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Supply and demand in the knowledge market


It should come as no surprise that by increasing the supply of graduate students (and in turn post-doctoral fellows), we have arranged to produce more knowledge workers than we can employ, creating a labor-excess economy that keeps labor costs down and productivity high (How much is a scientist worth?) – but is this what we want? While advantageous in the short-term, there is little room for additional gains and a more efficient and productive system will need to be created if we wish to actualize research-based economic growth.

Federal investment in the knowledge sector is better spent creating new employment pipelines to redistribute a highly-educated labor market rather than worsening the blockage. The imagery of a bottleneck is fitting, and something needs to give. Compared to their peers in engineering, law, medicine or business administration, post-doctoral fellows languish at the bottom of the salary scale. In North America, typical post-doctoral salaries begin at $38,000/year and cap out at ~$50,000/year. While most researchers commence post-doctoral fellowships at 27, the 20% that obtain their first faculty position do so, on average, at 42 years of age. At an average 50* hours per week (*Nearly one third of PhD biological scientists put in 60 or more hours per week; Careers and Rewards in Bio Sciences: the disconnect between scientific progress and career progression), this amounts to roughly $14.50 an hour.

Author’s note: Against my better judgment I could not help but do the calculation for myself – after 4 years in the Honours Bachelors of Science program at McMaster University, 4 years in the PhD program at the University of British Columbia, and nearly 4 years as a postdoctoral research fellow at Harvard Medical School, I now earn $12.58 an hour – less than I did in highschool!

By comparison, physicians enter private practice at 29, lawyers at 25, and earn $70,000+ (How much is a scientist worth?). Within the basic sciences, academic salaries average 40% lower than in industry, and are also subject to the steepest rises at every career stage among all of these professions (For Love and Money). Not surprisingly, the largest jump is from the post-doctoral to assistant professor level where top-level science positions are in the $100,000-$160,000/year range. Salaries in academia, while insulting, are not the most pressing concern – burnout is, and I’ll discuss it in my next post.

Jonathan Thon
Dr. Thon is the CEO and chief scientific officer of Platelet BioGenesis, and a faculty member in the hematology division at Brigham and Women’s Hospital, and Harvard Medical School in Boston.
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  1. amin amershi / October 24, 2012 at 23:04

    I am now a retired chaired prof. from a leading business school and have had 35 year career at top business schools since my Ph.D. in 1979. My story and decisions about my career will be helpful to many young bright science post-docs.

    I am by training, passion and craving a mathematician, physicist, and overall science and technology enthusiast, often near “freak” proportions. Yet by career I was a professor of accounting, by research into mathematical finance, “information economics”- bayesian decision and game theory adapted to economic issues and problems – and auditing. If you can wrap your mind around this concoction, let me tell you it was by choice when facing in 1975 a similar situation to what young scientists are facing today.

    At that time I was pursuing a doctorate in operations research,which itself was career shift from mathematics and quantum physics, my undergraduate passion and training. Why? Because there were few or no scholarships in 1972 to pursue a career in quantum physics at a top schools in North America and the competition was fierce. Furthermore, at the time, North American academics were quite ignorant about Non-West European universities and looked askance at people like me, even though my degree in mathematics was validated by the Imperial College of Science in London. So I had to achieve top results in both GRE Aptitude and GRE Advanced Math. tests. Even with that, admission with scholarships into operations research departments at business schools were far easier to get and more generous than in math or physics because of NASA winding down the space program.

    Yet I had done enough survival research at the rather young age of 24 about North american Academic culture to understand that admission into one faculty need not restrict pursuing interests in other faculties, and that funding depended largely on individual professors likes and dislikes than on fields of study. So, then I ended up pursuing OR for nearly 4 years and to my surprise even liked it a lot. I had almost completed a doctorate in stochastic optimization when my supervisor told me that job prospects in academia in OR were bleak. At the time I had worked with two accounting profs as a research assistant. They had had good training in bayesian decision theory and “information economics”, the new hot field in accounting research, finance and economics on the west coast all over North America. Plus they were the leading and founding academics in this new area. They suggested that I should seriously consider accounting academia as a career. Finance, which was already quite mathematical at that time, was more attractive to me and some of my OR colleagues, and almost nobody I knew among my Ph.D colleagues thought of accounting as a career chioce.

