A Multi-Purpose PhD

Issel Anne Lim
Sep 8, 2014

"With high numbers of postdocs emerging from universities, prospective PhD students must be prepared for the fact that they will probably not end up with a career in research."

So reads the the subtitle of a recent Nature editorial, "There is life after academia."

Upon graduating from college, I hoped that a research career would allow me to make a positive impact on various types of populations. Then, after "successfully" completing a predoctoral and a postdoctoral fellowship, I saw academia's lack of guaranteed funding, coupled with a lengthy time lapse in bringing technologies from the bench to the bedside. This made me start wondering: What is the purpose of a PhD? In a world where PhDs are increasingly moving into jobs outside of research, how can we identify metrics for success in these trainees and the grants that fund them?

During the semifinal round of applying to the AAAS Science & Technology Policy Fellowships, we were asked to write a memo on a particular topic. As part of my application, I wrote a piece that focused on points that were also mentioned in the Nature editorial. Here's a snippet with some statistics:

Researchers spur the global economy through innovation. A recent Research!America poll shows that 83% of Americans believe that investing in medical research is important for the US economy, with 70% of Americans believing that the government should encourage careers in Science, Technology, Engineering, and Mathematics (STEM). Training grants have uniquely contributed to the research workforce by promoting scientific leadership, diverse recruitment practices, responsible conduct of research, ethics, and career development. These programs are evaluated on whether trainees have been prepared for "productive scientific careers," traditionally focusing on academia. That said, the number of people with graduate degrees has doubled over the past 20 years, but only 25% of PhDs hold tenure-track positions five years after attaining their degree.

Of note is the price tag of a PhD: after a top-tier undergraduate education that costs over $200,000, academic or pure science careers often do not competitively compensate many promising researchers. After five to seven years of graduate training with an annual stipend below $30,000, these researchers must complete a postdoctoral fellowship with an entry-level salary under $43,000 -- less than a year of college tuition at Boston University, which is ranked #41 among national universities according to US News. Instead of continuing in academia, advanced degree candidates are joining the government, industry, management, communication, and other sectors that do not necessarily need scientific researchers, but do need leaders with analytical skills.

We must modify how we measure the productivity of trainees: instead of emphasizing how many papers a trainee has published, evaluating a training program should also involve gauging the marketability of alumni and promoting the diversification of quantitative problem-solvers to drive other fields.

What do YOU think? Let's gather thoughts here on how we'd change or challenge the current training schemes for PhDs. (Please comment below!)

Personally, I would like to implement a user-friendly, accessible, and secure online database that not only tracks the quantitative attributes of a training program's "success" (e.g., publications, patents, awards, etc.), but also the qualitative attributes (e.g., marketability, purpose, job satisfaction, faculty responsiveness, leadership qualities, or communication skills). We've been told many times that "soft skills" are super important in science and any career -- but how can we evaluate these skills? How can we use the data to improve how we train future generations of scientists? Can we prepare researchers for a broad range of careers in our evolving economy?

Overall, problem-solving skills seem to be quite handy for a growing number of leaders. Let's aim for skills that have a wide variety of applications, even as we research specific subsets of those applications. It's time for PhDs to not only specialize, but also to diversify.


Accompanying image created by Issel Anne Lim, PhD; Quirky Ink, LLC

Issel Anne Lim

Issel (pronounced "ee'-sil") is a Health Science Policy Analyst at the NIH, in the National Institute of Child Health and Human Develoment. She was a 2014-2015 AAAS S&T Policy Fellow in Big Data & Analytics at the NIH. She has dabbled in biomedical engineering, MRI, neurodegenerative diseases, and infection studies at JHU (PhD) and MIT (BSc). Issel led the AAAS Big Data Affinity Group to promote data science, as well as the AAAS FIRE Affinity Group to explore innovative program evaluation. Through her freelance design company, Quirky Ink, LLC, she builds websites, customizes graphics, and edits various types of writing.


This blog does not necessarily reflect the views of AAAS, its Council, Board of Directors, officers, or members. AAAS is not responsible for the accuracy of this material. AAAS has made this material available as a public service, but this does not constitute endorsement by the association.

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