We recently published a new career review on becoming an academic researcher by Jess Whittlestone. It covers issues such as:

  • Entry requirements and what it takes to excel.
  • What are your chances of success?
  • How to maximise your impact within academia.
  • How to assess your personal fit at each stage of your career.
  • Which field are best to enter?
  • How to establish your career early on, and trade-off impact against career advancement.
  • Review of the pros and cons of the path.

Check out our career review of academic research →

Here are some extracts from the full profile.

Research isn’t the only way academics can have a large impact

When we think of academic careers, research is what first comes to mind, but academics have many other pathways to impact which are less often considered. Academics can also influence public opinion, advise policy-makers, or manage teams of other researchers to help them be more productive.

If any of these routes might turn out to be a good fit for you, then it makes the path even more attractive. We’ll sketch out some of these other paths:

1. Public outreach

Peter Singer’s career began in an ordinary enough way for a promising young academic, studying philosophy at Oxford University. But he soon started moving in a different direction from his peers, by seriously trying to change the views and behaviour of the general public on important moral issues.

Singer’s first book, Animal Liberation, is one of the most widely-read books published by any philosopher. Many consider the book to have given birth to the animal liberation movement.

Singer has also argued strongly that we have a moral obligation to donate much more to those living in poverty. His writings on global poverty inspired the creation of the organisation Giving What We Can, whose 3,000 members have donated over $10 million to the most cost-effective charities, and pledged over $1 billion of future donations1

Early-career economist Max Roser made a website clearly presenting data on how the world is changing that now gets over a million visits a month and earned him introductions to politicians and philanthropists, as well as a large Twitter following.

Other academics venture far outside of their original fields of research. Noam Chomsky managed to convert an academic position focussed on linguistics into being one of the most prominent commentators on US foreign policy.2

As we argue in the career guide, advocacy seems like a promising approach in general to have a large social impact. And academia seems to be an especially good position from which to advocate for important ideas. Successful academics have developed the expertise required to understand complex questions, and the credibility to have people listen to what they say.

This is especially true if you want to advocate for issues concerning extinction risks, because some of them are emerging from scientific and technological progress itself. We need experts in the relevant fields to shape public understanding — to prevent the risks and benefits from being overhyped, while helping people to understand genuine concerns with, and the real potential of, these technologies.

However, it’s important to be careful with public outreach – it wouldn’t be that difficult to do harm by spreading slightly the wrong idea, in slightly the wrong way, to slightly the wrong audience. For example, writing popular articles about threats from artificial intelligence might lead to widespread fear and alarm, which could be counterproductive.

This suggests that getting the biggest possible platform for your ideas might not be the best route to impactful outreach – sometimes targeting communication at smaller, more influential groups might be a better approach.

For instance, academic macroeconomists have a great deal to say about appropriate use of monetary or fiscal policy, and are regularly appointed to decision-making roles in central banks. But communicating their ideas to the general public is difficult and likely to result in misunderstanding. As a result macroeconomists more often write books and papers aimed at a limited audience with the goal of influencing politicians or bureaucrats within government or central banks themselves.

2. Apply your research to problems outside of academia

John Beddington was a successful academic biologist, but his biggest impact seems to have come through his service as a respected science advisor to the government.

Beddington was the UK Government’s Chief Scientific Adviser from 2008 to 2013, and played a key role in helping the government to navigate the challenges of the Fukushima nuclear disaster, eruptions of the Icelandic volcanoes, and ash dieback disease in the UK. He also pushed to establish a network of “Chief Scientists” across all government departments.

Often the people in charge of making important decisions — about how to allocate funding, or what the appropriate policy response to a given challenge is — won’t necessarily have expertise in the most relevant fields. This means they need to call on external experts who do have this specialist knowledge, who can help them to make the best possible decisions.

These experts are very often academics, since academia is one of the best ways for people to develop the credentials needed to be taken seriously by policymakers.

And a need for guidance from academics isn’t limited to government – you could do a lot of good if you have the relevant expertise to advise NGOs like the Gates Foundation or World Bank, or tech companies that have a large influence like Google or Amazon.

Policymakers in many countries often seek the advice of experts in some relevant fields such as economics, data science and machine learning, and some areas of social science such as behavioural science. That demand means it’s not necessarily as hard to end up in a position of advising decision-makers as you might think.

