A good afternoon

So today, I randomly and spur of the moment decided to accompany my adviser/boss to a nearby small liberal artsy type college, where he was presenting guest lectures in two classes. I had a blast. The last time I sat through a class was in May of 2008. I realized that I very much miss math courses. It's soooo strange to spend 6+ years of your life getting really good at something (ie, sitting in courses and studying and such), and then to have all of that disappear pretty much overnight. So it was like a bit of a nostalgic thing to do, even if it was in a totally different place and with different people.

Besides, it was a realllly cool lecture topic - essentially using random walk concepts to derive the PDE (partial differential equation) representing diffusion of particles in space and time. Sexy equation, check it out: wiki

We even talked about some tricks for studying PDE's - mainly converting them to ODEs. And solved Fisher's equation, studying invasion fronts (the examples were even biological!). And all of this is the foundation for sweeet things like Turing structures, and Zhabotinsky soup. I wish I could have taken a class like this when I was in undergrad, alas.

The driving today gave me a good chance to spend some time talking with my adviser dude. I quite like him. We have surprisingly similar backgrounds, although he has come down much more strongly and unapologetically on the side of doing all theory and little experimental work. Who knows, maybe I'll end up like that too. One amusing (and all too true) comment that came up during a random conversation was that I'm a really good deal for him. If we get a solid paper out of my project, which I expect to do, then he'll have gotten a paper for the price of supporting a lab tech w/out benefits. In comparison to funding a graduate student (stipend, plus tuition, plus benefits/health insurance) or a post-doc (larger stipend, benefits, etc). Apparently I'm cheap! I decided to take that as a compliment.

I think I realllly really need to make sure that I land in a spot for graduate school where I can reliably get my math fix. I want to take courses in numerical analysis, statistics (esp. multivariate), nonlinear dynamics, and PDEs. For starters. And, while this admittedly vacillates, right now I'm of the opinion that maybe I should have studied even more math, or looked for a Master's degree in applied mathematics/statistics before heading to a PhD. Ooops. I'm also sort of temporarily at least wishing that I had applied for one or two of the more prestigious/rigorous math/ecology programs that I shied away from... Sigh.

But tomorrow I could swing the other way again, who knows.