Hi all, I’m a college sophomore going for a Bachelor of Science in chemistry. I have to choose between a few different upper-level math and physics classes to fulfill a requirement. I’m not interested in taking more physics so I have a choice between linear algebra and multivariable calc. After undergrad, I hope to get my Ph.D. and I really enjoy organic chemistry so I would likely focus my attention to that field. I am leaning towards linear algebra but would like some more opinions. Thank you for reading!
If you can, you should take both. If you can only do one, I would pick linear algebra.
I’m a PhD organic chemist, and now work at a national lab. My undergrad program required both multivariate calc and linear algebra because calculus as a prereq for quantum chemistry and linear algebra was a prereq for computational chemistry. A lot of the background of how the computational techniques were derived also requires calculus.
What area of organic chemistry do you want to do your PhD in? A lot of organic research is paired with computational modeling techniques. Organic chemistry at the PhD level is getting increasingly quantitative. It helps a lot to be able to handle complex kinetic/rate equations, which will require calculus. And it also helps to be able to do your own computational modeling and regression analysis for structure-activity relationships, which will require algebra. I very rarely have to do any math by hand, but I wish I were much more fluent in math concepts so that I can handle large datasets and write macros faster. In my day-to-day work, I still kind of use my math skills in that a lot of studies now include mathematical/computational models. I need to be able to tell if they’re reasonable models and the consequences of any assumptions they use.
Also, if you’re thinking about a synthetic organic PhD, know that the pure synthetic organic ‘chemistry jock’ is having lot more difficulty finding jobs in the chemical (pharma, petrol, materials, agro) industry. Companies like Genentech and Merck are looking for quantitative or cross-over biology skills. In drug discovery and some of process development, the chemistry is largely done by high-throughput robots. A new trend is using machine learning to find and optimize new chemical reactions. The PhD scientist adds value by being able to crunch large datasets while applying ‘chemical intuition’ to make decisions.