Description: In physics classes, we are taught how to think of lots of different types of technical problems from first principles. A common approach is to start with some very crude approximations, and them to make simplified yet fully explainable models of a system. Next we check the predictions of the model against data gathered from the real system we care about and use this feedback to refine the model if needed. Once our model matches observable data to the level of accuracy needed for the application, we use that model as a tool to help us make decisions.
With a physics degree, we gain lots of transferable skills that can be applied in many real-world situations, but we get comparatively little exposure to the specifics of most situations we could apply our skills to in the job market. Over the past decade since I have graduated, I have often found it useful to approach career problems the same way I would approach a physics problem. In this talk I will outline this approach (the physics of the job market), going over some examples mostly from my own career - including applying to grad schools, building a network, applying for jobs, building a business, and investing in other businesses.
Speaker: Dr. Ian Burgess
Host: Alan Chen