What are the main downsides?

Highly competitive and low chances of progression

As we mentioned earlier, academia is highly competitive:

  • A study by the U.S. Bureau of Labor Statistics found that in 2010, less than 15% of new Ph.D.’s in science, engineering, and health-related fields found tenure-track positions within 3 years after graduation. For Ph.D.’s in the life sciences, the figure was a grim 7.6%.
  • The NSF estimated that, in 2010, only 11% of PhDs in the biological sciences held tenure-track positions 3 to 5 years after graduation, down from 55% in 1973.3
  • One way to measure how competitive an academic field is to look at its “reproduction rate”: what is the mean number of new PhD students a typical faculty member will graduate during his or her career? This gives us an estimate of how many PhD graduates there are per faculty position. One study found that there is roughly one tenure‐track position in the US for every 6.3 PhD graduates in the biomedical sciences.4
  • Another looking at engineering finds that “a professor in the US graduates 7.8 new PhDs during his/her whole career on average … This implies that [barring growth in academic positions], only 12.8% of PhD graduates can attain academic positions.”5
  • The situation seems similar in other countries. For instance, in the UK, for example, only 3.5% of people with a science PhD make it to permanent research positions in academia and just 0.45% of STEM PhD holders in the UK become tenured professors (though note that the title “professor” is awarded much less often in the UK as in the US, as it is reserved for senior academic staff). Only around 20% end up in any sort of research roles.6

However, these figures vary a lot by institution – a 2015 study of 19,000 faculty members in business, computer science and history found that 25% of institutions produced 71-86% of all tenure-track faculty depending on the field.7 This means that if you’re able to do your PhD at one of the most elite universities, your chances of getting tenure will be substantially higher than 15%. (If we assume that all these universities produce the same number of PhD graduates, and that 15% on average get academic roles, then around 47% of graduates from the top 25% of universities would be successful but only 4% from the remaining universities. If the top 25% of institutions graduate twice as many students as the rest, then the figures move to 29% and 5%. This suggests your changes are 2-3x higher than the overall average at top institutions.)

Over the last 20 years, it has also become increasingly common to do one or more “postdocs” – temporary non-tenure-track research positions, normally lasting 1-3 years each – before getting a faculty appointment. According to the National Research Council’s report, “Bridges to Independence”, the share of recent PhDs in postdoc positions rose from 13 to 34 percent between 1972 and 2003.8 Scientists doing postdocs in the US spend an average of 3 years in this holding pattern and only about 17% ultimately land tenure‐track positions.9 A typical postdoctoral research associate salary is $45-55,000.

This seems to be a result of the fact that the number of PhD graduates has dramatically increased – in 1994, 7,800 people received doctorates in the life sciences in the US, whereas by 2014 there were 11,335 – while the number of tenure track and tenured professorship positions has stayed constant.

All of this comes after a large fraction of people who start PhDs fail to complete them. Between 41 and 78% of people who start PhDs have finished them after ten years, depending on their discipline. Computer and Information Science has among the lowest completion rates at (41%), Economics is in the middle (52%) and life sciences fairly high (63%).10 Though note completion rates are better among the most prestigious institutions.

What does it take to excel?

Track record

The best predictor of success in academia, as in many fields, will be your existing track record. If you have managed to publish respectable papers before or during your PhD, that is a great indicator that you could succeed in academia. Similarly, your ranking in your classes or the competitiveness of the graduate school you got into are leading indicators.

Below we will focus on other factors whose predictive value is not so obvious, and which don’t require you to already have pursued a PhD.

How important is intelligence?

