text:
How can a PhD student enlarge his academic collaboration network?
I am a new doctoral candidate of information and computer science and about to initiate my research, and typically collaborate with my supervisor and other group members. But seldom will a researcher limit his collaborators to those within the department he's in; he has to enlarge his network. I believe energetically participating in academic activities/events surely brings benefit. As a student, my quick thoughts are, for example, applying for internships at some research institutes, summoning team members for contests, or taking part in open source projects. Can you kindly share other experiences?

should this be Community Wiki?

Related questions : http://academia.stackexchange.com/questions/271/how-to-achieve-successful-collaborations , http://academia.stackexchange.com/questions/3029/what-skills-are-needed-to-sustain-a-research-group, http://academia.stackexchange.com/questions/2707/how-should-a-phd-student-approach-a-collaboration , http://academia.stackexchange.com/questions/2570/making-time-to-catch-up-with-people-at-a-conference

Happy Hours. Lots of Happy Hours.

No, personally I don't see any reason why this should be CW.  Why do you think it should be?  Actually, better yet, don't answer that question.  Rather than discussing here whether it should be CW -- if you think this should be CW, I suggest you create a thread on meta, carry on all discussion there, and here just post a link to the CW thread.

Of course, you’ll get there by engaging in a lot of activities where you will meet new people and work with people who will learn to know you. I recommend choosing them according to a few criteria:

Activities of a seemingly technical (or practical) nature. As a PhD student, you probably don't want to be on boring committees, board-style meetings, interdepartmental seminars. You will meet people, but not in a way that fosters collaboration. (However, you may want to attend these events for other purposes. Meeting key people involved in hiring decisions at a given institution is one such purpose that comes to mind.)
Informal settings. This favors meeting new people and getting to know them much better. Favor small meetings over big ones. Aim for a few persons you want to meet. Identify people you would like to approach (at a big event), then check what events they attend.
Manage to invite people for talks at your institution. Okay, this one might be a bit difficult for a PhD student in some places, but if you can manage to get someone invited for a day or two, get him to give a talk and discuss your research and his, it will be worth it.
Do not shy away from “learning” events: tutorials, “hands-on with XXX library” type of things.

All in all, I think the kind of events you want to engage in are:

Open source projects: you listed that one already
Workshops close to your research topic: these typically involve few people and long discussions. Many of my strongest collaborations (and a few friendships) grew out of workshops.
Tutorials organized on topics related, but not too close, to your research: you will learn stuff, meet people in a relaxed setting. Don't be shy of going to workshops where you already know some of the stuff, if only to put it in practice and discuss with the best experts. Also, be ready to present your own work and identify convergences with lecturers and other participants.

You might consider engaging with scholars whose interests overlap yours via digital arenas as well. Although the degree to which people in a given field varies by specialty, I'd be surprised if there aren't at least a few people in your niche of information and CS who use informal digital spaces to share work in progress, ask each other questions, and communicate about opportunities such as conferences and grants. For example, you might explore:

Blogging and commenting on others' blogs: Start writing short, regular posts about academic questions on your mind or scholarly endeavors on which you've been working. Do short reviews of interesting books and articles you've been reading, or use the space to be thoughtful about what it means to be a Ph.D. student in your field. Leave meaningful comments and questions on the blogs of others in your field, or respond to these posts with a blog post of your own (linking to the other person's post both as a matter of etiquette and because many bloggers automatically get trackback notifications of ho's been linking to their posts).
Using Twitter as a Scholar: Twitter isn't just for sharing photos of what you ate for lunch! Ryan Cordell provides some excellent advice on getting started using Twitter professionally and effectively. Use Twitter to share the links to those blog posts you've been writing (see previous bullet), cite intriguing articles you've been reading on the web, or ask questions of scholars whose work you admire. If your department doesn't have anyone already using Twitter for academic ends, you might try searching Twitter with some applicable hashtags (e.g. #computers? #infosci? some more specific terms?), following anyone who tweets about these topics and seems to be saying interesting things, and also check out who those people are themselves following. Many people use the Twitter setting that automatically notifies them when they have a new follower, so be sure to fill out your Twitter bio to create the professional impression you desire (e.g. what school are you at? what topics do you study?). Finally, consider asking interesting questions via Twitter and curating the responses via a service like Storify.

I am a biochem post-doc and just tried projectnudge.com for this exact situation.  The site appears to be beta testing social science collaborations.  I was told my posting will appear on the site soon when they start releasing the science collaboration proposals.

In the humanities, at least, websites like academia.edu are useful for following research trends and for connecting (and "following") the work of others. I've found it especially useful both for meeting folks with similar interests, and, when I've presented in or organized panels at conferences, for putting a face to someone's name while also seeing what else they get into.


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Efficient process for writing a STEM journal article
Background:
I have done quite a lot of research work for a particular project.
I am working in the field of operations research (i.e. applied math/physics),
so this work primarily takes the form of propositions, proofs and numerical experiments.
In the process of my research,
each day I write up my daily progress in my lab notebook,
which in my case takes the form of a very very long LaTeX file.
I am now trying to write up my work as an article for submission to a journal.
Question:
What is an efficient process which I can use to write the journal article?
Related links:

The Mumford method sounds interesting.
However, as Mumford is a philosopher,
his writing process seems to me to be less relevant to writing in the sciences.

I think the process of writing papers is pretty individual to each researcher. What works for me may not work for you. That being said, the following are a few rules that I usually give me mentees and students when we start writing a paper together:

As "Not Quite An Outsider" states, do start with an outline. Look through related work for papers with a similar scope / methodology / idea and start by imitating their outline. However, do not do so blindly. Instead, focus on understanding why the authors of your related work chose to structure their paper the way they did, and check whether their (assumed) reasoning is also useful for your paper.
Keep in mind that your paper needs a "story" - you know your material and reasoning, your readers do not. Start at the beginning, and end with the conclusions. Avoid statements that are not understandable at the point in the paper where they appear (rule of thumb: when you feel writing something along the lines of "as will be explained later on", you likely have a bug in your structure).
Plan the length of your paper. Fill each section with some Lorem Ipsum filler text of roughly the same length as you plan for this section. This allows you to see how much space you actually have for each part of your paper. During writing, when I start a new section I remove the filler text and replace it with what I actually plan to say at this point. I sometimes even go as far as drafting where in the paper I will have which figures, and put placeholder figures there instead when doing the outline.
Write the paper in order (i.e., in the same order as it will appear in the final paper). This is a bit controversial - I have seen many experienced paper writers suggest various other orders ("Start with Related Work" - "Start with Conclusions" - etc.). To me, the problem with writing in a different sequence is that it is very easy to lose track of what a reader actually knows at this point in the paper (hence destroying the story of your paper). For instance, you would end up using concepts and ideas that you actually only discuss at a later point. This makes papers unnecessary difficult to understand. I feel it is also much easier to produce a convincing line of argumentation when you produce the material in the same order as it will be read.
In any way, later rearrangements will be necessary. After reading the paper, you decide that you need to switch some subsections around, or that you do not need Section 3 at all. Stay flexible and don't be too much in love with your current outline just because it is how you initially wanted to do it. One additional sidenote in this is that you write your paper in LaTeX. This makes later changes in the outline trivial.
Write the text the way you suppose it should appear in the paper. Do not draft too much - there is no point writing throwaway text unless you really do not know how to write this section / part properly at this point. Only go on to the next section when the last one is pretty much done.
As soon as a section is pretty much done, get some feedback on it. Remember that your paper should already be coherent and complete up to this section, so there is no harm in sending it to colleagues or your supervisor and asking them to tell you whether the paper makes sense up to and including Section X.

