This was revelatory; published in Science, I was surprised to read that there is a talent crunch. I’d dive in the issue a bit later but get the grist first:
Those experiencing challenges span STEM fields, including biomedicine, chemistry, environmental science, anthropology, physics, and computer science. Many reported not only a drop in the total number of applications, but also in the quality of applications. “It took two rounds of advertising my current postdoc opening—once in October 2021 and again in April 2022—to find a competitive applicant,” one researcher wrote by email. “I received 28 applications in all, which in the past I could have expected within a month of the first announcement.” The number coming from applicants who are currently based at U.S. institutions has also declined, according to many respondents.
The faculty jobs rebounded post-pandemic as per a survey here:
Many speculated that the faculty job market would be severely impacted by the COVID-19 pandemic, potentially for years. Our examination of faculty job postings from 2018 to 2021 found that while they decreased in 2020, the market recovered in 2021. We also surveyed how the pandemic affected the perceptions, behaviors, and outcomes of individuals on the faculty job market in 2019 to 2020 and 2020 to 21. Approximately 10% of the faculty job offers made to 2019 through 2020 survey respondents were reported as rescinded. Respondents also reported altering their application documents in response to the pandemic as well as delaying or even abandoning their faculty job search. Thus, while the faculty job market may have recovered, the effect of the pandemic on postdoctoral career choices may have future implications.
However, these are surveys, and I don’t trust the results. There is no specific recruiting and hiring data through employment exchanges, and hence the visibility in the system remains opaque. Imagine if there were clear real-time data compilations of those advertising for the jobs, those seeking it and those getting hired. It would be a true reflection of the state of affairs. However, we are getting “employment-snapshots” instead. Surveys achieve little, since the data can be easily fudged to push through a narrative.
Yet, it bakes into fundamental problem. Are we paying the PhD’s enough? Most grind through poverty level wages instead and develop specific skill sets to apply them in industry or branch out in start-ups. It requires specific institutional reforms and a clear line of profitability to sustain the start-up, unless there’s a benevolent VC funding it through. Pure “research” is limited to government funded grants (mostly), while corporate R&D is in decline. Those adept in statistical number crunching find themselves working on advertising algorithms or exchanges.
This is concerning:
Postdoc salaries are frequently based on what the U.S. National Institutes of Health sets as its standard, “and that’s pretty low,” says Daniel Wolf Savin, a physicist and senior research scientist at Columbia University who is currently struggling to fill five postdoc positions. When hiring, he competes with national labs that offer up to $20,000 more per year in salary. “If we put in a research grant with a postdoc salary that they pay at a national lab, the program office is going to look at it and say, ‘Look, I can’t give you this much money. It’s so out of line with what everyone else is asking for,’” he says.
It is the same reason why research languishes. Science isn’t to blame, but it’s a complex mixture of economics, inflation, and stupidity of policies that limits opportunities for those engaged in vital sectors. I must reiterate that post-pandemic, the research goals should have been sharpened. For example, cancer research gets a lion’s share of biomedical funding, without real breakthroughs, because the pharma business is extremely lucrative. This comes at the expense of other lesser known diseases or guidelines-management or preventive aspects which have clear impact on populations (or communities). Research priorities also need to be clear; especially related to duplication.