steal your work. Also a common practice I have seen is adding a summary or a paragraph in each file of your source code saying that the following code is protected by xyz license.


How to encourage and motivate undergraduates to regularly and independently work on problem sets? I'm wondering how can a professor encourage students to complete their problem sets on their own in undergraduate classes. I'm not saying that every student cheats off of other students; rather, I'm saying that some, if not most, students free ride and copy the solutions from their peers (or from the Internet). In addition from my experience, I feel as if this problem is more pervasive among the non-science majors/students (at least science majors are given assignments; the number and quality of them and the level of studens' interest to get on with them are spectate issues). I've even heard a professor remark: "since I know most of the uninterested students in the class are going to simply copy off solutions, I won't be giving assignments; the serious students amongst you (who'll go to graduate school) can do assignments over there." Frankly, I was appalled upon hearing this statement.

I come from a college/place where the local cultural norms are such that students don't like to sit down and devote week in and week out on problem sets, and the professors (for the most part) don't make a serious attempt to give problem sets that really consume a student's week or so. I'm sure the professor who'll dare to give a problem set every 3 lectures (as is the norm in most U.S colleges) will be frowned upon by most students.

  Given such a context, I am interested to know how can professors, in the larger scheme of things, encourage their students to independently solve problem sets on their own? Also, are there any good strategies that professors can use to make problem sets which the students would eagerly wait to solve week in and week out. I know one can only change the mind set of students from the ground up. But how can professors teaching at the tertiary level cope with such (deeply rooted) problems?

Thanks.

A few (by no means exhaustive) suggestions:

Use extended-response or open-answer style questions. What such a question would look like is completely field-specific, but it's definitely doable in every field (yes, even the technical ones). In theory at least, this makes it harder for several students to copy off of another student without commiting actual plagiarism.
Avoid assigning problems directly from a textbook. This requires more effort on your end, but it prevents students from being able to just copy out of a solution manual.
Make the students propose the problems. Similar to my first suggestion -- if the problem is that students are uninterested, give them the chance to do something that is interesting for them. Obviously you need to put bounds on this, but even within the confines of a single problem set this is doable. For example, in a course on Data Structures in CS, you could ask something akin to "write a simple program that uses data structure X and methods A, B, and C." What they do is up to them, but you still test their comprehension.
Use a flipped classroom model. This is probably the most involved suggestion, but if done properly it means the students are working on homework right in front of you. Makes it a lot harder to just copy answers when the instructor is walking around the room.


Should you include uncited papers in your CV? Is it convenient to include in your CV papers that have not been cited at all along several years?

Convenient? No.  Appropriate?  Yes.

Unless you are at a point in your career where you can release an impressive "selected publications" CV, your CV is expected to contain everything that you have ever published.  That includes publications that nobody has cited and even ones that you are embarrassed by in retrospect.  I've certainly got some of those in my CV (we were all grad students once), and I simply trust that they will be drowned out by all of the good work that has been done since.


How to stay motivated during the final year of the PhD program? I used to be an extremely motivated and a goal-oriented person. But it's been three years that I go through long periods of unproductively, usually followed by a short period of productivity. It's my last year in the PhD program. I taught a class last quarter and worked almost everyday for hours. I overdid it. Now, I don't feel motivated at all. I have to write my dissertation. I promised my advisor to submit the first chapter at the end of this month but I haven't started writing yet (I have done the research). Do others experience this? What strategies do you use to stay focused? I already took a long break (20 days), and have traveled to my home country thinking it would motivate me to work. The good news is I don't feel super anxious anymore but I am very worried since I haven't been able to focus. There are no distractions here and that's why I moved back. Any advice?

Thanks!

The mistake that people make when "unmotivated" is to "take breaks." Of course, you need breaks from time to time, but doing nothing while hoping to later to be able to do something is a recipe for disaster. The best ways to stay motivated, at the end of a PhD program, or otherwise, has XXX keys:

Establish a system for accomplishing tasks.
Set your work calendar and stick to it.
Have a plan for when you are unmotivated, and use it.
Ward off distractions.