+1 for "What works for me may not work for you." This method of writing a paper does not work for me at all, especially the advice about mostly finishing one section before working on the next. Crafting a paper is a dynamic process, and each section will require many revisits (and usually several rewrites!) before I am satisfied that it is as good as it can be.

I should think an annotated outline (indented list of titles) would be effective.  Do a basic outline of the article with however many titles, and under each title put one or more of:

link(s) to the text to use from your journal
a short phrase to use in conveying the point of the titled section
an idea of how much (word, line or paragraph count) to use to fill this out.
links to other outline titles.

Once the structure looks good (or even make a few structures to pick from), go back over
and fill in the body under each title.  The annotations will help you keep track of
certain goals (word length, number of ideas, enough persuasive sentences, logical
coherence), and it is easier to manage a high-level version of the article this way.
It also makes editing easier if you prioritize which titles to cut.

If you are concerned about stylistic issues, again start with rendering existing articles into outline form, and then make your outline similar.  Other advice such as style and idiom are useful, but poor structure is less forgiveable (in my opinion) than poor use of style or idiom.

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text:
Is a postdoctoral scholar expected to work during the summer?
I am considering applying for postdoctoral positions in the US.
However, I would like to find more information about
how it is like to be a postdoctoral scholar.
Question 1:
Is a postdoctoral position a full-year position (12 months)
or an academic-year position (9 months)?
Question 2:
How should I interpret postdoctoral salaries?
For example, an MIT postdoctoral information page (see link)
lists the minimum postdoctoral salary
for a person with 0 years of experience at $42,000.
Is this salary for 12 months, or for 9 months?

Each specific job posting should make this clear. My guess (based on a very few examples) is that 12 months is more common. In some cases you may see the summer salary quoted separately.

I added the "US" tag, because I have the impression that this 'no work during summer' is mostly an American thing. I hope I did nothing wrong, feel free to revert it in case.

@FedericoPoloni Thanks. I have also edited my question to make it explicit that this question applies to postdoctoral positions in the US.

In general, postdoctoral positions—unlike faculty positions (in the US)—are considered to be 12-month positions, with the salaries determined accordingly. You are not normally expected to provide your own funding for the summer months, nor are you expected to find outside employment.
If this is not the case, then it should be explicitly mentioned in the advertisement for the position. However, this is so rarely encountered that it would be very much outside the norm for postdocs.

If this answer is specific to a given geographical area it would be good to make it explicit.

Actually, it's not really location-dependent. As far as I can tell, postdocs are employed on a 12-month basis everywhere.

The claim that postdocs being on a 12-month basis is "unlike faculty positions" is location-dependent.

Post-docs come under staff category not faculty, so it's always 12 months. More than 50% places expect you even too work in weekends.

This isn't always true.  When I was a postdoc, I was considered faculty, with the courtesy title of "Visiting Assistant Professor".  I had a 9 month appointment with 2 months of summer salary from a separate source (so effectively like 12 months but slightly different).  And "50% of places expect you to work weekends": This sounds like a made-up statistic.  Citation needed.

Postdocs at my institution are classified as "faculty" as well.

Also in my department, postdocs are faculty.

@NateEldredge Were you expected to teach classes?

@superbest: Yes. This is normal for postdocs in my field/country (mathematics/US).

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text:
Is there an efficient way to give a large class of students feedback about their assignments?
I am the course lecturer of a large undergraduate course
with about 700 students in the course.
One of the challenges of teaching such a large course
is grading the assignments and giving students feedback.
Here is some information about the grading process:

The students submit their assignments electronically,
using a learning management system
The graders grade the assignment by filling in a spread

I would like to give the students two types of feedback:

Students would receive their scores for each question part,
e.g., 1A: 10/10, 1B: 5/5, 1C: 2/5, etc.
For each question part where marks were lost,
students would receive some comments about why they lost marks,
e.g., wrong units in 1B, did not round to an integer in 2A, etc.

Is there an efficient way to give a large class of students
such feedback about their assignments?
I considered asking the TA to email each student
their score for each question part and the mistakes that they made.
However, this seemed to me to be very time consuming and impractical.
Response to questions in comments
Question:
How many students does each TA handle?
Is the group of a particular TA consistent throughout the course?
That is, does the TA handle the same students for the course?
Are the "graders" also the TAs?
Answer:
We have about 5 PhD students who take the role of graders,
i.e., their job is only to do grading.
We also have 1 TA who is a recently graduated BSc student,
whose job is primarily to do admin work,
although she also helps out with a little bit of grading.
Question:
What is the learning management system?
Do you know all of the available features on this system?
Answer:
We are using the Canvas learning management system.
It is possible to give comments for each student's assignment;
however, to the best of my knowledge,
this has to be done one assignment at a time,
which means that giving feedback this way would be fairly time-consuming.

How many students does each TA handle? Is the group of a particular TA consistent throughout the course? That is, does the TA handle the same students for the course? Are the "graders" also the TAs?

What is the learning management system? Do you know all of the available features on this system?

With such a large pool of students, why attempt individualized specific feedback? What is the goal you are trying to accomplish? That much data can easily point to specific concepts that are less understood which can lead to augmenting course content. Do you have any current feedback systems? Does this type of feedback exist in your institution from another class and/or department? Are there limits on you making an in-house database?

@Buffy See my edited question.

@KM- See my edited question.

@DavidS You raise a very good point that individualized feedback may not be necessary. Perhaps giving a one-page document explaining some common mistakes is sufficient...

In much smaller classes where I do all the grading, I keep a list of common error notes (one line each) and paste them into the LMS feedback boxes as appropriate.

Have you checked out Gradescope?

If the class has 700 students there should be a lot of students who are making the same mistakes. Therefore, I do not see much benefit in personalized feedback due to the impracticality of the context.
I would consider it wiser to determine what are the common mistakes that the majority of the students made and provide the same feedback to all students on how to address these common mistakes. This will help the majority of the students without having to commit to the time-intensive effort of personalization.
If there is someone who wants additional explanation they can speak with the TAs.

I built a “set” of six spreadsheets (one for each grader) and a master that would take the grades and comments.
Then, using a template in the master, create a “report” for each student - a vba code would then run through producing a report for each student.
Never did tie it to email to make that bit automatic...

