realllllJulia

Wow, that blog link is really interesting and I think I can learn a lot from that! I can share how I read scientific papers but I don't think I have such a detailed system.
It does depend a lot on what I want to get out of the paper because that dictates how much time/energy I spend on the paper. Since you asked about reading papers "quickly", I'll talk about the three methods I use for the lowest level of reading.
Level 0, for "keeping up" reading: The goal of this reading is to ensure I know about the latest papers. Every day, the pre-print server I subscribe to sends me a list of paper titles and abstracts for my subfield. This is how I mostly "keep up". The other way I "keep up" is to follow social media for my subfield---there are several facebook groups for various areas of interest to me and papers are discussed there. I also stay connected with my colleagues and see what papers they find interesting.
When I do this type of reading, I will read the paper title and the abstract. If I remain interested, I might also skim the introduction since that's how people put their work in context with the field. Once you are familiar with the subject area, skimming for key words and citations will tell you what area of the field they are building on. The main goal of the Introduction reading is to figure out what important question they are addressing and why I should care. Then, I skip right to the conclusion and see what their results are. I do all of this reading/skimming without taking notes. Usually over my morning coffee. I try to spend about 5 minutes per paper.
At this point, I decide whether or not to spend more time on the article. If I find the motivation compelling and the results significant, I will put the paper in my Mendeley library for further reading (see below) at a later time (sometimes right away if I'm really excited about it). Otherwise, I move onto the next one.
Level 1, for "cataloguing" papers. The goal is now to take good summary notes on these papers so that I am able to find more details when I need them in the future. I may never need them in the future. I download the PDF and import it to my Mendeley library. I assign it a unique ID (usually AuthorLastNameYear plus additional letters for extra papers in the same year). I have some Mendeley tags that I use to organize papers by topics (like Gmail labels) that I also assign. I also have some special tags like "citeThisinPaperX" so that I don't forget to cite the paper when I get around to writing it. After adding this meta-data, I read the abstract, intro and conclusions again.
This time, I will highlight key words. The goal is that if I am looking for details about X in the future, I want to be able to quickly flip through this PDF on Mendeley and have these important words pop out to me. I will also read over the methods section to ensure I know what they are doing. Often, this allows me to classify the paper further (using tags if appropriate). I'll also skim the rest of the paper, particularly the discussion to see their interpretation and any caveats. I use the "Notes" field of Mendeley to write a very short summary of the paper. Here, I also mention anything interesting that comes up or if I have any concerns, e.g. a new method, an unorthodox method, interesting interpretation, problematic assumptions, etc. I think this type of reading takes me about 30 minutes to do per paper.
Level 2, for "understanding" a paper. This is a more careful reading. I actually read every word this time instead of just skimming. I use more highlighting. I also now use the sticky notes annotation tool in Mendeley. One big use of the sticky notes is to make sure I can understand the authors' flow of logic in each section. After each section, if I found the logic hard to follow, I try to figure it out and then write a sticky note that summarizes what I thought they were trying to say in that area. I also add sticky notes for Methods. Since these notes are searchable, I try to use standardized terms so that I can find related papers easily. For the discussion and results sections, I use sticky notes to summarize each and every one of their individual findings (whereas in the above sections, I focus more on the big picture results). I add my own commentary to their interpretations where appropriate. The goal is to annotate the paper enough that when I view the paper in Mendeley, I can click the notes tab and see just the list of my sticky notes. I should be able to reconstruct the main argument from the sticky notes without having to read the paper again.  If I have done the "Level 0" and "Level 1" readings before this, then this more in-depth reading usually takes 1-2 hours, depending on the paper length and whether I already know a lot about the field. Sometimes it can take up to a half-day if I'm trying to read way outside of my area. I sometimes also print out a paper to read at this depth because it's a little easier for me to read things in print and when I want to be able to read it while away from my desk. I try not to print too much because it wastes paper and I will have to spend time importing my annotations into Mendeley.
I usually do "Level 0" and "Level 1" every day (or at least try to). The "Level 2" reading happens maybe once per week (a little bit more recently because there's lots of cool stuff). This is the depth I read to when I want to be able to speak about a paper at a Journal Club or something informal. Deeper reading levels, for me, include reading related papers , comparing results across papers, and making even more notes. I don't usually seek out papers to read to this depth level. Instead, I only do it when I need to, for example, when starting a new area of research and needing to know the foundational papers, or when I really need a question answered.

The ability to handle rejection and outright hostility without taking it personally is a skill you will need to succeed in this field (and academia more broadly, perhaps life...). As a graduate student I didn't expect everyone to love my work, but I never expected people to outright tell me it was garbage. I didn't have thick enough skin for such comments at first, and it was a struggle to find my confidence pretty early on in my program. It's important to view comments on your work as separate from comments about yourself. It's hard not to take it personally. There is something to be said about coming in with pre-existing skills in combinatorics, probability theory, and programming (be it R and/or Stata, LaTex etc), but the capacity to deal with pretty destructive (as opposed to constructive) criticism is really important. 

Your employer (i.e. the school/department) should provide you with all necessary supplies (e.g. textbooks for the course, etc.).
But I find it's fun (for me, as a TA) to have some non-necessary things to make the job easier. For example, I get a nice pen that I like using so grading feels less tedious. I also get stickers for my students' homework.