    My own and almost everybody else’s impression was that there could be no more boring and clerical field than endlessly noting down debits and credits in journals every day. I had seen my father do it; my brother had told me never to go near accounting unless I wanted to commit suicide by ennui. So I told the two profs, who were to become very good friends and mentors in my academic life, that I had no clue about debits and credits and had no interest in spending the rest of my life teaching the stuff, even if I had starve in math intensive fields. They told me that I had an incorrect impression of accounting from old British pedants and Dickensian foggies like Mr Micawber; that the then current accounting research was all information economics and my training in stochastics and decision theory would be a fantastic advantage. The field was virgin territory and almost no person with my math training was in the academic pipeline. For teaching accounting, I would have to learn the structure of double entry book-keeping, but that would be trivial for me to do it by self study since the basic technical pricinciples of inflow-outflow balance were invented by a 14th century mathematician named Lucca Pacioli and had hardly changed since. Acounting per se required study of the legal aspects of what is admissible as income and expense, asset and liablity and owners’ equity. But this was like game theory and optimization since the idea was to minimize taxes and maximize profits legally. Auditing was a forensic game much like detective work using statistical tools. So I thought maybe I should take a look at this stuff now that they had put it this way.

    From that moment till now, I have never looked back and regretted my chice of career. It took me 3 years of additional study after 1975 to master accounting and its problems to earn a Ph.D. in the information economics of accounting. However, the atmosphere in accounting research was most generous and liberal so that I was able to pursue mathematical finance, especially the information economics of financial markets, and the information economics of incentive structures and risk-sharing among different classes of stakeholders in a business enterprise. Employees are major stake-holders and not machines to be abused and moved around. That mentality still prevails among many business leaders, but it has nothing to do with the proverbial bottom line. On the latter, I know whereoff I am talking about. Most pundits and politically vocal business leaders have no clue about money flows in any organization. They hold forth only because they have money and power, not from knowledge. Coming into a lot of money is largely a matter of luck and not a matter of being smarter and wiser than everybody else. I know this impression enters into the ego of quite a few people who get intoxicated by money and power. This type of strutting by people on ego trips ought not to discourage young scientists from considering business as something evil and foul.

    At any rate, I never lost my knowledge of and passion for math, physics and science, but added to that, with liberal doses of math logic, philosophy, human sciences and much more broad minded view of how human societies function. At the same time I was in a financially stable and rewarding career. It is true that one may not find almost anyone to talk to among colleagues at business schools or such places about one’s scientific passions. I learnt from experience and also my own research in eceonomics that “eyes rolling over” by narrow minded academics in business schools at the mere mention of quantum physics is a defensive reaction to hide ignorance and fear, and not a signal that the knowledge has no economic value. It is their loss for having no understanding of major technologies. They can never spot business opportunities provided by fundamental science research.

    So my advice to young scientists is to be more flexible in their career choices and consisder application of their knowledge to pressing problems in human life, not in a broad and banal manner but in a very creative and sophisticated way. It is a great thinking challenge to take what you have learnt and apply it, with addition of other requisite knowledge, to problems in the field that the markets are willing to reward. There is no need to sacrifice ethical principles and beliefs to fatten botom lines. All of that punditocrap is simply that by ill-trained journalists and know-nothing op-ed armchair literati. In real life even an ordinary kitchen provides innumerable opportuinities for creative minds to think up processes and products that have economic value. But one has to learn the art of presenting ideas to people (including governments) with money and to learn what risks they face if they were to put their money into your ideas. You will meet immense and frustrating bureaucratic thinking from top to bottom. A frontal attck will never work with bureaucratic mind-sets. Finessing these mindsets is both an art and science that one has to pick-up like survival skills. A sense of entitlement is deadly for both creativity and survival.

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