Establish a System

There are many programs for accomplishing tasks, and most involve creating a task list and checking off those tasks. Popular ones that I like included the Pomodoro Technique and the Getting Things Done methodology. Regardless which method you choose, follow it. This not only helps you complete your tasks on time, it also prevents you missing your graduation because of a failure to file the 1000 forms that all universities seem to require in your final year.

Stick to a Work Calendar

This is easier if you are teaching, but make sure that you have work days and 'off' days (usually weekends). It is important to work on the work days, but it is just as important to take off days off. If you don't all of your days blur together, and it becomes even harder to get 'up' for the work days. On every work day, you must do some work.

Have a plan for unmotivation

Everyone has days that they just aren't ready to go, so plan for that. For me, I go through old articles and re-read them, update my notes on things relevant to my research, or refine my programing. That usually gets me out of a funk, and I sometimes get good ideas from it. You should always have a 'backstop' for these tasks, too, so they don't become your primary objective, which leads to...

Ward off distractions

Everyone fights distractions, but the two that are killers at this point are: new project ideas and ankle biters. It seems like everyone who is working on a Dissertation suddenly has 1 billion ideas at the end for what to do next. The temptation is to stop working on the dissertation and start on a new project, because it is all shiny and new. Instead, write it down in a notebook of file you keep for that purpose and accept that you will come back to it when you have more time. If you always keep such a notebook, you will never run out of research ideas.

Ankle-biters can take over any life, mostly because they are necessary. Most important is that you you prioritize your work first. Be aware of the deadlines, and don't do any of them until you are done with your actual work, or until they are due. Your research is your job; filling our paperwork isn't. If you treat it that way, you will better be able to stay motivated.


I am interested in retracting my old journal articles. Would it have any negative effects on my academic career? I managed to successfully publish my old bachelor thesis in a good quality national journal in my country. However, I am thinking of retracting the article due to certain circumstances. First, I felt really embarrassed by the low quality research methodology used in my bachelor thesis. I only used simple correlation in my research. After it was published, I realized that the journal editor team forgot to include a reference in that article because they were rushing me throughout the editing process. I informed them about their mistake and it seems that they have done nothing to fix the problem. I became a bit annoyed because the editor team has never made this problem in the past.

I felt that it would be better for me to simply ask for retraction to solve this issue, but I am a bit afraid of negative consequences in the future. Is it okay to do this? I am really interested of entering the academic world in the future.

The way to "retract" old work is to publish better work that references the old work and its errors. There should be nothing embarrassing about having found earlier errors and correcting them.

You have grown in the interim. Every active academic will likely have such an experience at least once in their career. The earliest work was done when you were, relative to now, somewhat inexperienced.

It is unlikely that they will retract the article for the reasons you give, but it is also possible that someone else will publish a better work based on your article. Your best course, I believe, is to publish it yourself.


How to cite a statement that cites several other sources? The below is in a paper I am reading, written by Gareis.

  One of the uppermost complaints of study-abroad students remains the lack of
  meaningful contact with host nationals (e.g., Gareis, 1995; Klineberg & Hull, 1979;
  Marginson, Nyland, Sawir, & Forbes-Mewett, 2010; Ward & Masgoret, 2004;
  Yashima, Zenuk-Nishide, & Shimizu, 2004).

Can I site this in my own paper as:

  Many international students complain about a lack of meaningful contact with host nationals (Gareis, 2010).

One approach is to cite Gareis (2010) as the source of the other citations:

  According to Gareis (2010), many international students complain about a lack of meaningful contact with host nationals (cited by Gareis, 2010: Gareis, 1995; Klineberg & Hull, 1979; Marginson, Nyland, Sawir, & Forbes-Mewett, 2010; Ward & Masgoret, 2004; Yashima, Zenuk-Nishide, & Shimizu, 2004).

If you use this approach, then you need to include ALL these in your References list (a.k.a. Bibliography).  In this case it would be 6 references total.

This approach is most useful if these specific sources are important for your purposes, either because they establish credibility, present details, or make important connections to lines of research or results.