If you're tech savvy, I would recommend getting a desktop computer with 16GB of RAM, a 128GB or 256GB SSD for the operating system and an additional 1TB HDD for files, and an i7 CPU with 4 cores (and 8 threads). Then, simply get a basic functional laptop and use to remote in to the desktop. If you're only getting a laptop, you want something with 8GB RAM minimum, and I'd still recommend an i7 dual-core CPU (with 4 threads). 
I really learned the value of a powerful CPU if you're running intensive simulations. Setting up simulations to run in parallel across the threads of your processor saves a ton of time. You may have access to a cluster, but for my work I didn't find it worth the hassle. I would personally rather just have a powerful desktop of my own. I'm starting a new job in July and will be building a desktop with the AMD Ryzen Threadripper CPU with 16 cores (and 32 threads)... I'm salivating over how fast my simulations will run on it!

In statistics (and I think biostatistics too), the PhD thesis is usually two or three of your papers stapled together, along with a literature review and a conclusion/future work section. Your PhD advisor will help guide you along the way, so you won't be left completely to yourself -- they will help you find a "doable" open problem for your first project, and help you through the entire process of: manuscript preparation (you'll probably go through multiple edits *before* even submitting to a journal), the initial submission, revise and resubmit process, the point-by-point response to reviewers, etc. Your advisor will know what is considered publishable quality and also have some idea of which journals are the most appropriate venues to submit your work to. 
Most PhD students have no idea what open problems are out there when they first start, so the bulk of the first semester after passing written qualifying exams will probably be spent just reading papers and books, teaching yourself a new area, and doing small exploratory projects (e.g. running simulations, reproducing results from a "seminal" paper, or something like that). A lot of stat/biostat PhD students will also have one or a couple of third/fourth author publications from helping out other people on projects (i.e. they'll be listed as a co-author for writing some R code, performing some data analysis, or otherwise making some small contribution).
However, by the time you finish, you should ideally have at least two FIRST author papers where most of the work was your own (the idea, the algorithm(s), the theory and proofs if any). At the end of the PhD, you ideally *should* know more about your topic than your advisor (it's your research after all).

I don't know if this is outside of the norm, but I gave my recommenders a few USB drives with their names inscribed on it. They seemed quite happy and I know they are using them; I am handed files in them sometimes :-) A cheap and techie gift for a techie group of people :-)

Berkoooooley (Computer Science, PhD (F18) Rejected via Website on 5 Mar 2018 U 5 Mar 2018 report spam Like I give a damn. Give my money BACK!  
Hit me right in the financial feels. SAME.

I second you. With only one acceptance so far, it's really frustrated. And I feel like my confidence has been torn gradually in this waiting game.
Though I still have three programs pending, I'm just hardly able to be as positive as I was when I applied. 

Feels like this will be a big week! Good luck to everyone

Oh, this one is now my most favorite:
Valar morghulis, one must only be patient

If you like sci-fi and mystery checkout Altered Carbon. It's been a fun watch so far

I'm losing my mind in this endless waiting game.

Waitlist advice threads:
 

Thank you @bluebird8 and @00ber! My troubles are over! Received an e-mail this morning confirming that I have been accepted with a 45% tuition scholarship!!!
Since it's my first choice I won't be applying to the other two programs.
Good luck everyone & keep positive. Good news is on its way for all of us.
 

Somebody's an All-Star....
 
ีUniversity Of Wisconsin - Madison Physics, PhD (F18) Rejected via Other on 14 Feb 2018 ♦ A 14 Feb 2018 Some-body once told me my study habits were going to role me. I ain't the sharpest tool in the shed. I was lookin kinda dumb with my application done and the night I hit myself in the fore-head, cuz My scores were nowhere near good enough for this school. rip, I so badly wanted to go here. Didn't oficially get rejected but at this point I have given up hope.

On Valentine's day...
 
Roses are red, violets are blue, Harvard said, "Nah, we just don't like you."

Assuming that Duke admitted for their goal class size of 12, and that 15% of domestic students roughly made the short list for the past three years then there were 35 domestic shortlisted students and 27 of them were offered admission based on their official statistics.  That is approximately 77%.  However range is probably something more like (60-90%).  I am not super confident in that estimate but I taking that as it’s definitely worth the wait.
Edit:  I guess I can come up with something a little bit better.   I’ll think about it. 

When I applied to MS two years ago, the decisions came out from early Feb till Early April. And the good ones came last.
                                                                                                 Wait and Hope!

When I applied to MS two years ago, the decisions came out from early Feb till Early April. And the good ones came last.
                                                                                                 Wait and Hope!

I'm losing my mind in this endless waiting game.

I'm losing my mind in this endless waiting game.

I'm losing my mind in this endless waiting game.

It took me this, my third round, to get ONE positive response - It is so incredibly heartbreaking and difficult; I get this so hard. But, if you really want it, do not give up. 
My first round I applied to 10 I believe and got shut out.
Second round I applied to 8 and got shut out, but I didn't hear from USC until AFTER April 15th, so I assume I was waitlisted there and didn't make the cut.
Third round, this round, I applied to 9 and have heard back from 1 so far (luckily it was an acceptance).

Just saw a good one that took me a couple minutes to get.
Stanford History, PhD (F18) Rejected via Website on 10 Feb 2018   11 Feb 2018 ?lo alto Poo-lo Alto.