An interesting study by two Economics profs at Georgia State University detailing the coming glut of bioinformatics graduates and the future job market. Ah, for the days when universities were falling over each other to establish bioinformatics programs. Gotta have that new new thing!
Optimal Foraging in Bioinformaticians
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Who would have thought
"These training programs are now beginning to generate graduates. Many of these graduates assumed they would go to work in industry, yet positions in industry appear to be on the decline, and many of the positions that are available are for individuals with considerable experience. The strongest area of demand in recent years has been from academe, seeking faculty to staff new programs and to broaden research expertise. Unless conditions in industry change dramatically in the next few years, it is likely that many trainees from these programs will have difficulty finding jobs in industry."
At my institute here in Australia the first crop of pure bioinformatics graduates are due to finish their degrees this year. I was always amused that part of the degree required an industry placement for six weeks, umm, Australia doesn't have a bioinformatics industry, hello!
The problem here is the perception that Universities are for training future future bioinformatics drones to work in industry. When it should be about teaching creativity, critical thinking, inovation etc. which will then generate new industry...Wow. I'm amazed I'm not more jaded.
Anyway, a worthy post. Gmail invite is on its way.
Glut in Bioinformatics
The article really rings true. There has been an overinvestment in what was initially perceived to be an explosion in bioinformatics, but that which never occured at the pace expected. With computational mechanisms fast replacing regular tasks like genome analysis, annotation and database integration, there is less for the bog-standard new bioinformatics graduate to do in real life.
Most job applications from students in bioinformatics are all about the number of technologies (the more the merrier!) they are familiar with, and less about how they think they can apply this knowledge in real life, research and innovation situations.
Lets face it, bioinformatics as a word is an often abused term applied to anything and everything which remotely links computers with biology. Even making a couple of graphs analysing someone else's raw data could be construed to be bioinformatics !! It may sound obvious, but the trick is not in analysing data, but in interpreting the data in a novel and intelligent manner which can provide insights previously unexpected. A form of data mining perhaps ?
boiling down
The whole subject, for me, boils down to one thing: the inherent messiness of biology. There is a notion, unfortunately prevalent even in people who should know better, that biology is the new physics. In other words, we are looking for the underlying laws that will explain a major portion of the physical world in reasonably simple form.
Once this idea is embedded, the extrapolation to, for instance, genomics, becomes easy: generate a load of data, pass to geeks with computers, invent new maths, solve major problem, collect Nobel. There's only one small glitch: it's all bollocks.
The unwelcome, messy truth is that biology is the new biology: it doesn't have rules, but habits, and habits can be (and frequently are) broken [1]. Yes, you can analyse data, and that requires sophisticated mathematical and computational infrastructure, which is being worked on. Yes, brute force is useful in the short term. But the idea that one can be taught a set of routines which are universally applicable to computational biology is horse-manure. The sad fact is that if you have no understanding and/or intuition of the underlying biological principles you cannot address these problems, any more than a biologist can (or could) saunter into CERN and find the Higgs boson. Releasing a clutch of Java-talking web drones with itchy mouse fingers and no Bio* experience isn't going to help. And no, they won't get 150k to start. They won't even get 50k.
[1] Might even persuade Greg to give away one of those Gmail thingos to anyone who spots the paraphrase :-)
re: Glut in Bioinformatics
I thought the last paragraph of the above comment sums it up very nicely.
Bioinformatics (if you must use the word) is a research tool. To my mind, it has "pure" and "applied" aspects - those are not entirely appropriate words, but I mean them in the following way. A "pure" problem might be "I want to calculate the GC content of all bacterial genomes". In other words, I am looking for a simple (or maybe complex) mathematical description, which may or may not tell me something about biological reality (which genomes have low/high GC content? What do I know or can I infer about those genomes?) An applied problem might be "I want to predict which proteins in a genome are membrane proteins, model their extracellular loops and determine which could be binding targets for small ligands, e.g. drugs". Here, I might employ a whole suite of methods, but I'm doing it on the basis of a prior biologically-intuitive notion. I want to ask a biological question from the outset - that's what I mean by "applied", rather than in this case, the drugs aspect.
It seems to me that we are training a lot of bioinformatics students to deal with problems like the first, pure example and not many to think about how to solve the second. I think part of the reason for this is that a lot of the students come from computer science backgrounds and have got hold of the idea that bioinformatics is the road to a high-paid job, rather than being a sysadmin or website designer or whatever. My personal view has always been (1) that as a research tool, bioinformatics makes more sense as a Masters or PhD than an undergraduate subject and (2) that more biologists getting to grips with maths, stats and computing is far more important than and preferable to computer scientists idly wandering into biology in the hope of big bucks.
The question is, who is to blame for perpetuating this notion that there is even any such thing as a bioinformatics industry? Industry itself? Academics? Basically, anyone who is forced to bullshit in order to attract investment?
I can feel a socialist rant coming on, so I'll stop there.
Return of the double-major?
Most of these issues would be solved if these unrealistic career expectations were not put into the heads of naive middle class students (and/or their parents). I'm told that at one institution in this city, a rep for the Bioinformatics undergraduate program has been known to tell senior high school students (and undergraduates) that they can earn 150k in their first year out or that they can "name their price". Such ridculous nonsense borders on being professionally negligent.
My personal view is that most of these issues would be solved if a decent level of repsect was again placed in a plain old science degree, perhaps with something radical added like a double major in biology and mathematics (ye gods!). I do seem to recall that the University I work for had a very flexible double major system in place a few years back -- I haven't checked whether it's still in place, but presumably has been replaced because it's not marketable enough (read: attractive to middle-class, private-school-paying parents who've actively tried to talk their offspring out of studyng anything other than business studies, medicine, law or something "useful", e.g. tourist studies), and is percieved as being too boring.
Who would have thought
Yeah, yeah. But there are quite a few tiny start-ups who'd employ a few grads if they could just get seed funding...:-)
This week's song: "We wouldn't be asking for money if we'd already done it..."
Incidentally, you can't teach creativity. You can foster, encourage and generally support it - or crush it if you're so inclined - but teaching it is a big ask.