Another approach is to omit the specific citations by Gareis (2010), but also to note that you omitted them.

  According to Gareis (2010), many international students complain about a lack of meaningful contact with host nationals (five citations in Gareis, 2010 omitted).

This approach is most useful when you only need the main citation as support of the statement and the specific citations are not useful or necessary for your paper or for the reader. In this approach, you'd only have one entry in your reference list for Gareis (2010).


How to determine peer institutions? Are there standard criteria to determine the peer institutions?

My institution is an american private liberal art university that follows the semester system, for which I can think of the following criteria:

Liberal art university
Private university
Semester-based university
Endowment of the university
Number of faculty in the department
Number of graduates with BS every 3 years say
Number of graduates with MS every 3 years say

Will that be OK? anything else?

The Carnegie Foundation gives 6 types of criteria:

Undergraduate instructional program
Graduate instructional program
Enrollment profile
Undergraduate profile
Size and setting
Basic classification

There are many factors involved--for instance, geographic region and percent of full time students are factors in 5 and 4.  I don't think semester versus quarter system is too important.  See the link for descriptions of these criteria.

There also seem to be a couple of Chronicle articles about selecting peer institutions:

http://chronicle.com/article/in-selecting-peers/134228/

http://chronicle.com/article/Who-Does-Your-College-Think/134222/

however I can't access the Chronicle website right now, but did find this other article which discusses the first Chronicle article linked:

http://theairspace.net/commentary/u-s-colleges-name-their-own-peer-institutions-rank-themselves/


I need an efficient way to catch up with all the work done in my field of interest I have an academic problem that I'm very interested in and want to explore the related research fields. Of course no researcher knows everything going on in a field but I feel I know far too less to go for a PhD right now. I'm in the last year of my undergraduate program right now.

What I did so far is...

Read a lot of papers. They build on a large corpus of knowledge so before understanding the theoretical details I have to read all those somewhat related publications.
Read advances papers for better understanding. This works quite well.
Organize links to all interesting publications and other material in a document. Not sure if it's really useful though. I haven't had time to read things from there I didn't remember anyway yet.
Start implementing the ideas and algorithms as computer programs. Doing so is good to validate my understanding but also takes a lot of time and it would be good to get some help when I'm stuck.
Join mailing lists and groups and talk to researchers. It's more networking than information.
Take somewhat related classes at other universities since there is not much at mine. However, there are no whole courses on the problem I'm interested in since it's too specific.

This all is a lot of fun. It also obviously takes a considerable amount of time. Do you have any advice to more efficiently organize and catch up with the current state of my academic field of interest?

the following points are based on my experience, on how to start learning about a research topic from scratch:

Common Knowledge: First thing you do is to learn the common knowledge. This is the basic that makes sense of the whole field and logically true. For this, you can read general available resources, such as books or Wikipedia. For example, if I want to start to do a research on operating systems in a distributed setting, I go and get a book about Linux, and a general book about distributed computing. Then moving on to computer cluster for example or something else, I see what my interests and curiosity takes me.

Note on 1: Don't think you are not reading research so you are not progressing. Common knowledge now was a research topic of the past, and you must learn them pretty well.
Earliest Resources(s) You Can Find: This might take a little time, but you need to find the first resources to the field. You should see how and for what this field is started.
Important Papers of the Last 20 Years: Find the 'top 20' papers of the last 20 years. See what they cited and what they contributed.

Note on 3: The last step will definitely take you for a ride for some time. And this is the whole point. You need to learn how to read and write research in a field during a Ph.D. and therefore this step is very important.
Day to Day Updates: You can join different mailing lists of different research topics, and also you can use online services, that let you know automatically via email, based on your specified keyword(s).

Conclusion: Learning the research topic and its history takes time; however it is essential to make you a good researcher who can contribute in the field. These things can be achieved by the following mentioned points.


Continue applications after accepting a position There are various questions (and excellent answers) here about what to do when one accepts a job regarding existing applications. The general consensus is "withdraw existing applications".

I write with a variation on this that I have not seen addressed here.

