Prospective career landscape for PhDs and postdocs

1. Prospective career landscape for PhDs and postdocs Michael s. teitelbaum Wertheim fellow Harvard law school mst1900@yahoo.com

2. OUTLINE • Symptoms of improvement? • Symptoms of malaise? The Postdoc as Canary • How attractive are careers for PhDs? • Can more Federal research funding solve? • What is in prospect for PhD/postdoc careers?

3. 1. Improvements since 2000 COSEPUP report • Remuneration up, primarily due NIH & NSF actions • Earlier NIH guidelines had dragged down • But still low for age and level of education • NPA, PDOs, PDAs (declare bias) • Spread of individual development plans • Agreed definition of a “postdoc” (2007) • Interest in postdoc scene from NIH Director • Also scientific societies (AAMC, FASEB, ACS, etc.)

4. Postdoc definition, agreed by NIH and NSF (2007) • An individual who has received a doctoral degree (or equivalent) and is engaged in a temporary and defined period of mentored advanced training to enhance the professional skills and research independence needed to pursue his or her chosen career path. • Source: http://www.nsf.gov/statistics/seind08/pdf/c03.pdf

5. 2. Symptoms of malaise? • Reliable & up-to-date data – a lot we don’t know • Science press: prospects poor – Correct? Anecdote?

6. Questions persist from the aspiring • What prospects for real research career? • At what age? Compatible with a “life”? • Future research $ for junior investigators? • Support for high-risk/high-return research? • Proposal success rates? Time proposal-writing? • Does tenure include salary? (med schools) • Funding gap risks? Gap funding from institutions? • Is PhD/postdoc right for non-academic career?

7. The Postdoc as Canary • Apparently grew rapidly over past 15 years • Rough estimate (2005): ~90,000National Science Board, Science and Engineering Indicators, 2010 • Ca. 50% of total in biomedical = ~ 45,000 • Substantial increases since then, apparently • % domestic PhDs taking postdocs down, esp women • Increasing % international postdocs

8. But our canary sensors are weak… • Numbers of postdocs? DK within factor of 2 (2005) • Unsure how much increase over past several years • Number postdocs on campus? Improving • Average postdoc career experience? Don’t know • Are postdocs in top labs doing well? Views differ • Either way, what about non-top labs? • Sigma Xi National Postdoctoral Survey (2003-4) is still sole national survey effort – embarrassing…

9. Postdocs in Biomedical, Behavioral, Social, Clinical Sciences, by citizenship and visa status

10. Postdocs in Biomedical, Behavioral, Social, Clinical Sciences:Primary source of support

11. 3. How attractive are careers for PhDs? • New normal for 5-6 year biomedical PhD cohorts • NB: Latest data = 2006 (much change since!) • Tenure-track academic career = minority • More in non-tenure-track than in tenure-track • More in extended postdocs than in tenure-track • Government careers pretty constant @ ca. 10% • Industry: > tenure-track & non-tenure-track academic • But depends on economic trends, esppharma and biotech • Both appear to have been flat-to-declining recently • “Other” = 10%: data esp. weak, mostly anecdote • Financial sector; patent law; out-of-workforce?

12. Biological Sciences: 5-6 Year Cohort(Stephan, 2011)

13. Biomedical employment by sector 1975-2006(US PhDs only; includes postdocs)

14. Postdocrough estimate: 89,300 in 2005[Source: National Science Board, Science and Engineering Indicators, 2010] • 22,900 U.S. citizens and legal permanent residents in academe (SDR estimate). • 26,600 temporary visasholders in academe (GSS) • 13,000 U.S.-educated persons in postdoc positions not covered by GSS (SDR estimate). • 26,500 temporary visaholders in positions not covered by GSS (assumes proportion of temporary visa postdocs is same as for those covered by GSS). • Ca. 50% in biomedical = ~ 44,500

15. Rising % Postdocs are Temporary Visaholders, (Biological Sciences, 1980-2007) [Stephan, 2011]

16. Why rising % int’l students/postdocs? • ~60% postdocs now international? If so, why so? • US students have options int’l students don’t • Can go directly into workforce (if there are jobs…) • Or can borrow for e.g. medical, law, business schools • “Opportunity costs” lower for int’l students • Most other countries do not finance many postdocs • Federal $ ample for int’l students/postdocs as RA’s • Similar $ not available for law, medicine, business, etc. • US univ’s: high prestige for those returning home • PhD/postdoc = visa pathway for int’l students

