Me personally, after deciding not to pursue a Masters degree in Bioinformatics, I realized that working in IT is also a (more lucrative but just as empty) sham. I've been focusing my time for the past year on learning new computational modeling on side projects, such as 1) contributing to QuantLib, open-source finance library with new option volatility surface curves, 2) parsing through PLoS Computational Biology papers and feeding any supplementary data from authors/research group to visualizations/statistics libraries and open lab notebooks wiki's; and verifying whether their assertions are truly statistically significant.

As the author noted, it is very hard to do the real research in academia unless you have a union-card of PhD. However working in industry even R&D, unless you have a PhD or are very lucky gets you most of the suckered into "technician" and mundane CRUD work. Not to mention the financial realities of having a family and setting down later in life vs. the idealistic dream of monastic academic research when you're younger.

What have you guys done to balance the two? Do you work on side projects while collecting the paycheck? Or do you work in R&D division or a research institute that allows you to take on novel research work? Or do you finance your research on your own or solicit grants/funding from other people (like David E. Shaw, Kickstarter or a "Hackerspace" that survives on membership fees)?

The problem is you can't rely on a "code for science" campaign. A research study isn't something done in a weekend Hackathon, though they are occasionally helpful. What happens if, 2 years into your 5 year study, your helpful volunteers, leaving you with an incomplete code base beyond your skills to maintain or extend?

The first is to have scientists break their problems down into chunks that can be performed by volunteers but which aren't completely beyond the ability of the scientist to manage the resultant code. This is doable for much of physics and computational biology, less so where a scientist isn't a programmer themselves. We're taking this approach with http://solvers.io.

The second is to have the scientists mentored by programmers to help them become better at it. This is the approach being taken by http://interdisciplinaryprogramming.com.

In both cases, any particular volunteer dropping out is probably not a massive blow. If a project is going to rely on a particular programmer long-term, they probably need to find the funding to pay them.

It doesn't seem mostly billed as "escaping" or "rebelling", though. Just, some people find different careers more attractive. Some people would hate some of the bullshit involved in academia but find consulting attractive; other people would hate some of the bullshit involved in consulting but find an academic job attractive; and other people do something else entirely, like working at Electronic Arts. People end choosing a pretty wide range of different careers, all with tradeoffs. Some people choose more than one! If anything, kind of amusingly, the narrative is a bit more frequent in the other direction: people who had a senior job at a big game company and "rebelled" or "escaped" by quitting the six-figure job and going back to school for a PhD. For example, the AI lead on No One Lives Forever 2 and F.E.A.R. left the AAA game industry to get a PhD... and now is leaving academia again to go back into the game industry, but as an indie (http://web.media.mit.edu/~jorkin/).

I get the impression a lot of applied CS has those kinds of dynamics. If you go to a systems, graphics, data-mining, etc. conference, there's a good mix of big-company, freelance, and academic people, and a number of people who've worn more than one of those hats.

I think the bio field is desperate for people with software skills and it is actually pretty easy to get into if your willing to take a pay cut vs industry software rates.

On the other hand, I was getting recruited by a machine learning company based on my open source contributions etc but interest dropped off when they found out I didn't have a PHD (and wouldn't move to the bay area).

I think the reality of bio research is that it does involve a ton of mundane work and that even when working on a novel project we spend a lot of time doing server admin, cleaning, processing, reformatting data, building databases and data portals etc. Every time the scale of a study increases one of our tools breaks and getting things to scale often involves more hacking then pure research.

Occasionally one of us engineers come up with a novel approach worth publishing and more often we make a contribution to a larger study that is novel biology even if it isn't novel analytically.

I would contrast this with, say, machine learning researchers chasing percentage points on well established data sets like MINST or even doing kaggle competitions. Our data tends to be less settled more noisy, heterogenous, missing etc and have questions that are less well posed (eg often one disease is actually many with similar symptoms) so there is a lot more mundane wading through things.

I'm not sure what my prospects are if/when I decide to change jobs but I'm hoping that my open source contributions and papers would convince an employer that I know what I'm doing enough to continue working on novel problems.

If it's both, someone at the top is very out of touch.

So for a code monkey to come in and tap away on his stupid keyboard to make like $75K is a travesty as far as the research academia is concerned.