If someone accepts a soft-money research position at one institution, and that position will start in 1.5 or 2 years, must they still withdraw and cease applying to other institutions?

Some context: The current role is post-doc. The goal is TT. The soft-money research position is a good step and starts when the post-doc ends.

It seems strange the candidate is effectively removed from the job market for ~2 years (1.5 until position starts, and one assumes it is bad form to apply for other jobs immediately in a new position), even though the next position is not committing to salary. It seems like other TT applications that are pending, or new ones that might be submitted in the next 1.5 years, could lead to the desired TT job, in which case the soft-money position would not be taken.

Is this approach unethical?

Edit

Soft money is a common term in my field. It means the institution provides no fixed long-term salary support. You are responsible for your salary by grant-writing.

Edit 2

Several questions about why the 1.5 year delay. This is part of dual career hire. One got TT, one got soft-money after post-doc ends.

In my experience, setting up academic jobs more than one academic year in advance is uncommon precisely for this reason: each party gets nervous that the other will back out.  Thus for instance it is relatively common that one wants to accept one position and "finish out" a current position, and in my experience it is quite often acceptable to stay for one additional academic year and very rarely acceptable to stay longer than that.

I would be interested to hear more about the circumstances in which a position gets offered and accepted 1.5 to 2 years in advance.  As for the ethics: formally accepting an academic position involves (i) announcing your intention to do so and (ii) signing something saying that you accept the job, with a certain start date.  I do know that some positions which are funded by external grants need to be accepted conditionally on final funding of those grants (I was quite recently involved in such a situation).  This is potentially awkward, as the risks involved in a conditional offer not coming to fruition are highly asymmetrical: for the employer it means that some people's time has been wasted and that certain proposed projects will not get carried out; for the employee it means that a highly trained, valued worker is out of a job for a year through no fault of their own.  It may be that one has the ethical right to turn down a conditional offer for an unconditional offer under certain circumstances; I don't think you should use this an excuse, but if you honestly have doubts that the offer will become actual, then I think at some point you are entitled to take a real job rather than a virtual one.  (I would be interested to hear more about this point from others.)

If you are really signing on a dotted line a commitment to a position far in the future, conditional on funding, and with an uncertain salary...well, it is not clear to me why one would sign such a contract.  Barring exceptional circumstances you probably shouldn't.

I feel like the standard unit of "going through with the position you accepted" is one academic year.  In other words, if you agree in writing to take a position, then ethically speaking you should keep it for at least one year (I think).  Most formal contracts I am familiar with are academic year to academic year anyway: I am a tenured faculty member and I still sign a contract every August.  In my department we have the understanding that a postdoc, for instance, should feel to vacate the position at the end of any given academic year if they get a better job: in fact, these usually count as success stories, including on our part.  In general vacating a postdoc for a tenure-track job seems especially understandable.

All of the above makes me unsure of what the etiquette might be on a position that starts so far in the future.  As you can see, I am skeptical that such an arrangement should be as ethically binding as a standard offer, but it depends on the understanding both parties had when entering the arrangement.

Added: The additional information seems helpful.  Is the current postdoc at the same institution as the partner's tenure-track job and the future "soft-money" gig?  I gather not.  Anyway, in this case the "soft-money" job sounds more like a courtesy to the tenure track partner than anything else.  Have you signed any paperwork saying that you intend to take the job?  If not, I think you're totally fine not to end up taking it (however if your partner plans to stay this should be done carefully so as not to cause trouble for him/her) and they probably will not even be that broken up about it.  Probably you haven't signed a contract for something so far in the future, right?  If you did sign a form signifying your intent to work at a certain job, it seems to me that you need to ask if you can not take the job rather than tell.  But it's hard to imagine the circumstances in which they would hold you to a future job that you no longer want.


Finding a professor beforehand I want to know your opinion about the following situation.

Having read all recommendations on how to apply to graduate school abroad, how to choose the professor to work with, I found a really interesting suggestion of someone. The person was describing the similar process applying to graduate school and in parallel he was looking for someone to work with in the same university, a bit early but if know what do you want to do, why not to do it. Having found a good candidate to work with, the person offered to work together for from few weeks to few months.

