有人在思想家公社群里贴出这个博文http://mariobarbatti.wordpress.com/2013/12/15/is-there-a-fair-future-for-computational-theoretical-chemistry/（需翻墙），博文标题为Is there a fair future for computational theoretical chemistry?。我看了一下，感觉很多地方写得很在理。我特别推荐打算要读计算化学的研究生看看，没准儿会对他们的前途有很大影响。对这个问题我也一直有很多看法，不吐不快，于是在这里就说说。这个博文我贴在文末了，其中两个比较值得一看的回复也给出了。
Is there a fair future for computational theoretical chemistry?
Computational theoretical chemistry is amazing, but it is a career dead-end. Today, hordes of grad students are in the field doing technical work with little scientific innovation. They will earn a doctor title and then move to a completely different field. The system needs them to keep up to the high-production demands, but is it fair? Maybe the future of CompChem is in outsourcing.
I am a professional in computational theoretical chemistry (although my background is in physics). Many people have never heard of this field, which consists of investigating chemical processes through computational simulations; and developing methods and computer programs to do such simulations.
Maybe the field will become a bit more sexy now that the Nobel Prize in Chemistry 2013 was awarded to three scientists in it. But for the chemistry community, computational theoretical chemistry, with its branches into fields as far apart as molecular biology and material sciences, has been part of the scientific routine for decades.
(Just for curiosity, a couple of illustrious names who once contributed to the field are Peter ‘Boson’ Higgs and – serious – the German chancellor Angela Merkel.)
There is an elephant in the room, anybody wants to talk about it
The problem with computational theoretical chemistry is that it is a career dead-end. After earning a doctorate in the field, the young researcher will find out that the job market is saturated. If he is clever enough, he will quickly move to a completely different area (like Merkel did), otherwise he risks haunting chemistry departments for years, jumping between precarious temporary contracts.
The reason the job market is so bad is a basic population ecology problem: too many people for too little resources. Any research group to survive must recruit hordes of graduate students to produce loads of scientific papers. This is just normal in hard sciences, and it is not generally a problem for most of chemistry fields because industry will absorb those young professionals. The particular problem with theoretical computational chemistry is that positions out of the academy are rare, creating a great surplus of people with a useless doctorate title.
From a cold population analysis, every established professor should be educating in average not more than the number of professionals that the job market will be able to absorb. In a field like catalysis, where professionals are largely required by industry, this may allow a professor to award few doctorates a year. In a field like computational theoretical chemistry, however, this may allow to award only a few doctorate titles during the whole professor’s career.
Right now, the situation edges the ridiculous: professors in the field often have half-dozen simultaneous students. I have colleagues who, even without tenure, have already few doctorate students. (And in a couple of years they will be competing with their pupils for a position!)
There is nothing that those senior researchers can do, as they need the students to keep the projects running, but I cannot avoid asking: Is it fair to let students specialize for years in a field that they will most probably have to completely abandon? Is it the better use of scholarship resources investing them in people who will not act in the field?
My two cents to move the elephant out
Research on computational theoretical chemistry should be deeply reformulated.
First of all, the number of graduate students in theoretical computational chemistry needs to be strongly reduced. To compensate the shortage of people, most activities in computational theoretical chemistry should be outsourced to technical departments and companies.
Much of the work in the field are technical and routine activities. If the research group needs simulations of the thermochemistry or a benchmark of vertical excitations for a new compound, this could be perfectly done by a technical staff. This data should be requested to a technical department in the same way we request NMR measurements.
If the group needs maintenance of their computer cluster, they should call the local IT department or have budget prediction to hire a company to do the service.
If the group needs to compute a property that standard commercial softwares can still not provide, their budget should allow to call their favorite CompChem company and hire them to implement it. In fact, if the group is developing a robust software in the field, it should be stimulated to spin-off from academy, as Gaussian or Turbomole successfully did.
Right now, armies of graduate students are buried into doing DFT, MD, CC, CI, MP2 simulations (make up a random acronym, probably it is already in use), writing codes, administrating computer systems. They think they are doing science. No, they are doing technical well-stablished routine work with little scientific innovation. The science happens afterwards, when those data flowing out of the computers clusters are taken, analysed and used to model reactions, discover new processes and understand nature.
Outsourcing is the key for a fair future for computational theoretical chemistry, where professionals have real working contracts and career perspectives; where studentship fundings are not wasted to educate people who will ending up working on a completely disconnected field.
Gregg says: May 1, 2014 at 6:47 am
I think this article is very very true. I was active in this field since early nineties and have gone through a number of temporary contracts that forced me to drag my family through various places around the world.