But in research, you're better than the sell-out's trying to make people click on ads and shit though. So part of your paycheck every week is padded with tokens of self-righteousness and moral superiority that you can redeem in times of needed philosophical consolations.

Beyond that, good programmers are stupidly helpful, but not mission-critical.

Funding seems pretty impossible if you're unaffiliated, though.

In CS (I am unfamiliar with other areas), I'll agree that the really big grants usually go to academic institutions, big defense contractors, or consortia of the two. But there are pretty decent funds set aside specifically for small businesses, using funds that Congress has earmarked to the National Science Foundation exclusively for such a purpose. Last I saw, the success rate for applying for such funds (in terms of % of applications successfully funded) was actually higher than for academic applicants, though the total awards are smaller.

You do have to convince a funder that your independent research organization is serious and capable of delivering research. But if you can do so, in the U.S. there are two NSF programs specifically targeting research money towards small businesses. The first is the Small Business Technology Transfer Program (STTP). This requires two organizations, with a small business and an academic institution submitting a joint proposal. They propose a plan for taking current academic results and turning them into viable products that will support a small business. The idea is to give money that will enable the academia-industry barrier to be crossed, with one partner on each side who explains why they are a good team for making the crossing happen. The second is the Small Business Innovation Research (SBIR) program, which small business can apply solo to. This funds activities that take place wholly in the private sector, but present a credible research plan that the evaluators consider to have a high likelihood of producing scientifically interesting results.

In Boston, we're looking to revitalize DIY bio at BOSSlab http://bosslab.org/

But it still happens, albeit at the margins. I have been working myself as a scientist in the academy for the last twenty years and even held assistant professorship positions in prestigious universities in Germany for almost ten years without a PhD and without much publications. In my case, that was most of the time due to a combination of factors: 1) the need for an outsider in the lab (particularly to avoid conflicts over scarce tenured professorship positions) 2) being able to teach and research topics for which more than one person would have been needed otherwise 3) being (a little) known in the field, and known as eccentric but proficient at the job.

Funding is certainly an issue. You do need an academic affiliation (at least a formal one) to apply for grants. But I do not feel I have been less successful in securing funding from European and German research funds than colleagues with PhDs and habilitations and lots of publications. As soon as past projects were successfully completed, it has never been a big issue. The real problem is that in my field only fashionable and pointless projects are being funded lately.

As a consequence, I have come to carry my research almost completely independently. Coding and data analysis for private corporations and casual teaching at the university pay the bills. From time to time, I still rely on academic grants to fund field research. My wife and I work together and we have a very spartan way of life, dedicated to science and study.

Doing science at the margins of the academy implies its share of abnegation, is certainly viewed as bizarre by many but it happens. Although I do not complain, I won't recommend it either.

Academia suffocates you with its processes, and the tendency of it to zombify young academics to thinking that high abstraction is the only way to go in life is in itself horrible.

In the end, I'm happy doing what I do. Mathematics was a fun challenge, but I never viewed myself as just a mathematician - I have a deep thinking highly adaptable mind that is geared to solve problems, not just be a specialist.

It basically means that continental philosophy is my hobby. I try to keep up with 'real' academia through following certain people on Twitter, and submitting papers to conferences, reading things...

Whilst plugging away at my thesis I have gotten interested in data analysis, data mining, etc. and my default data set consists of PLOS articles. I blog about stuff I do here: http://georg.io

Industrial Research can be on stuff that will lead to products in the near future. I think you can get a lot of the same feel of academic research by working on things like international standards. I have been able to do this without even a bachelors degree.

I don't think that I would have believed this until I got into graduate school but it's really true. A PhD doesn't mean anything. If I told you that someone had a PhD, that wouldn't have told you anything else else about that person.

I would say that if we want to think in terms of "union cards", we should just scrap the PhD and pin "science ranks" to publication metrics, as the real scientific job market already does. After all, what we really need from a scientific union card isn't to tell us how good a scientist is (and it doesn't do that), it's just to give us some baseline for separating real scientists from crackpots and wannabes (of which there are far too many).

In a PhD you potentially have vast intellectual freedom to learn what you want whilst earning a (small) income, rather than being molded by a company.

I say potentially because whilst I've had a lot of freedom over the past 3.5 years, I can't say that this would be true of all institutions and all supervisors. If you get treated and worked like cheap disposable labour then maybe you won't get as much out of it.

