亂談計算化學領域的研究生就業問題
有人在思想家公社群里貼出這個博文http://mariobarbatti.wordpress.com/2013/12/15/is-there-a-fair-future-for-computational-theoretical-chemistry/（需翻墻），博文標題為Is there a fair future for computational theoretical chemistry?。我看了一下，感覺很多地方寫得很在理。我特別推薦打算要讀計算化學的研究生看看，沒準兒會對他們的前途有很大影響。對這個問題我也一直有很多看法，不吐不快，于是在這里就說說。這個博文我貼在文末了，其中兩個比較值得一看的回復也給出了。
計算化學學完了能干嘛，畢業后能有什么出路，這是很多很多年前就經常被人提起到問題。目前來看，出路實在是太窄了。很就很久以前形勢還算比較好，計算化學博士出來往往能找個還不錯的青椒或助研崗位，繼續搞研究，日子也過得安穩。但隨著空位越來越稀缺，接近飽和，如今幾年，進像樣的高校的難度呈指數型增加，對于絕大多數搞計算的研究生來說（非常牛或Boss話語權很大者除外）這條路幾乎快被封死了，留下的縫隙越來越窄。經常提到制藥公司會招搞計算的人設計藥物，有些計算化學軟件代理公司或者計算中心會招這些人當工程師和客服，一些領域內的期刊會招編輯等等，但最終得到這些機會的人終究也只是很少數，大部分畢業了之后都是轉行，干一些和計算化學幾乎沒有任何關系的行當，自身優勢在求職中得不到利用，知識很快被荒廢，是極度可惜也令人遺憾的，是計算化學界的悲哀。看了這篇博文，特別是最后F的回復，會感到這種現狀，無論是國內還是國外，是相當殘酷的。
我想告訴學化學的本科生的是，如果對計算化學沒有興趣，讀研只是為了增加就業的砝碼的話，絕對不要稀里糊涂地選計算化學當研究生的研究方向，有機、分析、材料等，什么都比這有前途。研究生不慎誤選了計算化學也罷，如果還要讀個計算化學博士，以為這樣會使自己在從業上更有優勢，那就大錯特錯了，這只會越陷越深，到最后發現悔之已晚。讀個其它出路好的方向的博士，或者有好的機會的話去就業或創業，都是比這好得多的選擇。
對于那些已經不慎誤選了計算化學專業的人，也不要過早氣餒，強烈建議多寫寫程序，一方面會使得研究工作效率高很多、增加研究深度。而且把編程練好了，出路會廣闊得多。編程絕對沒有很多人想象中的困難。而諸如那些博士幾年當中只是一直沒完沒了地拿Gaussian找過渡態的人，我認為這人生中最寶貴的幾年很大程度都被荒廢了，沒賺什么錢，枯燥地干了幾年，弄了個如今一點也不稀罕的文憑，沒學什么對自己有價值的知識，攢的經驗在未來一點用也沒有，還不如其它專業的碩士甚至本科吃香。
計算化學工作者的出路得自己去找，不要墨守成規，隨波逐流，要早點結合自己的情況思考自己的未來。“不在沉默中爆發，就在沉默中滅亡”，這句話其實挺大程度上也挺適用于計算化學工作者的，要敢于折騰和冒險。而那些還沒踏進計算化學領域的學生，就更要謹慎選擇上不上這條船。如果你不愁生計問題，又喜歡計算化學，那么歡迎上船。如果養家糊口還是問題，在這方面又沒才華又沒興趣，那算了吧。
目前計算化學領域的現狀就是上述這樣，雖然計算化學本身的特點在很大程度上導致了這種就業局面，但也不完全是計算化學本身的問題，在一定程度上也是因為計算化學實用化、市場化程度不夠所致。如果適當地耕耘和開拓計算化學領域，著眼于解決這些問題，還是有可能有較大發展前景的。一方面使計算化學產生更大實際價值，而不是沒事找事瞎算，另一方面也解決畢業生的出路，是互惠互利的大好事。在博文中作者也提供了一些思路，和我的想法也有類似之處。雖然國內也有很多軟件代理公司，也算某種程度上開發了計算化學市場，但我認為他們只做了很小一部分，而且也往往太功利了，動機不對。
不過這決不代表計算化學在科研領域沒有獨立的地位，而只能依附于實驗工作。純理論、方法的研究的意義依然重大，但有機會、有才能專門從事這方面研究的終究只是極少數，不適合干這方面的人不要去做這些，否則弄得身心俱疲也出不了什么成果。
上面提到的經營方式，某種程度上將計算化學變成了一項工作來做。實際上，即便不這樣經營，如今的高校、研究所里的多數計算化學工作者實際上也是將科研當成工作來對待而已。科研本身是應該憑借興趣而為之的，因此這樣的現狀是比較可悲的。不過，大多計算化學出身的人想把研究當成日常工作來做尚且沒機會，如果能給他們提供這樣的機會，用自己積累的知識和經驗來獲得相應的回報，換來安穩幸福的人生，必定是件好事。