+1 good suggestion!! I was about to suggest something similar. Couple of semesters ago I did something similar using a MS-Word "report" template with form-fields setup (see for example https://stackoverflow.com/a/11991591) and automated emails generated (https://stackoverflow.com/a/37302823)

I'm not familiar with Canvas, but can your graders add markup to documents easily (the electronic equivalent of the old red pen)? If you provide a set of solutions just marking the errors should make it obvious what most of them are, but a one or two word note can be useful, especially in short-form problems or ones with fairly limited and obvious right or wrong answers.
Expansive written comments are more important in long-form written work, since the marking criteria are often a lot fuzzier and it is, IMO, important to be clear about why you think someone has demonstrated only a "good understanding…" instead of a "very good understanding of XYZ" and so on, and because there are often fewer points in the total grade. That takes longer, but those assignments tend to take longer to mark anyway, so the burden isn't too large.
If the errors are mostly "stupid" errors like the ones you described, which don't show any real conceptual problems, just reminding the class in a lecture can be enough feedback.

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Impact of student suicide on PhD advisor’s tenure prospects
If a PhD student kills himself, how does that affect the advisor?  Does it count against him for tenure purposes?

To get the elephant out of the room first:
If you are contemplating suicide and wondering whether you will hurt the tenure case of your advisor by this, stop this thought right there and get counselling. The tenure case really is of no concern in this question. I am sure your advisor would also agree to this.
Now, assuming that this is a hypothetical question, or it concerns a suicide that already happened.
A suicide of a student will very likely not hurt a tenure case directly. No educated person in her/his right mind would react like "he killed this guy, he must be the worst teacher ever!" I would rather expect a wave of sympathy and compassion about the loss. Of course, whenever a student leaves (for whatever reason), the tenure case is indirectly hurt a little, simply because the advisor needs to start from ground up with a new student, who is likely not going to be very productive for some time.

I would like to add that suicide is treated as very serious problem in many PhD. programs, and departments are aware that these programs cause great deals of stress on the students.  It seems to happen more often in these programs then in other areas, it is not a stain on your record - mental health is a practical issue. If you communicate with your department that you are having trouble of this nature, they will attempt to work with you.
For example, some students may take a break from their program and continue later without ill consequence and the department's blessing.

I'd like to add:  If your student has died, that is a traumatic event and you probably also need conselling.

I'm quite sure that for most professors, their own tenure is about last in the things they care about in this situation. Professors are people too, they care about their students and how they do. In some sense, your students are your children too, as you see them grow up and spend a lot of time together. You're proud if they succeed, and you're sad if they struggle. If a student kills themselves, from the perspective of the adviser it's first and foremost a human tragedy. The impact on the tenure case is really something that's secondary (or tertiary, or even less important).

There is no obvious link between a student suicide and the supervisor's tenure. As you may know, even a breaking up with his/her boy-/girl-friend can lead to a suicide.
If you are planning to punish/revenge your bad-ass supervisor, there are more than 100 ways, but none of them would be a suicide. If he/her has ever abused/hurt you, just report to the committee, and you may find that someone even help you punish him/her.
If the tragedy has happened to your student, please first make sure not to blame on yourself too much -- unless you really helped a lot on the tragedy -- a suicide is also a decision of him/herself.

Suicidal behavior is not a normal response to a breakup.  It's associated with poor mental health, not external events.

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Is there an available network analysis of all academic papers and/or a 3D representation?
I know multiple paid or open databases are available online for a meta-analysis of academic articles, but I was wondering if there are any published papers or graphics on a network analysis of the available data, particularly in reference to time.
Ideally, what I’m looking for is a three-dimensional representation of correlation of all available research papers by word similarity, keyword, title similarity, etc. and with vertical axis as time of publication and which allowed relatively assessable identification of nodes, density, cluster, and relationship patterns.
If something like this exists, a link would be greatly appreciated. If not, any nudge in the right direction of meta-research on academia would also be greatly appreciated.

I seem to remember someone talking about this. That being said, I don't remember how to search for the thing.

Thanks; if you remember or find out, please let me know!

Related: http://academia.stackexchange.com/questions/14258/visualization-tool-for-paper-citations

Also related: Can you get statistical data on research paper submissions and publications?

If you want to read a paper like that, write it yourself.

What do you intend to do with this information? It is somewhat a specific question, but I wonder if there are other solutions to your problem.

I would google something like "PageRank for Research Papers", since PageRank is Google's algorithm for ranking webpages based on network analysis. Google scholar is handy for finding how many citations a paper has and which papers it has been cited by.


text:
Should I cite sources about a technology description?
I want to add some description of a technology (Node.js = server-side JavaScript) in my thesis. The description is about what exactly this technology is, how it works, what it can do etc.
I want to use Node.js Wikipedia page, a blog page, one of my supervisor's lectures for gathering information.
Should I cite these sources, given the fact that they say pretty much the same things and these things are just observations, not scientific contribution?

What do people normally do, in your field, when they include such descriptions? Familiarize yourself with the norms of your field by reading what others write and emulating it.

If something can be deemed common knowledge in your field there should be no need to cite it.
MIT define common knowledge as;

Broadly speaking, common knowledge refers to information that the average, educated reader would accept as reliable without having to look it up.

There is further detail on that link about Common Knowledge and it's applications. They also say that there best advice is: 'When in doubt, cite your source.'
That said if you are taking something verbatim from a source you should cite it.
Just on your sources; in academia you tend to shy away from citing from wikipedia etc. You can see a discussion on that issue at this question

the thing is that Node.js is a relatively new technology (around 5 years) so not too many poeple would know how it works... at least not as many as the ones who know how C++ or Java work...

@SorinAdrianCarbunaru Who is the audience? If you can assume they already know about Node.js there should be no need to cite. If they don't expect them to have any knowledge you should cite.

I'm writing my Master's thesis... so the main audience is made of the professors from the committee who will evaluate my thesis, and I suppose that at least some of them, don't know about Node.js... but, again, what I want to include in the description is only information like "it's a platform that you have to install on your computer, it is based on this, it works like this and it offers this"... it's more like story telling

If you use information from another source and the people reading your thesis may need to go to that source if its not common knowledge to them then you should cite.

This is the same as citing any other software; you would follow the standard guidelines for such citations. APA guidelines follow, from this Purdue website:

Computer Software/Downloaded Software
Do not cite standard office software (e.g. Word, Excel) or programming languages. Provide references only for specialized software.

Ludwig, T. (2002). PsychInquiry [computer software]. New York: Worth.

Software that is downloaded from a Web site should provide the software’s version and year when available.

Hayes, B., Tesar, B., & Zuraw, K. (2003). OTSoft: Optimality Theory Software (Version 2.1) [Software]. Available from http://www.linguistics.ucla.edu/people/hayes/otsoft/

As usual, you should check with your journal to see whether they have any specific formatting requirements/require any other specific information for such  citations.

