SEO Blackhattery Superhack #1: Make a very simple statement that nobody can argue with and put a swearword in the title to make it exciting. Submit to social sites. Rake in the fucking money.

Science is disillusioning. I used to have a 2nd job doing programming work for bioinformatics researchers. I did this off and on for about 4 years: 2000-2004. I had two reasons for doing this - I harbored a desire to do 'science' and contribute to the grand body of human knowledge. I hoped the contacts I made would help me get into a good graduate program. The other reason was money - I worked in my spare time and made an extra 70 grand a year doing this. Note to hackers: if you want a really easy job that pays pretty well, makes you appear smart on your resume, and gives you a lot of free time to work on side projects, I highly recommend befriending the PI of a well-funded university research group that needs a programmer.

The reason I was brought in was because in addition to the research paperwork, the grants I worked on required some software artifact to be produced. The grad students and post-docs working on the project were unable to write software, so I was the hired gun. What I produced was crap, but I'm not sure that mattered. It just had to survive a demo at the end of the year and get to the grant renewal stage (in startup speak, 'next funding round.')

I'm not sure if the other researchers were actually unable to write software, or if they were just uninterested in doing so. It was strange to me, since the department I worked for was pretty much 'bioinformatics' - the point of which was to design software tools for biological research. It seemed like people should want to know how to make software, since it was...uh... kind of important to what they were doing.

The day to day environment was much like "The Office", only it was in a "lab", and it was seldom funny. The lab had a laboratory area, with test tubes and fume hoods and whatnot. The main workspace, however, was essentially a cube farm, except instead of out in an office park somewhere, it was above the university hospital's food court.

Most of the people working there were like people working at any big, lame bureaucratic institution, only they had or were obtaining PhDs. Most of their time was spent surfing the web, sending email, and attending meetings. I have never worked anywhere else where people attended so many meetings. I once worked at a giant megacorp for a year, and would lose my mind when I had to go to three meetings a week. At the research lab, they had on average three meetings per day. Journal club, data sharing, data club, journal sharing, guest lecture, team status report meeting, department status report meeting, grant status report meeting, etc. I'm familiar with the horror stories about post-docs working 100 hours a week, but if other programs are similar to the one I worked for, 40 of those hours are spent in meetings, 20 hours are spent wasting time on the internet, 10 hours are typical office chatting, 15 hours of going to classes and lectures, and then maybe 15 hours of actual work... but I'm skeptical that anyone spent 15 additional hours doing work. Normally everything was queued up until the very last moment, then people would spend a couple feverish days slapping something together before a presentation.

I shuffled around between a few different projects and was able to do most of my work offsite. I learned about some cool ideas, but didn't really feel like I was contributing to much of anything. On the last project I spent more time at the lab, simply because I was tired of working at home. Aside from a couple strange aspergy maniacs, most of the people seemed very depressed. One woman finished up her PhD and was planning on moving back to Europe to run her parent's bed and breakfast. Two others were really hoping to get into dental school.

I'm not sure what the people were being trained to do. The wet lab work was supposed to be done by PhDs, but could have easily been handled by undergraduates. Indeed, anything that required advanced knowledge actually WAS done by a young indian female undergraduate who seemed quite harried after being stuck in the lab while her post-doc and grad-student peers were off at another journal sharing. The software work simply wasn't done by anyone in the lab at all - it was all done by hired contractors like myself. It seemed that the only practical training that people received was in reading journals and applying for grants. The most 'successful' guy in the program was hired for $90,000 by a pharmaceutical firm where his job was to read and organize various journal articles...

I could go on and on about this, but the longwinded 'point' I wanted to make was that I agree with the article. I worked in a hot field at the time with a lot of grant money, and it was very bleak and depressing. And, before I get the chorus of people telling me that things are different at good universities, all of this work was done at that other university in Cambridge, the one down the street from MIT with a square named after it.

Do whatever would make users love you so much that they spontaneously recommend you to their friends.

Anyone else suspicious that this article from a site called seoblackhat got 26 points and got to the top of hacker news in 3 hours?

I am.

Although I agree with nearly everything he says in this essay, it's worth pointing out that he has written several other pieces that would make most normal people question his grip on sanity. At the very least, this guy is eccentric. Also, the numbers he cited are from 1999, and are getting a bit dated. NIH post-doc stipends are now roughly $40k/year (including in the most expensive cities, like San Francisco); grad-student stipends are around $25k per year.

Everything else is true, in my experience. If you start a PhD in the physical or biological sciences this year, you'll spend 5-10 years in grad school, barely making ends meet at $25k a year. Then, if you're incredibly lucky (think 95th-percentile lucky), you'll get a stellar paper that will set you up for a post-doc in a superstar lab, which will give you a roughly 50/50 shot at a tenure track position somewhere (don't count on living in a city, or even a place where your significant other can find a job, however, because you're now living at the whims of the academic system.)