我上面都是對那些想通過計算化學謀求生計的人說的，并不適合那些對計算化學或自然科學極度熱忱，一心想做研究，以探尋真理和求知為最大樂趣，甚至為此不惜與世界為敵的人。這些人只要能有合適的機遇，肯定能做出很好的成就，造福于人類。但是，現狀還是和前文提到的那樣殘酷，想繼續搞科研卻很難找到合適的職位。哪怕進了高校、研究所，但總是會被亂七八糟的事纏身，諸如講課、應付考核、申請基金、處理人際關系等等，弄得難以專注。對于這些人，我如今十分建議搞一些其它的能夠賺錢的副業（甚至作為主業來對待），不會將所有時間占滿，或者只是占滿前幾年，由此獲得穩定的生活環境，保證科研能夠順利進行，然后用剩下的時間做自己喜歡的研究。這種做法屬于“民科”，但并不是如今貶義的那種低級民科，而是屬于所謂的“專業民科”，研究者是有專業知識背景的。在如今科研環境日趨惡化的情況下，我相信專業民科會逐漸成為一支充滿活力的新生力量（盡管必定很小眾），做出不亞于甚至遠勝于正統學術機構中所誕生的成果。肯定有人會說民科哪來的實驗條件什么的，其實這一點，正是計算化學所不用擔心的。只要不是跑那種計算量很大的任務（實際上，凡是需要拼計算量的研究，在我看來大多不會是什么會有深遠意義的研究），自家的計算機足夠用了。比如我就認識兩個退休的曾經從事科研的老先生（都是Multiwfn的用戶），他們都是退休后開始做計算化學，不花納稅人的一分錢，用自己的機子算，幾年內發表了不少有意義的優秀文章。至于我上面所說的副業，類型很多，比如投資金融產品、淘寶開店，或者利用自己的特長做自由撰稿人、開培訓什么的都可以。另外，假如以后真的把上面說的那種承接計算化學研究的服務市場做成熟，那么這些計算化學專業民科們做這方面也會十分適合，比如平均每天一半時間算別人的任務（畢竟也是自己的專長，總比干其它的工作明顯更有興趣和動力），一半時間搞自己的研究。
說來，曾經有個人碩士剛畢業的人，他思維很活躍，喜歡搞研究，考中科院博士沒考上，但是據說是有不錯創業的機會，問我怎么選擇好。我毅然決然地說，甭考那個博士，創業吧，少年！考上了博士有什么用？也就是給人家干活，自己的思路沒法充分施展。如果創業，賺了大錢，生活無憂，想研究什么研究什么，可以不受制約地盡情鉆研，還可以自己開個研究所當Boss，招一批人給自己干活，從不用看上級的臉色，人生豈不快哉？而博士讀完了，說不定最佳創業機會也喪失了，反倒可能以后沒什么發展了。其實我搞科研當初是十分鄙視錢的，即便到現在也認為“金錢=糞土”，不過在萬惡的三次元，錢是科研的物質基礎，所以靠副業或者做其它的主業來合理、合法、憑良心地斂財，和高尚的科研精神、科學家的至高理想是完全不沖突的。不過，切勿被金錢沖昏了頭腦，而最終忘掉了科學成了商人。錢賺到一定程度，達到無后顧之憂程度時，就應該把精力轉移回鐘愛的科研了。
總之，計算化學就業，是計算化學領域當下最大的問題之一，應該在業界予以廣泛的關注。建議在開各種計算化學大會的時候，也別總是討論那些有的沒的的主題，說一堆陳詞濫調，互相忽悠工作，真應該留下一些時間，讓那些在領域內已經很有影響力的專家教授、政府和相關企業人士，以及正身處求職或者在讀狀態的計算化學研究生們一起好好交流探討這個問題，這是影響計算化學領域未來發展的一件關鍵性的大事，這個問題已經日趨嚴峻，不能再被忽視了。
最后順便提還想說一下，我總看很多人抱怨這抱怨那。比如埋怨高校工資低，難以養活一家。這有什么好埋怨的，高校就是那樣，嫌待遇低，或者呆得不爽，那不去不就完了，非要圖個安穩，那就只能是這待遇；還有的埋怨世道不好，不尊重知識，好不容易讀了博士出來也找不到好工作。這在我來看也沒什么值得埋怨的，自己所掌握的計算化學知識在別人那里就是帶來不了什么經濟效益，人家不是慈善家，就是不需要這樣的人員，怪只能怪自己，當初沒做長遠打算，或者缺乏主見和判斷能力，而且自己又沒習得其它一技之長。
以上說的這些，語氣強硬，必定有些地方偏激，肯定會招致很多人不悅，所以標題是“亂談”。但不管怎么說，我希望看到此文的打算搞計算化學的本科生或者已經從事計算化學的研究生們，能盡早考慮自己的后路和未來，免得到時候像博文當中名叫F那個人一樣落魄。
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.
MB
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.