Add a footnote
This is supplementary information that isn't required for your thesis, but for some readers might be useful for understanding the context.
This isn't realy a citation - most likely you aren't using Node.js documentation as a direct source for something that you are writing there, unless you're comparing details of some API descriptions. You probably are using a part of node.js technology, and the reference is to extra information about that part, for people who don't know a prerequisite. So it's something where using a footnote would be the most appropriate way.

well, one point of my thesis is the generation of web services which run on the Node.js platform... and I want to describe how the platform works, for people who don't know... and I don't know if such a description should have citations added


text:
How to present a model which is based on the result not yet discussed?
I am facing the following problem while writing a paper. I have a model which contains a function whose explicit form I derived empirically from the data presented in the paper itself.
However, I would like to present the model during the introduction and thus before the result. However, to justify the shape of that function, I have no other way than to anticipate the result (saying something like: “Since in the result of the experiment we found X, we empirically assumed X in the model“). I am not completely happy with this, because I would like to present the result directly in the result session, not earlier.
A solution would be to move the explanation of the model after the results. I do not like this either because I want to fit the real data with the model itself, and I don’t think it is wise to start fitting something without explaining it first.
So, what it your advice in this matter? What would you do?
Also, any papers with example of something similar are welcome.

Two questions: 1) Are you sure that you do not apply circular reasoning? 2) What’s wrong with using a placeholder for that function?

Quite sure. I use the experimental result to get an idea about the shape of the function (for example, its dependency on experimental conditions). This does not imply that the model (which function is only a part of it) will absolutely fit my data. I don't think it is so uncommon to build a model based on empirical findings.
I don't feel I can explain the model satisfying if I do not give an explicit version of the function. Plus, in fitting my data, I use the explicit version, so I need to present it before the fitting.

Side note: reminds me of https://en.wikipedia.org/wiki/Empirical_Bayes_method

Memming: thank you for the interesting point. I have been advised to present the basic part of the model (the one that does not rely on the result) in the introduction, and to introduce and explain the empirical function after the result, fitting the data again. What do you think about this solution?

You have data S, and a model M={H, f(H), g(H)}, where H are the set of assumptions of the model, and {f(H), g(H)} are components of the model that of course depend on the assumptions in some way.
Using the data, you estimate a functional form for f(H), for lack of mathjax denote it empf(S,H)
Then you apply your model to the data and obtain a measure of fit, expressed here in abstract as a distance measure between model and data
{M,S}->d(M,S)*   or **{[H, empf(S,H), g(H)], S}->d([H, empf(S,H), g(H)],S)
One (not all) components of your model had a chance to "fit with the data"  prior to applying the whole model, and so it has increased the chances of your model as a whole to fit the data.
So the "distance" is not purely between model and data -it is a distance between a model that has already come "closer to the data", through empf(S,H), and the data.
In a rather known dialect, "you trained (partly) your model, using the same data set on which you are going to test it". I would not consider this as scientifically acceptable.
The way out of course, is to estimate f by using a different data set, a data set that should, according to your theory, be able also to be represented by the same model. And this also guides you as to how you could go about writing your paper.

Thank you for your answer.
I think that the validity of this line of reasoning depends on the particular formulation of empf. In my case, empf has a really low power to fit the data without the rest of the model, but the models does need an explicit form. It seems reasonable to base this explicit form on empirical findings.
I don't see any scientific problem in this.
Any model which aims to describe reality is based on empirical evidence. Of course the model needs to be tested on more than one dataset to be valid.
If there is any mistake in my reasoning please feel free to let me know.

What I pointed out is that you need to use a different data set for obtaining empf, than the one that you will use to fit the whole model -not that you should not use empirical findings. This has nothing to do with "testing the model on more data sets". Here you are using a data set to form the model (partially), it is not sound practice to then use the same data set to see "whether the model fits well to the data".

I think this depends on how I actually used the data to form the model. One think would be, as you said, to train a model with the dataset and test it with the same dataset. Another thing would be to use the dataset as an indication that, for example, one function of the model need to be concave, as the data shows. Yes, using the model based on the real data increased the chance of fitting the data, but it is possible and reasonable to argue in some cases that most of the "fitting" is done by the part of the model not based on the data itself.

...meaning, for example, that the function in question might have been specified as convex, and nothing visible will change in the results? I understand your view of the matter, but if you cannot somehow quantify "how much of the fitting" is due to the "rest" of the model, I believe your research will be open to easy criticism on this point, perhaps unjustly compared to the overall achievement, but not unjustifiably, nevertheless.


text:
Is it ethical to explicitly or implicitly bias against student papers unless co-authored with senior researcher(s)?
A few days ago I was browsing open-access social-science journals and I found one ‘author guideline’ explicitly saying that they are accepting student submissions if and only if the manuscript is co-authored with the academic advisor or a senior researcher.
I have acquaintances with several editors and editorial board members at various journals and I know from experience that some of us tends to be careful with manuscripts coming from PhD students. This manifests in practices that I find questionable (e.g., insisting on three unanimously positive specialist peer evaluations before acceptance, while a senior researcher’s manuscript may go with only two positives) and in other practices that I find to be biased (like an easier desk reject, or being less willing to deal with them, which results in longer peer evaluation cycles).
Is it justifiable for editors to restrict – formally or informally – the opportunities for PhD students to publish in their journals, like restricting them to submit only co-authored papers or subject their manuscript to more strict criteria than those of senior researchers before acceptance?

I am not from the Social Sciences, but yes, that sounds very questionable to me, especially as a formal policy.

Do they define student in any way? After all, in some countries (like mine) PhD students are not considered students for most purposes. (Not that it is okay in my opinion, if the policy is only against, e.g., undergraduate students.)

No that journal did not gave a specific definition of 'student'; from what they say they can refer to both BA/MA and PhD students (as they all have advisors).

Another question that arises from curiosity (but does not really affect the answers): Is this a pay-to-publish journal?

Not on Beal's list. It is a hybrid journal, both printed an open access. However they charge 10USD for publication per article page (if accepted). I can't say for sure it is not pay-to-publish.

@HunSoc: While most, if not all, publishers on Beall’s list are pay-to-publish, not all everything that is pay-to-publish is predatory and thus belongs on Beall’s list. Pay-to-publish means that the authors have to pay some fee to have their article published and 10 $ per page are such a fee.

In my opinion, such a policy is absolutely unethical.
One of the key principles of science is that scientific work can be done by anybody.  Good science can be done by people who aren't even in academia, let alone by students.  A scientific paper should be evaluated on its merits, not an argument from authority based on its authors.
Now, humans being humans, reviewers will tend to bias towards known authorities and prejudice against unknowns, students, etc.  But this journal's policy, rather than fighting against such a tendency, explicitly enshrines and adopts it.  Likewise with the informal policies that you describe: anything that amplifies unfairness in judgement rather than de-amplifying it is highly suspect and likely scientifically unethical.
This doesn't mean that one should drop standards.  Rather, it means that one should treat a paper coming from a well-known PI at an august institution with just as much suspicion as one from a student author from a developing-world university you've never heard of before.  Being status-conscious primates, we're not very good at doing this, but such a condition is the goal towards which we should strive.
PS: Note that a policy the other way, i.e., student journals that don't accept papers without student authors, is not problematic because it is inverting the privilege gradient.

Yes. The main point is, while it may happen, it can not be an official  policy!

While I’m sure that you’re right in general, I note that when I reviewed papers I was actually slightly more demanding when the author was a ‘name’.

@BrianM.Scott Then I salute you sir, and thank you for your service.