This person was lucky, he made a really good choice, they decided to proceed working together towards a masters degree and application to the university was a useless formality.

One minor point though, it was a quite expensive, to buy a fly ticket, rent a room etc.

What is your opinion about this form of finding a professor, do you have more examples like this?

Well, if you want to find a good professor to work with, you could search for the available professors in a certain university (online, in their website).

After having all the names, you could "stalk" them online, find some of their papers, etc. Most of them (if not all) will have a webpage in which they post lots of information about themselves, such as, their papers, students they worked with, even their hobbies. You'll probably delete quite a few names that way.

You'll still have some professors names not crossed out. You can then try to e-mail the students they worked with and ask them what's their evaluation of said professor.

Not sure if this is what you're looking for, sorry if it's not.


Pure mathemathics: authors appearing in alphabetic order So the title of the question is quite broad, I've seen a few of questions in the site regarding this particular topic (quite a few actually, so let me know if this is somehow a duplicate).
My problem is the following, I am working on my PhD thesis, and so far me and my supervisor have collaborated in a few articles (that somehow constitute the body of my thesis). Right now I am working on a particular article (on which I've made all the work). The fact is that my supervisor, and apparently all the members of my faculty tend to put authors in alphabetic order. The fact is that my last-name starts with a "T" so by using their logic I will almost surely  end-up being the second\third author.
I don't feel this is actually fair, since after some search online I've seen that in general the order of the authors reflects somehow how much work was done by each one. So it seems strange for me to be like "coauthoring" my own PhD thesis.
What should I do? I don't want to appear pretentious, or rude in front of my supervisor, but I don't think it's fair for me either.
Do you have some advice on what to do?
In case it's relevant my field of research is pure math.

The convention in pure math is to list authors in alphabetical order.
Since this is generally known inside pure math, readers will not draw any conclusions from the author order about the relative importance of contributions. In fact, my impression is that most pure mathematicians prefer to avoid discussion of relative importance of contributions altogether, with the exception of occassionally giving more credit to their coauthors in slightly informal settings.
[As a side note, Author contribution statements seem to be unfeasible for widespread use in math. While there are collaborations where X proved Theorem 1 and Y proved Theorem 2, it is in my experience far more common that X and Y talked repeatedly over a long period of time, and at some point the proofs materialized.]
Admittedly, being listed first will mean being noticed a little bit more. However, in line with the convention about author order, the "X et al"-style is typically avoided. It seems far more common to refer to unwieldly large groups of authors by initials (eg GKSSW proved that...).
The place where your advisor is supposed to express how overwhelming your contributions were is in your letters of recommendation.
That said, in pure math it is also convention that merely advising a student does not establish authorship. It is even a common sentiment that advisors should be very reluctant in appearing as a coauthor on an advisor/student paper.


Citing a link that was removed? I run a small blog about both the academic and professional aspects of my industry as I both teach a course at the university I am attending as well as work in the industry full time. The blog answers viewer questions and has even made some changes to core industry values which has boosted productivity and efficiency in some schools, and jobs.

One of my posts answered a question that required extensive research and would be unbelievable without my sources. This post is almost a year old and the link that was most important to my reasoning and proof of concept is not longer active.

I am faced with two choices:

Remove the post all together because most of the credibility was in that link.
Leave the post up without the proper accreditation to my research.

This is one of my most popular posts that effects both the academic and professional aspects of my industry and I have no way of contacting the original owner of the website that was removed.

If the page was up for a while, you can probably obtain a copy via the Internet Archive.  Once you've got that cached version, you can host it yourself, with appropriate attribution (i.e., the fact that the original source is missing, its original location and authorship, time that the snapshot was taken by the Internet Archive, etc.)

This could be a problem from a copyright perspective, but if the original material truly is abandoned, then you've got nothing to worry about.  If the owner does contact you, then either they'll likely be willing to post a copy (or its equivalent) again, obviating your need to host your own copy.  Only in the rather unlikely case they both want the material taken down and are unwilling to repost it themselves will you lose the source.