Dear readers, please be warned that commercial spin-off can also prove to be a career trap, as it happened in my case: the company, after investing many-million funding into combined, experimental and theoretical study, filed for bankruptcy before concluding the research, the management drove off with their brand-new Porsches and I, among other former employees, was left with the feeling of disgust and yet another gap in my CV. I then tried REALLY hard to change my career track. My goal is a career in IT, but it is not as easy as some people might think. Contrary to computational chemistry, job interviews tend to be hard, and you are always confronted with the questions like ‘are you going to go back to the academia?’ or ‘all the time you did this computation stuff, why this sudden career change?
I’m not writing this to discourage people to try their luck in spin-offs or start-ups, but just want to stress that this path has been walked before, and it is precarious one, too. Computational chemists, especially after turning 40, need stability (they are normal people after all!), and my opinion is that choosing to change one’s career path at a more ‘advanced’ age will most probably be final and decisive for the rest of the professional life. It might be better to look for opportunities where there are more jobs overall, but more applicants. Today’s science is governed by economy, global financial factors are influencing country’s state budgets. And pure research is financed from taxpayer money. On the other hand, investors, whether business angels, venture capital, or banks, have skilled analysts who will no doubt determine if there is market for computational chemistry services, before deciding on the funding (and this is this very funding which is going to pay your rent or electricity bills or your kids’ school). I’ve faced investors before and believe me, it is not an easy task to convince them your research is going to bring revenue, and they don’t care about the Schrodinger equation!
I think one has to stay realistic, but some optimism will not hurt. Fingers crossed for all the hard working computational chemists.
F says: July 9, 2014 at 1:05 pm
How I wish I’d read this article six years ago, before writing three theses (B. Sc., M. Sc., Ph. D., where I come from) in Computational Chemistry. The future really does look bleak for our kind.
I have literally lost count of the number of cover letters and CV’s I have sent out. First I tried to look for placement in my own field (Computational Materials Chemistry), regardless of whether a position was being advertised or not. I wasn’t picky: Europe, USA, Canada, world class institutions like MIT and Oxford and obscure little Universities in towns I’d never even heard of, as long as they did something vaguely similar to what I’d been working on, they were all fair game. Many never even bothered to reply, some were kind enough to let me know that they had no vacancies, one even shortlisted me for an interview, but competition was stiff and I didn’t pass. After a while I became discouraged, and as my Ph.D. approached its conclusion and the prospect of unemployment drew nearer, I started sending out applications to any company that happened to be looking for a chemist: I tried many different fields, including but not limited to oil, renewable energies, paper, paint, cosmetics, food. No one showed the slightest bit of interest: understandably, they were only looking for people with lab-experience, preferably in their specific sector.
Eventually, after reading through the 1000th-or-so job posting list, I took the hint and realized that pharmaceutical companies are practically the only ones outside of Academia that hire people with a background similar to my own (more or less). So when one slow Sunday afternoon I saw a position being advertised for MD modelling of proteins at a respectable University I applied right away: I was interviewed less than two weeks later and I was able to land a three year contract.
Which is nice, all things considered, but I still have the distinct feeling that I have only postponed the problem: by making myself marketable to Big Pharma, my chances at finding a job have increased slightly, but what if they don’t take me? I guess what really scares me is that in this career there doesn’t seem to be room for any Plan Bs: if worse comes to worst, experimental chemists can always swallow their pride and recycle themselves as lab technicians, scrubbing beakers and running tests on the local product to make sure it meets the quality standards. Computational chemists don’t have that option: unless you manage to become a professor or a researcher at a big company, you (and your spouse and children) are doomed to a nomadic life of one-to-three year post doc contracts at different cities, countries, even continents, unable to make any sort of long term planning and with the fear of unemployment constantly looming over your life. Like Gregg, I have also considered the IT path, but so far I only know Python, and then, I’ve never coded anything longer than a few hundred lines. I was thinking of taking programming classes and maybe pick up another language, but after reading Gregg’s post, I’m not so sure it would be worth the effort any more.
I wish I’d not had to learn all this the hard way. Science is my vocation in life and even if I could go back, I would still choose to be a scientist and take a Ph.D. But if someone had warned me, I would have taken a different route and opted for something perhaps not as intellectually titillating as DFT or CASSCF, but with more career options and a better chance to provide some stability for my family. I never expected to become rich working in Science, but this feels downright unfair.
I also wish someone had told me this: “They think they are doing science. No, they are doing technical well-stablished routine work with little scientific innovation”. That pretty much sums up the entirety of my Ph.D. work. And now that I have finished writing this comment, I feel even more robbed.