I would agree in general. I do see a problem case though - imagine as a popular journal you receive tons of submissions. you are receiving so many submissions in general that your staff cannot possibly go through them all without creating a run-away backlog. You find that most of the low-quality submissions are coming from papers authored only by a student without the help of a senior. What new rule are you going to create to ensure you can keep up with submissions? Bonus points if your solution also increases quality of submissions..

@DoubleDouble Given the way that publications usually work, I strongly doubt that this case is likely to occur.

You would probably know far better than I. Just thought I'd throw that out there.

@DoubleDouble Rejecting low-quality submissions should be easy and much faster than rejecting high-quality submissions which have subtle problems. Most likely what needs to happen is a list of common errors which cause immediate failure (regardless of author) and quick tests (automated if possible) drawn up.

I know that academia varies strongly and I am not familiar with the customs and procedures in the social sciences. Therefore this answer is based on assuming my field’s situation and it may ignore some pecularity of social sciences that plays into this. Anyway, I want to take another point of view at your example, i.e., the explicit exclusion of papers with only students as authors:
Most papers whose primary author is a student originate from some work happening under supervision, whether the supervisor is a co-author or not. Going by authorship standards, the latter question depends on whether the supervisor made an intellectual contribution to the paper. Often this is ignored and the supervisor is made coauthor for no reason other than being the supervisor. This unethical “custom” is ensured by the student’s strong dependecy on the supervisor and there is no need for journal policies to enforce it.
So, most papers that could potentially be submitted a journal without an advisor as an author are originating from work happening under a supervisor and thus the mentioned restriction can easily be surpassed by the authors by just asking their supervisor to coauthor the paper. Note that easily refers to the practical aspects, as it would be unethical and may have a slight negative impact on the student’s career. Thus, the main consequence of this policy is that supervisors are added to papers ignoring authorship ethics.
Now it is debatable whether rules that lead to unethical behaviour are themselves unethical, but in my opinion they are at least to some extent and hence this policy is unethical – in particular as I can see no positive effect justifying it. I would refuse to review or author for a journal holding such a policy.

I see your point, but following this logic, another main consequence of this policy is to prevent gift sole authorship to students (which is also ignoring authorship ethics).

I also never heard of an official journal policy in the Social Sciences which ban student authored manuscripts altogether, but I was aware that informally, there is some bias against such papers at some editorial boards, hence my original question.

nother main consequence of this policy is to prevent gift sole authorship to students – Do you mean that students are allowed to claim the sole authorship when there actually is a coauthor? If yes, you are right, but is this really something that frequently happens?

How often does a PhD student have a paper ready to submit without enough input from their supervisor(*) to merit a coauthorship?  Such a contribution is likely to  be in experimental design (or equivalent), analysis, and/or actually getting a paper (& figures) to a publishable standard. (*) Or another academic/postdoc who helps supervise some of their work

@ChrisH: What exactly are you aiming at? Sure, the majority of papers by PhD students will have supervisors as rightful coauthors, but those are not affected by the rule in question anyway. For whatever it’s worth, I successfully published one paper without any input from my supervisor (because it was a “hobby” paper not related to my PhD project) and I am going to submit another paper as the sole author in the next days where my supervisor mostly made an internal peer review and does not meet the authorship requirements.

I just mean that with respect to your para 3, the intersection of student-only papers with this misguided policy is necessarily small because the number of legitimate student-only papers is small.  Your case is unusual I would say, though perhaps not in your field.

@ChrisH: I agree that this policy only affects a small portion of the total number of papers, but the majority of papers it does affect are legitimate student-only papers – unless there are a lot of unlegitimate submissions to social-science journals, which I doubt, or some other unknown factor. It’s like making a law that forbids men with long blue hair and a mustache to cross streets whose name begins with a J on Sunday morning – it affects few people, but those whom it does affect it affects negatively and unethically.

That sums it up quite nicely, I agree with your take on it.  The journals I've dealt with are pretty mainstream and don't have policies like this -- in fact some of their other material suggests they would oppose them.  Perhaps we need a list of journals with discriminatory policies relating to authorship etc. to keep the numbers down.

@ChrisH How often does a PhD student have a paper ready to submit without enough input from their supervisor(*) to merit a coauthorship? — In strong PhD programs in my field, about once per semester per PhD student, starting around the third or fourth year of their PhD program.

It is both justifiable and unethical.
It is justifiable because, in practice, the peer review process is rarely good enough to catch all or even most errors that might appear in a manuscript.  The presence of a senior researcher on a manuscript indicates (not in a foolproof way, but it's better than nothing) that someone with the experience and interest to catch (some of) these errors has already had a go at it.
Of course there are cases where exactly the opposite is true (a senior researcher pushes for inclusion of a flaw based upon their hunches/experience), but on balance having a senior person responsible on board improves the quality and lowers the error rate, which lessens the burden on the peer review process, which makes the journal less likely to publish something which is wrong.  (And if they do, people are more likely to blame the senior author than the journal.)
But it is unethical because the long-term success of the academic endeavour depends critically upon the ability of peer review to actually be a good review of the work.  The journal shouldn't be shirking its duty there, or at least if it does it should do so apologetically.  The editorial staff's job includes summarily rejecting papers that have too many basic mistakes (unclear abstract, no references, etc.) that more often are made by Ph.D. students alone, but they can and should do that on the basis of the content of the paper, not the seniority of the authors.
So unless this is the Journal of Opinions of Prominent People whose Importance is a Social Construct, I would view the policy very unfavorably.

Note that just that all authors of a paper are students does not mean that their supervisor did not carefully read the manuscript. The benefits of “internal peer review” are (hopefully) common wisdom and if the advisor isn’t an author, what better choice for an internal reviewer is there? (And tomorrow a manuscript introduces a rule that at least one senior scientist must be acknowledged for critical comments on earlier versions of the manuscript or similar.)

@Wrzlprmft - It's still likely that on average papers with a supervisor's name in the author list are better-read by said supervisor than those that aren't.

Sorry, IMHO that is not justifiable. You can't try to fix one problem (incomplete revisions) by implementing another problem (a unethical policy). I won't even elaborate on expanding this logic to other problems to not automatically lose the discussion :)

@FábioDias - If your only measure is how good overall outcomes are, it's absolutely possible to partially fix one problem by introducing a second compensatory problem that fixes more than it breaks.  In other words, it's justifiable in that it arguably results in better outcomes than lousy peer review without additional measures to help ensure the accuracy of the paper.  This doesn't mean that it's the best course of action, or that it's right, just that it sorta works, and its sorta-workingness is a justification for the policy.


text:
Official Transcripts: Applying to Previous University
I am applying for Graduate Admissions to the Previous University where I graduated nearly 10 years ago.
Application says to send official copies of Transcripts from Previous University.
But I am applying to Previous University, shouldn't they have it?
Sure, I can upload photocopies of their transcripts (application process is online only), but what else do I need to do?
How do I address this in application?
How do I tell them "I am uploading copies of Transcript, but you already have official Transcript"
Thanks!
Ok
I'll request official transcripts and return it back to them

Whether they have it or not, including a copy will make the admissions office's job much easier. If at all possible, follow the instructions.

@keshlam I updated question. Sure, I'll upload copies, but how to tell them they already have Official Transcripts?