Personally I think I have gained a lot of skills that are useful outside of academia (largely implemented in Python). This happened because I knew that I didn't want to pigeon hole myself into academia and made choices correspondingly (e.g. Python instead of matlab or idl).

I believe the opposite. Before entering grad school i was under this impression, but now at the tail end of my PhD, saying someone has a PhD tells me that they're motivated above everything else. You don't just 'get one' for going to classes and writing a few papers. It really pushes you to establish solid techniques and approaches to conduct meaningful research. More importantly, as many ideas fail before finding something that works, it's pushes the student to stay motivated.

You could read the literature and try to get far enough up to speed to publish entirely yourself, but I guarantee that you will miss many subtleties if you don't connect with folks in the field. Enough that you are face a lot of hurdles trying to pass your work through peer review. The idea of doing that alone seems twice as daunting as doing a PhD.

That said, I am neither teaching nor in academia (gov't at the moment). My retrospective might be a bit different if I was trying to elbow my way into tenure.

This translates to, "you need to learn to speak the correct dialect of bullshit to get into the club."

You would have gained just as much, except for the PhD certification.

I don't think you would need a PhD to do science. Journals never ask for your CV in a submission.

However you need it to get a job in science, because your employer does not know if you actually can do science. That's why you need certifications.

All that said, I think pretty poorly of physics academia now. In retrospect, it seems like a small, incestuous group of people consistently reminding themselves that they are the smartest people in the world and are working on only the most noble and difficult pursuits.

There are far easier ways to earn money in the long term than doing a PhD. A PhD gives you 4 years* of relative freedom to build yourself intellectually within some rough bounds (these bounds are dependent on your program and can be quite tight though). You also get to hang out on campus with other PhDs (ymmv!).

But, you could get similar freedom with even less bounds by working and saving hard for the next 4 years and then doing what you want. It depends what motivates you.

*depends where you are though. I'm UK.

Of course it's remotely possible that our society will reject the PhD due to rapidly rising educational costs, but I don't think that's going to happen.

A sizeable fraction of folks in Science/Engineering do not pay tuition for their PhDs, and receive a modest stipend for living expenses.

Academia does a breadth-first heuristic search on possible research, slowly converting the search space of potential ideas into published papers. If you want to work in the research system, you get slotted into a specialty and an education largely just according to what your grad-school and postdoc supervisors already work on. Hence why I'm calling it a breadth-first search: new scientists are almost literally additional nodes in a search tree.

The problem is the heuristic that governs where the tree is expanded (and how quickly): publication numbers and grant funding (which is determined by publication numbers). From the personal perspective there's also the sheer coincidence of which research fields and which advisers you've heard of at all when you finish your BSc or MSc and apply to your postgraduate research degree -- which is governed by grant funding and publication numbers.

Thing being... not only is a tree-shaped expansion structure generating untenable job markets, but the expansion heuristic in question doesn't really correspond to what we want out of scientific research. There are three main reasons to prioritize one research proposal over another: we think it will be technologically fruitful, we think it will be cheap or easy, and we think it will advance knowledge. In short: technology, convenience, and mystery. Grant funding and publication metrics, however, almost exclusively target convenience, with technological applicability coming in second-place and the fundamental scientific issue of filling in our ignorance about Nature stuck waaaay at the back of the bus.

There's nothing more I can say about, or add to this. Read it again instead.

  I look for interesting problems that I can solve. I
  don’t care whether they’re important or not, and so I’m 
  definitely not obsessed with solving some big mystery.

From his Wikipedia page http://en.wikipedia.org/wiki/Freeman_Dyson

His friend, the neurologist and author Oliver Sacks, said: "A favorite word of Freeman's about doing science and being creative is the word 'subversive'. He feels it's rather important not only to be not orthodox, but to be subversive, and he's done that all his life."

It's easy to see that things like video games, artificial life and fart "apps" are leaves and we shouldn't spend time working on them. It gets painful when we apply the rules to things we value more highly. Astronomy, particle physics, space flight, fusion power: these are all noble pursuits, at least the first two or three were branches in the past, by rights they should all be branches today. But they're not. They're leaves. That's the cold fact of the matter, and the world has to be dealt with as it is, not as it should be.

http://www.ias.edu/about/publications/ias-letter/articles/20...

Just numbers.