We need to reboot academia, at least for graduate training. I am speaking from the point of view of ecology/evolution (EEB). Why you ask? Because of the following line of reasoning:
First, the most important factor for me comes down to supply and demand. We have too much supply (=graduate students) and not enough demand (=faculty positions, etc.) - see this comic at PhDComics for proof. This seems especially apparent when you hear from your fellow postdoc friends that there were hundreds of other people with Ph.D.’s applying for the same position.
Second, funding is getting thin. I have never received funding from a competitive grant, despite having 12 published papers to my name. Recent cuts to the NSF, NIH, and other federal agencies mean that getting a grant will be harder and harder. Furthermore, the mean age of a first time NIH grant recipient in 2008 was 51 according to a recent study in PLoS One (Matthews et. al. 2011).
Third, we don’t learn the skills we really need. This is many fold. First, we don’t learn the appropriate mathematical and statistical techniques in undergraduate and grad school - a forthcoming paper found that in a survey of nearly 1000 ecology and evolution graduate students, most thought they were unprepared wrt to math and stats (interview with author in Soundcloud widget below). Second, we don’t learn enough computational skills. Digital data (not on your physical clipboard, but your digital one) is more and more important, requiring knowing how to leverage and keep track of data. Yet, we aren’t taught these skills, at least in my experience. The need for training in computation/coding is evident from the sold out Software Carpentry workshops. Third, reproducibility is not something we are taught. Well, we are taught to check over everything in detail (read: proof your data), but there is often no way to reproduce analyses when we use 10 different expensive software programs to do an analysis (read: MS Word, JMP, SAS, SigmaPlot, etc.). And isn’t reproduciblity important?
What do we do?
To address the supply/demand issue, I think we need fewer graduate students, period. I think this will work for a few reasons. If there are fewer graduate students, those that get in will be of higher quality because profs can be more selective, they may get payed more (hopefully) since there are few students, and they should in theory get more attention from their advisers (if they want it). In addition, there would be less competition for the very few grants out there for grad students. This would then lead to fewer postdocs, and less competition for faculty positions. I think the supply/demand issue in EEB is particularly problematic. That is, in EEB there doesn’t seem to be the large quantity of private sector jobs as there is for Ph.D. graduates in engineering, physics, etc.
The funding situation is beyond me, but definitely makes me want to leave academia. Crowdfunding, especially #SciFund, is an option for scientists, but mostly only on a small financial scale. Any thoughts?
The skills issue will likely be addressed in time, and vary among schools for sure. Some schools will focus on natural history, which is good (that’s where I did my undergrad and it was great), and some schools will incorporate more of these science 2.0 skills (advanced stats, better math training, and computer science).
Get the .Rmd file used to create this post at my github account - or .md file.
Written in Markdown, with help from knitr, and knitcitations.
Matthews KRW, Calhoun KM, lo N, ho V and Germano G (2011). “The Aging of Biomedical Research in The United States.” Plos One, 6. http://dx.doi.org/10.1371/journal.pone.0029738.