So in other words, request one department of the University send itself official copies of transcripts.

In keeping with the tone of the existing answer and the comments:
Just do what the application instructions say.
In the best case, the university agrees that you do not need to send the transcript. You have saved yourself about 5 minutes of work.
In the worst case, your application is desk-rejected by an overzealous clerk. You never even find out why.
In a plausible middle-of-the-road case, you need to send some clarifying mails back and forth about why you haven't included the transcript. You initially saved 5 minutes of work, and then spent 30 minutes. Worse, somebody else also needs to spend some time on this.
Frankly, even writing this question probably already took longer than just sending the transcripts.

So in other words, upload copies of Transcripts, and then request the University send itself Official Copies?

@SohniMahiwal, no. Just add the official transcripts as everybody else does.

As the comments say, you make the applications office job easier by getting them through the regular channels, and forward them as anybody else would do.
At least around here, the graduate admissions office is quite separate from undergraduate affairs, so it would be a significant hassle for them to ask for transcripts. They might even be pissed off enough to just file your application under "incomplete" in the round archive.


text:
Conversational tone of Statement of Purpose Essay
I am writing Statement of Purpose Essay for University, which happens to be my alma matar.
It asks how has academic and work experience prepared me for graduate education.
For one, I already had graduate education, but so many other things, especially the intangibles in life have prepared me, or made me more mature, and receptive to higher education.
My question is, can I make the essay conversational, or does it have to be dead-on-serious.
For example, I wish to write (because my alma matter used to be called A, now is called B, see previous post)

After earning Masters degree from A (oops, slip of tongue, I've always
  called my alma matter A) I moved 200 miles away from home to live and
  work in XYZ.

or should I write

After earning Masters degree from B I moved 200 miles away from home to live
  and work in XYZ.

Honestly if it was me going over applications, and as long as the person answered the questions thoroughly and clearly and had all the qualifications, I would be amused and appreciate such a down-to-earth Statement of Purpose.
It certainly breaks the mold of reading stiff Statement of Purpose from kids who just come out of Undergraduate, really haven't seen the world, and really learned to lighten up.
Please weigh in. If you were going over applications, which statement would you prefer.

Don't do it.  A statement of purpose is an opportunity to demonstrate your formal writing abilities.  Jokes like this make it sound like you are not taking the application seriously.  (And I don't really think this one is funny, anyway.)
Also, be concise and to the point.  I don't see how the name of the town where you moved, nor the number of miles between it and your university, has any relevance to your application - people who are reading large numbers of such statements really don't want to spend time on unnecessary text.  Stick to information about what you have accomplished and how you believe it is relevant to your preparation for graduate study.
You can certainly highlight the fact that you graduated from this university, and perhaps mention any particular aspects of it that make it a good fit for you.  But you can do that in a serious and professional tone.

ok ok ... I'll keep it to the point. I guess when reading large number of applications you would like to finish sooner. It's like Microsofts Script Guy tutorials ... too many corney jokes that I no longer visit the page

Irony is, I was limited by space on the essay and had to omit other interesting, yet relevant things that prepared me for graduate studies, i.e. living on my own, intangibles in work environment, hobbies that expand mind to help work-related tasks, thinking out of the box. Your answer gives new perspective.


text:
How to answer “Why is graduate study important at this time in your life?”, when the reasons are very personal?
I am applying to our organization‘s scholarship program to pay for graduate school (if I get accepted).
One of essay questions is:

Why is graduate study important at this time in your life?

Well, there are lot of personal reasons for that. For instance, I wish to get my mind off a terrible tragedy in my life that happened about a year or two ago, and they say being productive and busy is one of the best ways to get over things.
Question: How much personal things to include in a scholarship essay? Would this add depth to the essay, or simply detract. I mean, the word life is in the question and it includes all sorts of things beyond academics and career.
Update
Thank you all for your feedback.
It also answered other questions that I did not post, so a big thank you to all.

@ChrisWhite That's a good idea. Might post on Workplace because its my employer that is funding this.

"they say being productive and busy is one of the best ways to get over things"... for my personal experience, I think this is incredibly bad advice. In this way you do not get over things. You simply forget about them, without resolving the actual issues. Which means if in the future that situations, for some reason, comes to your mind again you'll be in the same situation as before. Running from problems doesn't solve them. Sure standing up against a tragedy (a loss in my case) is hard, but distracting doesn't really help in the long run.

@Bakuriu Well, that does make sense. I mean, I'll still apply for scholarship for grad school, but I won't try to forget these situations.

To add to what @Bakuriu said - there are a lot of different methods to get over tragedy. "Standing up" to a tragedy, means to understand why its made you feel the way you felt, accepting what you [could have done/ were not able to do], and letting it go.. moving on as a better and wiser person. Different religions (not that I'm for, or against, religion) usually offer different ways to achieve that, and therapists or counselors can also help lead to understanding. Being able to let go of any pain you still have, (if you still have any) might be worth looking into your options.

@DoubleDouble Thank you so much. In Buddhism they say face the pain and thoroughly analyze it in a detached sort of way. We all get badly hurt at some point or another.

You should probably keep your academic interests as the main point. If you write that you are applying to recover from a tragedy in your life, it might not be clear whether you are actually interested in that specific program (or are you just looking for something to do) or whether you might change your mind later.
Also, someone could suspect whether you could tolerate additional stress right now.
Anyway, if you have been out of work or study for a long time due to the tragedy, it is probably best to briefly mention it.

I like this approach best.

You want the readers to feel like you want to be running to something - not away from something.

For instance, I wish to get my mind off a terrible tragedy in my life that happened about a year or two ago, and they say being productive and busy is one of the best ways to get over things.

When you say this, I read it as:

I want to distract myself since I'm emotionally unstable and a wreck. I'm hoping to bury myself in my work and make my problems go away and not deal with them.

It's important to consider how the person reading what you write will interpret it. You might say, in your words, one thing but those reading it might interpret something very different.
In this case, there is nearly no way to write what you are attempting to communicate without worrying the reader.
Instead, write something more like:

I really want to focus on learning. I have a passion for this and I've really been missing the focused learning available in graduate school

or something similar, etc.

If I put a summary on your answer, it would be "Don't focus on what prevented you from doing it previously, focus on why you want to do it now, and what you want for your future."

I would caution against including too much intimate personal information on scholarship application.
First, it is not clear how your personal story will be received by the people reading your application. Depending on the nature of the tragedy, some people may feel sympathy, but others may find themselves offended or uncomfortable when reading the essay.
Secondly, certain personal tragedies are "stereotypical", such as wanting to study cancer biology after the death of a family member or wanting to study clinical psychology after suffering from mental disorders. Although there is nothing wrong with these experiences motivating your desire to study a particular field, such stories have been used so many times that they tell very little about you as a suitable applicant to graduate school.
Finally, I don't see how the personal tragedy provides a compelling reason why your graduate study should be funded. True, being a graduate student will keep you busy, but there are many other cheaper ways to keep yourself engaged. If you insisting on putting this personal experience in your essay, you should think about why graduate study stands out as the best course of actions.