Fraudulent credentials Someone I know is apparently claiming to have obtained PhD when I know for a fact that he did not.  He is working in a biomedical company and having himself presented as Dr.  Is there a way to have this checked out?

Sure, just contact the registrar's office of the University from which he claims to have graduated.


choosing workshops/conferences to attend and publish research I have been able to attend a few different conferences and workshops during my limited time being a masters and PhD student. Some to present my research and some just to watch presentations.

I have have found my experiences throughout the various conferences/workshops vary quite a bit. I am not referring to the organization of the conference in particular (lunch, venue, extra events) but rather the experience itself. For example, the audience varies greatly in size and age with some having large and mixed audiences and some having smaller and older audiences. Some conferences seem to cover a wide range of topics and some cover more specific subject matters. Also, the quality of talks seems to vary greatly.

Having been to a few of these now it has made me reconsider the benefits/usefulness of attending these events. Originally I had thought it was beneficial to attend as many conferences as possible to learn from presentations and network with other researchers. But after having attended a few conferences which have had limited talks which relate to my research, I've found I often end up being jetlagged in another country not being able to do research and just kind of wasting time.

Because of this, I have been considering whether it is better to just try and choose one or two conferences per year which have a younger audience and seem to be moving in the right direction and focus on trying to publish at those yearly. By doing this I can see getting more benefit from attending the conference and also have an academic community to grow with over time.

What are your experiences with getting the most out of conferences, do you attend as many as you can or limit it to specific ones which relate to your research? How do you decide which conferences are worth your time and aren't just looking for registration fees? My particular area is computer science/engineering.

What one gets from attending conferences depends a lot on some personal factors, especially for junior researchers: some people socialize easily and can build fruitful professional relationships, some people are well organized and able to continue their regular work on their laptop while attending talks, some people are interested in almost every talk whether it's close to their research area or not, etc.

Personally I'm not very good at any of these things :) This is why I don't try to maximize the conferences I attend. I try to attend a couple every year, most of the time when I present something. So I choose conferences primarily as a venue for the topic/level of my paper.

To me conferences are a good way to get a general overview of what the field has been up to, finding what are the interesting new directions and the odd clever approach. Poster session are usually a good way to discuss things in more detail and ask about things which are a bit far from my own research area. I often find many interesting things to study later at conferences... and usually I don't have enough time to actually study them later ;) But overall it's really useful in order to see where my work stands in the context of the community.


What is the IEEE citation style for content obtained from wikipedia? I have added a paragraph from wikipedia in my thesis. Now I need to add reference to that wikipedia page. What is the IEEE formatting and citation style for that? Currently I use as below.

In chapter of thesis added copied content from wikipedia as below

  The waterfall development model originates in the manufacturing and construction
  industries; highly structured physical environments in which after-the-fact changes are
  prohibitively costly, if not impossible. Since no formal software development
  methodologies existed at the time, this hardware-oriented model was simply adapted
  for software development [1].

In References page

  [1] (2014, April 22). Waterfall Model [Online]. Available:
  http://en.wikipedia.org/wiki/Waterfall_model

For correct citation of Wikipedia, see Wikipedia's guide to citing Wikipedia.  Since you are using IEEE styles, you should probably be using BibTeX to manage your citation, in which case you can directly use the BibTeX formatting template provided.


'Scholarly' alternatives to Goodreads As you can read on Wikipedia,

  Goodreads is an Amazon company and "social cataloging" website founded
  in December 2006 and launched in January 2007 by Otis Chandler, a
  software engineer and entrepreneur, and Elizabeth Chandler. The
  website allows individuals to freely search Goodreads' extensive
  user-populated database of books, annotations, and reviews. Users can
  sign up and register books to generate library catalogs and reading
  lists. [...] On the Goodreads website, users can add books to their
  personal bookshelves, rate and review books, see what their friends
  are reading, participate in discussion boards and groups on a variety
  of topics, and get suggestions for future reading choices based on
  their reviews of previously read books.

My question is:

  Is there a scholarly alternative to Goodreads, that is, a website
  where you can shelf papers, journal articles, scholarly websites, and
  preprints as well as books?