In general, high IQ seems to provide a significant advantage in doing scientific research. A study of 64 eminent scientists (physicists, biologists, and social psychologists) by Harvard psychologist Anne Roe found that their median scores on tests of verbal, spatial and mathematical reasoning corresponded to IQ scores well above the median IQ of PhD scientists (though some have contested this, as we discuss below).11 If IQ were irrelevant beyond a threshold, we’d expect this group of successful scientists to have average scores similar to the average population of scientists which are already very high. Another line of support for this comes from the fact that intelligence is correlated with job performance more generally12, and the correlation is stronger for more complex jobs13. Since research is among the most complex careers, this suggests intelligence will be strongly predictive of success in research.14

Beyond this, more specific abilities – in verbal, quantitative, and spatial reasoning – seem to be important predictors of which fields a person is most likely to succeed in. A more recent longitudinal study of “mathematically precocious youth” over 35 years found that ability level (as measured by SAT scores aged 13) contributed significantly to academic accomplishments (securing a doctorate, tenure-track position, patents or noteworthy publications), but that ability tilt (the difference between math and verbal SAT scores) was highly predictive of the kind of domain these achievements occurred in. Subjects who reached high levels of achievement in the humanities were more likely to score high on the verbal SAT relative to the math SAT, and the reverse for those whose achievements were in the sciences.15

Results from the same 35-year study of talented youth found that spatial reasoning ability (the ability to match objects seen from different perspectives, judge what cross-section will result when an object is cut in different ways, etc.) is predictive of academic success in addition to verbal & quantitative reasoning. A 2013 analysis found that verbal & quantitative reasoning jointly accounted for about 11% of the variance in the number of patents & peer-reviewed publications a subject had, and that spatial ability accounted for an addition 7.6%.16 David Lubinski, one of the study’s co-directors, suggests that spatial reasoning “may be the largest known untapped source of human potential… no admissions directors I know of are looking at this, and it’s generally overlooked in school-based assessments.”17

However, this doesn’t mean that you /need/ to have an IQ or test scores in the top 0.01% in order to have a chance of contributing valuable research. In A Question of Intelligence, Daniel Seligman reports that the correlation between IQ and elementary school grades is 0.65.18 This is a high correlation, but far from perfect – meaning how hard you work and other personality factors are also likely to be important, as we’ll discuss below. Seligman points out that if becoming a tenured professor is a one in a thousand level accomplishment, then we’d expect the average tenured professor to have an IQ of around 150 if the correlation between IQ and academic success were perfect. But if the correlation is 0.65, then we should expect the average tenured professor to have an IQ around 133, with quite a bit of variability around that.

There’s also reasonable variability by field – high intelligence, and high verbal/quantitative/spatial reasoning ability will be more important in some areas than others. Here are the average GRE scores of applicants to the following PhD courses:

  1. Physics (1899)
  2. Mathematics (1877)
  3. Computer Science (1862)
  4. Economics (1857)
  5. Chemical Engin. (1845)
  6. Material Science (1840)
  7. Electrical Engin. (1821)
  8. Mechanical Engin. (1814)
  9. Philosophy (1803)
  10. Chemistry (1779)
  11. Earth Sciences (1761)
  12. Industrial Engin. (1745)
  13. Civil Engin. (1744)
  14. Biology (1734)
  15. English Lang. / Lit. (1702)
  16. Religion / Theology (1701)
  17. Political Science (1697)
  18. History (1695)
  19. Art History (1681)
  20. Anthro. / Archaeol. (1675)
  21. Architecture (1652)
  22. Business (1639)
  23. Sociology (1613)
  24. Psychology (1583)
  25. Medicine (1582)
  26. Communication (1549)
  27. Education (1514)
  28. Public Administrat. (1460)

We worry about the reliability of this data, which is purportedly from 2002, and would like to find a better source, but so far it is the only one we have found.

We can also get a sense of how important IQ is in a field by looking at the age of peak performance in that field. Since IQ declines sharply with age, fields where researchers make their biggest breakthroughs early in their careers are likely to rely more on intelligence — in physics and pure mathematics, the age of peak output is around 30, for example, suggesting intelligence is highly important for contributions in these fields. In medicine and history, by contrast, the age of peak output is closer to 50 — suggesting that accumulated knowledge and effort play a much larger role in making contributions to these fields. Psychology falls somewhere in between.19