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text:
What are the best question to ask a committee panel after a PhD interview?
I've a Skype interview for PhD application (it will make me miss one of my classes today.) I've been asked, in advance, to prepare a short presentation and then there would be some discussion with the panel (I guess.) I expect that they will ask if I have some questions so, I'm wondering what are the best (type of) questions one might consider?

It is not mandatory to ask questions. Generally they offer you the opportunity to ask questions in case you are not sure or confused about anything or any process related to application/lab/university.
When I had given PhD application interview almost all times interviewer asked me if I have any question. I didn't ask questions for most of the time. However few times I do asked question specially when position they were offering had partial financial support from supervisor. That case I asked about chances of getting rest of financial support. They were quite helpful and actually suggested me to check for RA positions in other related departments. In another case, I asked professor about possibility of collaborative work because I was interested in some interdisciplinary work. He was very impressed by question as it showed that I had already focused area of interest.
I also remember few of my friends have asked questions like, "Are there many flowering plants around campus because I am allergic to pollen-grains?" , "Can I get accommodation on campus if a dependent is accompanying me? ", "You were working on XX problem before are you still working on that?" etc.
You should ask questions depending on university you are applying and professors interviewing you. Do some basic research on their background from university web page. Don't ask cliche questions and don't ask for the sake of asking.

I guess, your presentation topic must be in alignment with the interviewing professor's research area so IMHO it's best if you ask some questions like (1) What is the future plan or goal of that research i.e. some abstract model or a prototype etc. (2) You can discuss about your ideas which you got after reading any of his paper.

I guess, your presentation topic must be in alignment with the interviewing professor's research area, Yes, it has to be. By the way it is just and introductory demo to highlight my back ground and my future goals.

One of my favorite go-to questions is along the lines of "why should I choose you?" Basically, ask them what makes their research group different or special, compared to other places you might be applying for. You could research X at a million different places, so why is institute Y the best? I think this question is great for a few reasons. It's nice and open-ended, and you'll often get an interesting response that can give you some insight into the group. It's a versatile question, so you can ask it literally anywhere you interview, but it still has more substance than "when's lunch?" Finally, it puts an ever-so-small amount of pressure on the interviewer by shifting the dynamic so that they're trying to impress you, rather than the other way around.
Of course be a little gentle with the phrasing of the question. Something like, "I've been applying to a number of PhD programs, and I know that Institute Y is one of the best departments with great faculty and an excellent lab. I've been wondering, though, what do you think makes this place unique, or what's different about it compared to some of the other top-tier research institutes?"

"why should I choose you?", I doubt that's good question to ask.

you should ask something around the lines: What qualities do you think I am missing, that would make me a better candidate?
He will tell you what he perceives as your weak points and give you a chance to elaborate.
E.g.:

Student: What qualities do you think I am missing, that would make me a better candidate?
Prof: It would be nice if you have more publications
Student: I didn't manage to publish anything yet, however we have  3 manuscripts submitted, 2 in preparation and I am a columnist for 'Cats and Dogs' magazine.
Prof: You're hired!

Unfortunately, I followed this answer, and I was not selected :)

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text:
Strategies to avoid burn out due to systemic lack of time
When I was an undergrad student I used to procrastinate a lot. I managed to get things done in the nick of time by staying up all night before exams, and so on. Not very different from what Tim Urban talks about here. That's why I know this is not my problem any more. During my PhD I managed to stop procrastinating by virtue of having no other option: it was impossible to finish up everything I had do to on time unless I worked on it steadily (including until late at night and sometimes on the weekends).
During my short career in academia (I'm now into my 4th year of postdoc) I have always expected my work load to start decreasing at some point. Reality speaks a different truth: my work load has steadily increased from day 1 of my PhD until today.
Now I have to work on my own research, supervise students' research, write grants, do peer review, prepare conferences and seminars, and some teaching. With the added weight of lack of job security (even in the short term).
Even though I work long hours, I just literally don't have enough time to do everything I need to do. I always find myself working on a priority basis: try to get whatever has its deadline approaching nearest done first. Just by looking around I can see this is a systemic problem, some of my colleagues have it even worse than me.
I find myself on the brink of burnout. What are effective strategies to both avoid burnout and optimize time management in academia, having as a premise that it is literally impossible to wholly fulfill all of one's commitments?

Are you looking for mental/emotional strategies to avoid feeling burnout despite being overwhelmed with work, or practical time management techniques to avoid being overwhelmed with work in the first place? Please [edit] your post to clarify.

@ff524 Ideally, both better than either.

Related: http://academia.stackexchange.com/questions/7668/what-can-i-do-to-recover-from-a-short-term-burnout/7692#7692 and http://academia.stackexchange.com/questions/9331/too-burnt-out-to-continue-msc

I find myself on the brink of burnout. What are effective strategies to avoid burnout and optimize time management in academia, having as a premise that it is literally impossible to wholly fulfill all of one's commitments?

Find a therapist. Really. There is no shame in getting help when dealing with a difficult life situation. This won't reduce your workload, but a therapist should be able to give you custom tips for better managing it.
Learn to say no. Fundamentally, if your workload has been ever increasing, this is a good sign that you are bad at saying "no" to tasks. This is an extremely important skill to learn, and a therapist may be able to help you learn it if you can't do it on your own.
Start delegating. In addition to saying "no" to tasks, start delegating (parts of) the tasks that you still agree to carry out. Remember how you as a PhD student sometimes needed to help the senior people in your team with organisational varia, reviews, literature searches, etc.? You are now one of those senior people. Don't be shy to ask the students you help supervise to lend a hand with your tasks.
Accept that sometimes there is too little time to get everything done (or: accept that sometimes some things can't be done well in the time that is available). Many of us have this little perfectionist in us that requires us to (a) come through on everything we promised at some point, and (b) do everything in the best possible quality. In real life, there is usually just enough time to do some things well, and the rest either not at all or in mediocre quality. This is not your fault, and it is best to accept that sometimes you will give a presentation that's not very well prepared, or be unable to submit to this workshop even though you promised the chair a month ago.
Be aware of your priorities. Relatedly, be aware of what you personally really value and want to do right. For me, being badly prepared for teaching is a no-no. For you, it may be skipping a major paper or grant deadline. Note that I specifically said your priorities, not necessarily the priorities of your postdoc advisor or students. While in an ideal world you want to take their preferences and needs into account as well, if push comes to shove you can't consistently ignore your own priorities over the needs of others. Four years into your postdoc you should easily be senior and independent enough that you can push back if your mentor wants to force her/his own agenda onto you (if this is not the case, I suggest getting the heck out of there).

Thanks, I think this is sound advice. I have trouble both delegating and overlooking the details (the perfectionism you write about). Ironically, I have considered therapy for some time now, but have postponed seeing a therapist because "I don't have the time". I will wait for other answers before accepting this.

+1. Instead of a therapist, a coach may be called for - your university may even offer such coaching. And/or a good book on time management and prioritization. I personally like Getting Things Done. Either one will require some up-front time investment, though, but it's better than burnout.