Your post-doc will take 3-4 years, and will pay you less than you could have made right out of an undergraduate CS program, in exchange for more risk and longer hours. You'll be expected to work nights and weekends, and in case you lack the drive to do it, there will be some guy from China with a J-1 visa sitting next to you. He's probably living in a boarding house right next to the university with ten other post-docs, and he's willing to work 100-hour weeks for a shot at a job in this country. That's your baseline.

If you're astronomically lucky, you'll get a faculty position -- hopefully not at Podunk U -- where you'll be paid significantly less than that undergrad CS major (who is now probably making over $100k/year, buying a home, getting married, etc.) You'll be competing for grant money in an insanely tight market (the funding rate for NIH research grants is well below 5% now), and evaluated by established faculty who will torpedo your proposals if it helps their own chances. At the end of six years of insane work, you'll get a shot at keeping your job. If you get tenure, you can settle down to a lifetime of below-market wages, while working relaxing 50-60 hour weeks.

Of course, if you choose to leave academia after grad school, the prospects are equally dismal. The rare position that requires research experience is essentially set aside for friends (you hear a lot about "networking" on the science job boards, but little practical advice on how to actually do it), or for people who have been poached from other companies by recruiters. Meanwhile, once you have a PhD, you're untouchable by most employers -- considered too theoretical and expensive for "practical" work. Ultimately, most people with advanced degrees in the sciences spend years teaching courses on contract, or jumping between dead-end, low-paying jobs, hoping to start something that resembles a career.

I'll start by saying I'm a weird guy.

A long time ago I realized that people mean different things when they say 'priority'. If you only mean the 'value' of a certain task, then that's not a good way to prioritize, IMHO.

I've changed my model to prioritize strictly according to return on investment. I.e., how much value I or the company receives for unit of work.

In my professional project management and in my company, here's the algorithm that I pretty much use for every sort of task prioritization:

(1) I put together a list of items

(2) I put a relative cost (RC or C) associated with each item-- for a task list this tends just to be the hours you predict you'll spend.

(3) I hide those costs and then add some number that represents the relative business value (RBV or BV) of each item. (More on this in a second)

(4) I unhide things and then put another column that just calculates RBV/RC which indicates the return on investment (ROI) for each task.

(5) I then sort it all by ROI and work my way down the list in ROI priority order, always working on the tasks that offer the most ROI, I adjust values and costs (and re-sort) as my needs change, work completes, and as my understanding of each task changes.

The units used to value each assigned task is not really important. It's only important that tasks have a value that makes sense relative to each other.

For example, if I have these tasks:

  * Setup tech support email account
  * Improve usability for site logon page
  * Write a blog article about our recent features

I might then give these costs:

     01 hour  - Write a blog article about our recent features
     01 hour  - Setup tech support email account
     16 hours - Improve usability for site logon page

Having a tech support email account, I know that's important and I must have it, so it gets a high value. In this case, I'd say "Improving usability" is something we could survive without, but I firmly believe it could increase our revenue.

I might then give these relative business values (I'll just say points):

      200 pts - Write a blog article about our recent features
    10000 pts - Setup tech support email account
     5000 pts - Improve usability for site logon page

When I calculate the ROI and sort them, I get this list that I work from top to bottom:

    10000 pts/h - Setup tech support email account
      313 pts/h - Improve usability for site logon page
      200 pts/h - Write a blog article about our recent features

As long as when I add new tasks, I evaluate them against the other values and costs to ensure they're all relatively correct, the list always sorts to provide the tasks with the 'biggest bang for the buck' at the top.

Nice.

I'm going to file a patent for putting my arms in the air and waving them like I just don't care.

Philip Greenspun had a great article about this as well: http://philip.greenspun.com/careers/women-in-science

Your objection here doesn't make any sense. Of course people could be spending more time doing work and less time on news.yc. But asking for stats isn't any better or worse than any other use of this site.

Obviously this site isn't a community to you, but it is to some people. It's also entertainment. I'd rather have stats on this website than watch whatever is on network television right now.

There's nothing statistically odd about the voting on it.

Why not read Dive into Python -- it's excellent -- and then learn about the new stuff in 2.5 later. The new stuff gives minor efficiency improvements, but Dive into Python is plenty good.

http://docs.python.org/whatsnew/whatsnew25.html

Don't be misled by the promise of freedom in academia. It's not like that at all.

Remember that some labs are more dysfunctional than others. Yours sounds pretty bad. My own experience at the same big crimson-colored university was considerably less bureaucratic -- we lost only about half a day per week to meetings, although there was still plenty of paper to be shuffled, between the grants and the articles and the manuscripts and the review manuscripts and the insane procurement process. And morale was rather higher, though perhaps not an order of magnitude higher.

The "wasting time on the Internet" factor should not be underestimated. Remember, the only reason we're all here is that Tim Berners-Lee spent a lot of his time fiddling around with the Internet instead of doing his physics research.