I recently got an email from newly graduated Math(s) major (mildly edited):
I am someone with a deep-seated desire to help the planet remain as habitable as possible in the face of the trials humanity is putting it through. I’d like to devote my career to this cause, but am young and haven’t chosen a definitive career path yet. My bachelors is in pure math and I am considering graduate study in either applied math or statistics. I’m curious what you would recommend to someone in my position. Between getting, say, a PhD in statistics vs. one in applied math, what positions me best for a career in the climate science community? What are its acute needs, where are the job opportunities, and how competitive is it?
My response was as follows (also slightly edited):
As you may know I too started out as a mathematician, and then moved to more climate related applications only in my post-doc(s).
I can’t possibly give you ‘the’ answer to your question – but I do suggest working from the top down. What do you see specifically as something where someone like you could have maximum impact? Then acquire the skills needed to make that happen. If that seems too hard to do now, spend time on the developing your basic toolkits – Bayesian approaches to statistics, forward modeling, some high level coding languages (R, python, matlab etc.), while reading widely about applications.
One of the things I appreciated most in finding my niche was being exposed to a very large number of topics – which while bewildering at the start, in the end allowed me to see the gaps where I could be most useful. At all times though, I pursued approaches and topics that were somewhat aesthetically pleasing to me, which is to say, I didn’t just take up problems just for the sake of it.
I’ve found that I get more satisifaction from focusing on making some progress related to big problems, rather than finding complete solutions to minor issues, but this probably differs from person to person.
But what do other people think? How should people prepare to work on important problems? Are there any general rules? What advice did people give you when you were starting out? Was it useful, or not? Any advice – from existing researchers, graduate students or interested public – will be welcome.