17. Effects of NIH Doubling 1998-2003? • Caveat: postdoc data are quite incomplete • Growth in biomed postdocs (16K =>19K in 5 yrs) • Most growth in temporary visaholders (8K => 11K) • mostly foreign PhDs (likely, but not certain) • % temporary visas 60%, up from 50% in 5 yrs

18. Summary, as of 2008 • Prospects for new PhDs & postdocs “bleak” (Stephan, 2011) • Likelihood of tenure-track slot low • ~15% biomed?; somewhat higher in other science fields • “Buyers market” for PhDs • Universities: financially constrained, risk-averse • Decline in tenure-track hiring, hiring freezes, etc. • Decline in NIH budget (adjusted for inflation) • Industry hiring: • Was increasing (has it reversed since?)

19. After 2008? • Career data mostly lacking • Unlikely to have improved given deep recession • Press reports of industry RIFs common • But we really need quantitative evidence… • Need more up-to-date data (“flash data”) • Pharma/biotech: has net hiring reversed since 2008? • Collate from industry associations (PHARMA, BIO)? • Collate from industry publications, newsletters, websites?

20. 4. More research funding as solution? • More Federal research funding desirable • But can’t resolve career problems – structural • Natural experiment: NIH doubling • 14-15% budget growth did improve career prospects • But when rapid growth flattened, “crisis” • “Crisis” after 100% budget increase in 5 yrs • Fundamentally structural

22. Positive feedback loops => instability • More research $ => more PhDs & postdocs • with multiyear lag • Effects have been modeled (math PhDs, 2% increase) • Funding pulses make career prospects worse • Biomedical fields: • “…inherent problems of a system that relies on young temporary workers to staff labs – and continues to recruit students despite the difficulties recent graduates experience in finding research jobs…” [Stephan, 2012, p. 71]

23. Most Fed educ support from research $ • Only small % of funds for graduate students and postdocs from “education”/”training” funds • NIH: 22% of graduate students and postdocs • NSF: 14% of graduate students, 2% of postdocs • Other Federal science funders (DoD, DoE, etc.) • A guess: even lower percentages from education funds • Implication: research budgets are drivers of graduate student and postdoc numbers

24. 2/3 NIH-supported graduate students on RAs

25. 2/3 postdocs supported by NIH research grants

26. Other positive feedback loops • More research $ => med school expansion • Rational response to incentives • Expand faculty to capture expected research grant growth • Non-tenure-track limits institutional risk • Buyers market enables • Risk shifted to researchers • Even tenured vulnerable due soft money financing • Expand research facilities financed by grant overheads • Fed funding rules incentivize debt financing, leverage • Risky for institution if research funding flat

27. Erratic funding trajectories exacerbate • Biomedical: evolved structure requires rapid growth • Need +6%/yr NIH budget for system stability • Prescient Science article by D. Korn, et al. in 2002 • Less true for other academic research fields • Boom-bust, stop-start funding increases instability • Lobbying for “doubling” -- NIH, now NSF, NIST, DOE • Congressional view: “take the $ when you can get it” • Major risks fall on younger researchers • Careers depend on “when” they complete PhD/postdoc

28. 5. What in prospect for PhD/postdoc careers? • Past S&E forecasts: bad karma • NSF (late ‘80s) forecast S&E workforce “shortfalls” • Congress responded quickly with increased NSF budget • Early 90s: Congressional investigation of whether misled • PhD supply/demand in S&E: forecasting failure • “Interest in predicting demand and supply for doctoral scientists and engineers began in the 1950s, and since that time there have been repeated efforts to forecast impending shortages or surpluses… This need, however, has not been met by data based forecasting models, and accurate forecasts have not been produced.” [National Research Council, 2000, p. 1.]