Continue reading →

Notes and references

  1. Full disclosure: Giving What We Can is part of the Centre for Effective Altruism, which also serves as the parent charity of 80,000 Hours. Without Peter Singer, there’s a good chance 80,000 Hours would not exist, either!
  2. "Prospect/FP Top 100 Public Intellectuals Results". October 15, 2005.
  3. Julie Gould. The elephant in the lab. NatureJobs Blog 2015.
  4. Ghaffarzadegan, N., Hawley, J., Larson, R., & Xue, Y. (2015). A Note on PhD Population Growth in Biomedical Sciences. Systems Research and Behavioral Science, 23(3), 402–405. http://doi.org/10.1002/sres.2324
  5. Larson, Richard C., Navid Ghaffarzadegan, and Yi Xue. "Too many PhD graduates or too few academic job openings: the basic reproductive number R0 in academia." Systems research and behavioral science 31.6 (2014): 745-750.
  6. Taylor, Martin, Ben Martin, and James Wilsdon. The scientific century: securing our future prosperity. The Royal Society, 2010.
  7. Clauset, A., Arbesman, S., Larremore, D.B. (2015). Systematic inequality and hierarchy in faculty hiring networks. Science Advances, 1, 1
  8. Bonetta, L. (2009) “The Evolving Postdoctoral Experience”. Science Magazine
  9. Andalib, Maryam A., Navid Ghaffarzadegan, and Richard C. Larson. "The Postdoc Queue: A Labour Force in Waiting." Systems Research and Behavioral Science (2016).
  10. Ph.D. Completion and Attrition: Analysis of Baseline Program Data from the Ph.D. Completion Project. Downloadable here.
  11. Roe obtained difficult problems in verbal, spatial and mathematical reasoning from the Educational Testing Service, and created three tests which were administered to the 64 scientists. The same tests were also administered to a cohort of PhD students, who also took standard IQ tests, which were used to normalise the V, S, & M tests. The median “normalised” scores for verbal, spatial and mathematical reasoning amongst the 64 scientists were 166, 137 and 154 respectively - the median IQ of the PhD graduates tested was 141. The median scientists’ score on the spatial test was lower than the median score of PhD graduates, but Roe notes that spatial reasoning scores correlate with age - younger men are likely to get higher scores - so the comparison with PhD graduates is not so direct (i.e. the scientists may have scored higher than the average PhD student when they were the same age.)

    See Roe, A. (1952) The Making of a Scientist.
  12. Hunter, John E. “Cognitive ability, cognitive aptitudes, job knowledge, and job performance.” Journal of vocational behavior 29.3 (1986): 340-362.
  13. Hunter, John E, Frank L Schmidt, and Michael K Judiesch. “Individual differences in output variability as a function of job complexity.” Journal of Applied Psychology 75.1 (1990): 28.
  14. “Although GMA predicts performance in all jobs the more complex the job is13, the stronger the relationship between GMA and performance.14 And the more complex the job, the more variation there is between top performers and bottom performers.15 So if you have one of the highest levels of GMA in a highly complex job, you’ll have a high output compared to the average performer.” Intelligence matters more than you think for career success.
  15. Park, G., Lubinski, D., and Benbow, C. (2007). Contrasting Intellectual Patterns Predict Creativity in the Arts and Sciences: Tracking Intellectually Precocious Youth Over 25 Years. Psychological Science, 18, 11, pp. 948-952
  16. Lubinski, D., Benbow, C., Kell, H. (2014). Life Paths and Accomplishments of Mathematically Precocious Males and Females Four Decades Later. Psychological Science, 25, 12, pp.2217-2232
  17. Clynes, T. (2016) How to raise a genius: lessons from a 45-year study of super-smart children. Nature 537, 152-155
  18. This is the best place to understand the true relationship between IQ and academic performance rather than later in the education system, because at later stages lower-IQ people have already dropped out, so other factors beyond IQ will account for more of the variance.
  19. “At one extreme, some fields are characterized by relatively early peaks, usually around the early 30s or even late 20s in chronological units, with somewhat steep descents thereafter, so that the output rate becomes less than one quarter the maximum. This agewise pattern apparently holds for such endeavors as lyric poetry, pure mathematics, and theoretical physics, for example. At the contrary extreme, the typical trends in other endeavors may display a leisurely rise to a comparatively late peak, in the late 40s or even 50s chronologically, with a minimal if not largely absent drop-off afterward. This more elongated curve holds for such domains as novel writing, history, philosophy, medicine, and general scholarship, for instance.” From Simonton, Dean K. "Age and outstanding achievement: What do we know after a century of research?." Psychological Bulletin 104.2 (1988): 251.