I work as a structural engineer in the aerospace industry. My main task involves finding out how load is redistributed throughout structural elements (basically an issue of the relative stiffness of the different load paths) and then checking components against their various failure modes to determine how close they are to failing in the different conditions they'll have to withstand. I also support related work, like determining accuracy of models based on flight data.

Rationality is related to my work in that determining how a model should be changed in light of flight test data (given the various sensors) is an elaborate application of Bayesian reasoning. Also, there is pressure to always "show the structure good", presenting the danger of writing your conclusion before you begin reasoning.

As a side interest, I like to learn about AI and any topic that I believe will provide insight on it, such as biology/evopsych, thermodynamics, consciousness, and information theory (the latter of which I've been deemed an expert on by Steven Landsburg, somehow). Information theory in particular looks like a fruitful topic to study because of the unifying vision it gives to all the others, and one of my projects has been to convert constraints of physical law into constaints on information, and I think it has enhanced my understanding of various topics.

My blind spot is in chemistry, especially organic, which I think would be helpful to learn as a case study in how a system can maintain very specific order against the 2nd law pressure, so knowing the nuts and bolts of how it works at the molecular level would be very helpful to me.