29. Rely on national occupational projections? • BLS: 10-year projections, based on prior 3 years • Basis of recent reports by Carnevale et al. • Admirable: BLS assesses past projections • BLS assessments of its 1996-2006 projections • Missed major effects of oil price and housing bubbles • Overall, at macro levels, are better than “naïve” forecasts • “On the whole, the BLS 1996–2006 labor force, occupational employment, and industry employment projections outperformed those of naïve models.” • Better for large industries/occupations, less good for smaller • “…BLS was more accurate in projecting changes in the employment of large industries and occupations than changes in the employment of small industries and occupations. [Wyatt, 2010, p. 66.]

30. For credible 10-year S&E projections… • How overall US economy will fare over next decade • Oil prices, Euro, housing markets, financial system stability • Future R&D “offshoring” (China, India, Singapore) • Corporate R&D locational subsidized, mandated • Future R&D “in-shoring” into U.S.? • E.g. European, Japanese pharmaceutical firms to Boston? • Future Federal R&D budgets (next decade)? • NIH budget? -- the 800-pound gorilla in largest science field • DoD, DoE, NASA (defense, aerospace, energy industries) • Healthcare policies (for pharma, biotech workforce) • Academe: state $, endowments, Federal research

31. Humility re: foresight • Real humility required re: foresight ability • Projections are not forecasts/predictions • Need to re-do projections every 2 years – rapid change • 10-year projections: useful for only 2-3 years out? • Need more up-to-date labor market data • Comb industry-specific reports, data, publications • pharma, biotech, semiconductors, IT, etc. • Up-to-date labor market trends in academic science

32. My speculations…(not predictions!…) • Constrained Federal $ = instability in Academe • Industry R&D: unlikely to take up slack • Increased stability requires structural changes • But unlikely: strong interests support current structure • Gradual declining US interest in research careers? • “Buyers market;” career prospects unpredictable/unstable • Males: careers relatively unattractive (for citizens/LPRs) • Ditto females, plus conflict with “a life” • Caveat: Expect much variation by field, and over time • Ample temporary visas amplify drivers of trends

33. “Treatments” favoring stability (1) • Attenuate positive feedback between research $ and numbers of funded graduate students and postdocs • Shift support from research grants to “education”/“training” • Align PhD/postdoc system with career demand • Better data, and need to be MUCH more current • Provide accurate career info to prospective students, postdocs • Enable Federal support for Professional Staff Scientists • Reconsider growing Federal $ for int’l students/postdocs • Raise success rates for new investigators • Some successes from NIH interventions

34. “Treatments” (2) • Avoid rapid acceleration & deceleration in funding • Urge instead sustained increases keyed to GDP growth • Buffer erratic year-to-year Federal funding • E.g. “stabilization overhead” to support gap funding • Limit % faculty salaries on grants (Alberts, 2010) • Adjust incentives in overhead rules • Professional Science Master’s for non-academe • www.sciencemasters.com

35. Could do far better on data front • Create an “Observatory” to monitor science careers • Ongoing analysis of NSF and NIH data • Collect “flash” data • Current, if preliminary, like inflation & unemployment rates • Flash data, online surveys of key knowledge gaps • Current data to univ’s, funders, students, postdocs

36. Selected sources • Ian D. Wyatt, “Evaluating the 1996–2006 Employment Projections,” Monthly Labor Review, September 2010, pp. 33-68. • Paula Stephan, How Economics Shapes Science (Cambridge, MA: Harvard University Press, 2012) • National Research Council, Forecasting Demand and Supply of Doctoral Scientists and Engineers: Report of a Workshop on Methodology (Washington, DC: National Academy Press, 2000). • David Korn, Robert R. Rich, Howard H. Garrison, Sidney H. Golub, Mary J.C. Hendrix, Stephen J. Heinig, Bettie Sue Masters, Richard J. Turman, “The NIH budget in the ‘Postdoubling’ Era,” Science 296, 1401-1402 (2002) • Michael S. Teitelbaum, “Structural Disequilibria in Biomedical Research,” Science 321, 1 August 2008, 644-645. • Bruce Alberts, “Overbuilding Research Capacity,” Science 329, 1257.

37. THANK YOU!(questions/comments welcome) Michael S. Teitelbaum mst1900@yahoo.com

38. NIH success rates equalizing (but low)

39. But 42+ years on average

40. Recent trend reversal (Rockey, 2011)

41. The Cliff (Rockey, 2011)