Delegation is particularly important; you need to make sure your time goes primarily to the tasks that you are uniquely situated to address. I view these tasks as leadership oriented (identifying research questions, designing experiments, communicating results), and teaching others to handle the responsibilities that can be delegated will give you more time to do the tasks that the lab can only get from you. As you advance upward your time gets more valuable, it is unfair to both yourself and your lab to not spend that time contributing in the most beneficial way you can.

One thing that really helped me through grad school was learning to focus on energy management over time management. There's a whole school of thought on this practice, but I rather like this quote from HBR:

The core problem with working longer hours is that time is a finite
  resource. Energy is a different story. Defined in physics as the
  capacity to work, energy comes from four main wellsprings in human
  beings: the body, emotions, mind, and spirit. In each, energy can be
  systematically expanded and regularly renewed by establishing specific
  rituals—behaviors that are intentionally practiced and precisely
  scheduled, with the goal of making them unconscious and automatic as
  quickly as possible.

So, in academia, learning to optimize your energy might take the form of minimizing the number of decisions you have to make on a daily basis. I wholly concur with the above suggestions to delegate, prioritize, and accept that things won't always be perfect.
The main one that I'm going to add is to automate where possible. Software can be a miracle worker for academic productivity, but it can also be it's own vacuum if you spend more time fiddling with an app than letting it help you. So choose wisely. Any tool you select shouldn't be based on the most bells and whistles available, but rather what's going to easily fit into your workflow to automate the little decisions you have to make. The idea is to save your energy for the big stuff, the fun stuff. Here's a few places you might think about simplifying and automating:

Your email inbox. Streak is a GREAT tool here if you use Gmail - check out some academic use cases here). Scheduling interviews for a research project? Automate the follow-up. Writing a book? Automate the invitations. You get the gist.
Your reading list. The way you keep track of "what to read next" will probably depend on how you like to read, but for me, adding something to my reading list should never be more than a Chrome extension away. Consider Pocket, Google Keep, or something more multipurpose like Evernote.
Your collaborative projects. Please don't waste time emailing versions of a paper back and forth. In 2016-going-on-17, collaboration with your academic colleagues should be real-time (even if they're still insisting on using Microsoft Word). Ain't nobody got time for version control. Google Docs, Authorea, ShareLaTex etc. are all great options for working on academic papers and other projects with collaborators.

Whatever you can do to optimize the energy you devote to your academic work, the better positioned you will be to both manage your time and avoid burnout. And remember somewhere underneath all the craziness this is actually supposed to be fun!

Thanks a lot for pointing out to Streak. It really helped out cleaning the mess scheduling seminars caused in my mailbox.


text:
Interviewing for a lecturer position in the UK
I have been invited to interview for a lecturer position (AFAIK, equivalent to assistant professor elsewhere) in the UK, after being pre-selected following a Skype interview. This means that the department is probably reasonably interested in me as a prospective hire. I have been a postdoc for 3.5 years now, and this is my first interview at this level.
I also do not have much experience with interviews in general, since I got my PhD position at the first try, and then was offered my postdoc position (I did not interview for it). In the middle I had two other interviews for postdocs that I didn't get, one of which went badly on my part. The other one went well but the position was extremely competitive (1% chance) which makes drawing conclusions difficult.
So I would like to have some pointers from academics who are familiar with the UK system on what to expect and how to best prepare for the interview. The email they sent me asked me to deliver a 30-minute presentation on "your research, enterprise and teaching aspirations at [univeristy name], with the first 5 minutes directed at an Undergraduate audience". Then, there will be a panel interview, followed by tour of the department and lunch. I should add this position puts more emphasis on research than teaching (externally funded).
Specifically, I'm interested in:

What to focus on during the presentation, e.g., what is a good balance of my past/present research versus future plans
Should I link the undergradute part to my research topics?
What kind of content the panel is expecting from me: "research, enterprise and teaching aspirations" sounds a bit vague (perhaps that's intentional?)
What to expect from the panel interview: technical questions, career plans, ...?

Update:
I had the interview, which I think went reasonably well. I found the advice given by the accepted answer to be quite valuable in the end. Things that came up were for example 1) subjects that I can contribute to the teaching portfolio of the department which are not currently taught, 2) what kind of funding I am going to secure to do research, 3) how my research ties in with what current members of the department are researching, 4) why I chose this university/department, 5) some more technical/specific questions about the research project attached to the position (as I said this position is externally funded).
Things that did not come up were salary or REF.

Update2:
I was offered the position. Unfortunately (or maybe not) I could not accept it because of a mixture of personal and professional reasons.

I suggest that you should add details about your subject area, as this may well make a big difference to the answer.

@NeilStrickland The area is computational chemistry/physics.

UK hiring is all about the REF.

@StrongBad I'll try to have a good look, although I'm pressed right now to finish up my presentation. What specific sections of the website are most relevant?

Re the REF, all UK universities obsess about their position in this, to a greater or lesser extent (there is non-trivial central funding attached to the scores). The methodology changes from REF to REF (infuriatingly), so everyone's second-guessing the process (infuriatingly), and the whole damn thing is a sink of effort (infuriatingly). If you can roughly indicate how you might fit in to their submission for the ‘Unit of Assessment’ they're part of, and even improve their ranking, they will listen.

This is all pretty standard practise for UK  lectureships. They are basically testing your skills that will be required in the position.
In the presentation they will want to see a demonstration  that you can communicate your own specialism to both an undergraduate audience (as in teaching class) and your research peers (like for a conference). They want to know that you understand how research  is done and where the money comes from (knowledge of funding sources), and some assurance that you demonstrate the basic skills to communicate and cooperate with others already in the department to achieve  that goal. They will also want some indication that you have done some background intelligence to discover their particular departmental specialisms and how your skills will fit in their niche. You should at least have read the pages on their web site!
The presentation is likely to be done in a "public" venue with most staff and PhD's invited, who will also ask you questions at the end, just as if it was a research  paper.
The  interview will be behind closed door with the panel, often with senior staff such as Deans and HR who will ask questions that verify things from your CV/Resume. They will find out about your past employment, measure your level of experience, salary expectation plans for career development and so on. They would want to know how long you planned to stay with them to know if their investment in you was returned. They would want to know that you were self assured and reliant and not dependant on your previous supervisors, but conversely not a loner who could not collaborate with the existing and future teams.

The only additional point I would add is to expect in the interview to be asked how and where you would get funding for your research, so do some study on how UK funding works.

They'll also want to know what recent outputs you have that are suitable for submission to the REF, and what plans you have to produce further such outputs.

A very UK specific thing is the REF. It is an exercise that happens every 6 years or so. Every university in the UK obsesses over it. While the rules/targets keep changing, it has consistently stressed quality over quantity. The last REF only looked at your top 4 outputs. What hiring committee was to know is what would your previous REF submission have looked like and what your submission for the next REF will be. Be prepared to answer what your top 4 publications are from 2008-2014 and your top 4 from 2015 forward and future publishing plans are.

There will be a lot about the TEF in this hiring round, as fees may be linked to TEF results. Previous hiring rounds were REF  obsessed but it is a changing landscape. More senior hires would be looking at REF capability.

Just for the sake of one data point: neither REF nor TEF came up in the interview.