So the Twitter is all a twitter over evolutionary biologist E.O. Wilson’s latest op-ed in which he offers this dreadful advice (boldface mine):
Over the years, I have co-written many papers with mathematicians and statisticians, so I can offer the following principle with confidence. Call it Wilson’s Principle No. 1: It is far easier for scientists to acquire needed collaboration from mathematicians and statisticians than it is for mathematicians and statisticians to find scientists able to make use of their equations.
This imbalance is especially the case in biology, where factors in a real-life phenomenon are often misunderstood or never noticed in the first place. The annals of theoretical biology are clogged with mathematical models that either can be safely ignored or, when tested, fail. Possibly no more than 10% have any lasting value. Only those linked solidly to knowledge of real living systems have much chance of being used.
If your level of mathematical competence is low, plan to raise it, but meanwhile, know that you can do outstanding scientific work with what you have. Think twice, though, about specializing in fields that require a close alternation of experiment and quantitative analysis. These include most of physics and chemistry, as well as a few specialties in molecular biology.
For the life of me, as a trained evolutionary biologist, I fail to see how evolutionary biology doesn’t require quantitative analysis. But I digress. Because the real issue that this advice could only be offered by an 83 year-old BSD scientist from Harvard:
BREAKING!! Senior tenured faculty member at Harvard and leader in his field can find others to do the technical bits while he thinks Huge Fucking Thoughts. Guess what role you’ll play?
Now back to our regularly scheduled post. First, most PhDs won’t wind up in tenure track jobs. Like mothers used to tell daughters in days past, learn how to type. In other words, have options. If you can do some math or statistics, you have a skill that could allow you to do science–even if it’s outside of academia (AAAIEEE!!!!). Second, employers will be interested in you doing certain things–the Big Thought stuff, at least initially, is their purview (even if they suck at it). They’re not interested in hiring thinkers.
Of course, scientists need think conceptually and broadly, and the overemphasis on models can be harmful (economists are the worst about this, where they attempt to convince politicians to change reality when reality violates the assumptions of their models). But in an era of declining funding, having a well developed set of technical skills can keep you gainfully employed as a scientist (it’s like he doesn’t read my blog or something….).
Wilson’s column appears to be part of the long tradition of very successful people giving the rest of us really bad advice.
Well, this seems to be a particular problem for people dealing with tenure, career etc. in academic settings. As far as good analysis is concerned, his point about collaborations that bring as much thinking as the mathematical/statistical circus required to translate that thinking into practice, perhaps holds in evol bio as much as it does in public health (where I come from). The whole debate in my discipline about dealing with “complexity” requires as much conceptual clarity and intuitive understanding of health systems (read natural history?) as it does of the methods that can be used to make causal inferences in such complex settings (read modelling).
I (when I teach) will often advise students in STEM to go ahead and minor in mathematics with a strong dose of statistics. Generally when you point out you know mathematics on your resume, people are very impressed.
Once hired (outside of academia) though, you *really* need to be able to do something with that knowledge – something with excel. Become comfortable with using Excel formulas and VBA scripting, because no matter what you might use for your analysis – you’re going to need to put it into an Excel (or Word) document for everyone else.
You will be amazed at what passes for ‘analysis’ in the business world…
I shouldn’t agree with you because it ups my competition 🙂 . But that said I’ve already been able to bolster my income as a postdoc with private statistical consulting. Also I’ve gotten both ,my postdoc in evolution and maybe my next jobs on the merits of my programming and math skills. I’ve even been offered a job in biotech because they have statistical models that parallel the ones we use in ecology. When I hear about 600 people applying for faculty jobs I’m just glad years ago someone said to me:”learn to program”.
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My takeaway point from the Wilson quote was somewhat different: mathematicians in isolation are pretty much useless for doing anything other than constructing abstract models, and those tend not to have any descriptive power with regards to the real world (economics theory, anyone?). This is the gist of paragraph 2 of the quoted material. Furthermore, mathematicians are at a disadvantage because it is far more difficult for them to make successful overtures to life scientists (“Hi, I have a solution that’s looking for a problem”) than it is for scientists to find mathematical collaborators who are starving for something relevant to do (paragraph 1). Collaboration would be a win-win situation, but the guys who have the data hold all the cards, and have to make the first move. Finally, paragraph 3: if you suck at math, maybe it’s not a good idea to specialize in an area that requires a lot of math. Nothing wrong with that advice, IMO.
That comment was laughable. In the dark ages of the late 1990s I was working on a project that require a great deal of genomic mapping and phenotyping. Immediately there was a big problem. The statistical models needed to be drastically tweaked in light of how diffuse regulatory elements were proving to be within the genome. Until statistical models caught up – it was a hair tearing mess. The models started making their way to the molecular biologists like me, over the course of the project. Eventually, I had something I could work with. But I was not capable of creating my own statistical model…because I wasn’t a statistician.
Tenure is often abused. When I teach, and the kids moan that they are not in a “name school” I tell them that they should thank God they are not. They are being taught by Ph.D.’s – not some overworked and harried graduate student who probably can’t speak English that well. They are being taught by Ph.D.’s whose primary mission is to TEACH. Meanwhile, these big wheels bottle up the ability for younger faculty to make any progress. Then once the younger people move up, they will sit in those spots till they drop because they need the money. If you are in serial post-docs until the age of 40 – you will have to work until you are 80.
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