There indeed is plenty of web sites where you can shelf articles, preprints, etc. (Mendeley, Zotero, CiteULike, and so on; a fairly comprehensive list is available on Wikipedia) but if you also would like to have the possibility of adding reviews like in GoodReads, the things are somewhat different.

One site that I know of that allows you to do this, in addition to merely bookmarking the items, is ResearchGate with its Open Review feature, but you can only bookmark and review items that already are in their database (you can add the articles that you (co-)authored but I doubt that reviewing them is your intention). Perhaps there are some other sites with a similar functionality: e.g. according to Wikipedia CiteULike has it too; on Mendeley you can share articles' annotations within private groups.

Also, there is a number of sites allowing you to bookmark and review arXiv preprints (e.g. SciRate) but not the other kinds of items like the books.


PhD programs: select a very specific one in order to narrow down my area of interest? or a more general one and specialise as a postdoc? I have perhaps a common doubt, a common conundrum. I'm an MS graduate, and my goal is to become a researcher in a very specific area in biotechnology, which is a branch of neurotechnology.

I'm currently looking for a PhD degree, and by searching through programs at different institutions, I have found that the field that I want to work in is in fact quite new, so not many institutions are currently doing research in it. This leaves me with only very well known institutions like Caltech, Yale, and Johns Hopkins that are working in my field of interest.

I do not consider myself especially above average but I'm a very self-driven person. Even so, I know it will be hard get a scholarship to study in one of these very well known institutions.

So my question is, what is most advisable?

To spend one or two years studying in order to get the scholarship (and I might not get it), and focus my research into this one narrow specialism early on;
or, to enter a less demanding program, less expensive, still focussed on biotechnology, but not at all that narrow, perhaps in the Netherlands or Switzerland, and specialise later in my career.

I'm not entirely sure what you mean by spending 1-2 years studying for a scholarship, but you must formally stay in academia. Your MS was your 1-2 years of prep for a Ph.D.

My suggestions would be as follows:

1) Apply to your ideal top-tier universities (Cal-tech, Yale, etc...). Spend a considerable amount of time on your application. Especially your statement of purpose since you do indeed have a clear goal to go there. Do well on your GRE. If not you will get filtered out before they really evaluate the rest of your application. I know they changed it since I took it but when I did it was a completely beatable test (at least the quantitative section). Practice. Practice. Practice.

2) Apply to the universities/labs that actively or recently collaborated with the labs you ultimately want to work with. Probably more than half the post docs in our lab came from collaborators (or competitors) labs.

3) Apply to your "fall-back" universities. You'll want to at least stay active in the field.

4) Do you best to attend conferences that your top-tiers will be at. Make contacts, friends, collaborations, etc...with members of the group you want to be with. As a Ph.D. student we ended up evaluating many of the Post-docs that applied to our lab. Know that what you mention to these members in passing will often come up during your evaluation. Be aware and make this an advantage.

Realize that you are probably a poor judge of your own talent (good or bad). Don't let the reason you didn't make it be that you didn't try.


Is taking a method explanation from books and papers considered plagiarism? I have been reading a few Q/A about plagiarism, but I still have a doubt about the use of books and papers to explain the method I am applying in my thesis.

I mixed up the infos I found in a book and in a paper to explain the method (because some parts where better explained in the book and some others in the paper), of course I cited them at the beginning and I put them in the bibliography. Is this considered plagiarism since I am not using "my words" to explain it?

EDIT to be clearer: I am not doing copying and paste: I am following the same flow of ideas to present the method, some parts where omitted in the paper, therefore I had to rely on the book to take care of every aspect

And at the beginning I wrote:"the method is fully explained here [1][2] and it is here reported for completeness

If you are using somebody else's words, you need to make this fact clear and explicit via quotation/block quotation; to do otherwise is clearly plagiarism, even if you are splicing together multiple different sources into some sort of Frankenparagraph.

If you are making a complex remix of two sources, proper quotation may feel very choppy and incoherent, however, so you are probably better off paraphrasing into your own words instead.