In a few months, I will complete my PhD and I'm considering leaving experimental chemistry and looking for a postdoc on computational chemistry. During my PhD I used some computational tools like CASTEP and Gaussian, to be honest, I used these tools without understanding a lot of the physics behind them and I guess that should be the step forward.
I would like to keep working on heterogeneous catalysis, but I'm interested in exploring computational approaches like molecular dynamics, machine learning, some data science, and computing observable properties (spectroscopy?)
I do understand that I will be a bit behind other people that did PhDs in computational chemistry, and for that reason, I want to learn as much as I can before I apply for such positions. I did some googling and found a lot of books about computational chemistry, but they are so many that it is difficult to select the one that would make the transition “easy and fast”. A bit like a catalyst?!
With all that said I was wondering if someone could give their opinion about what topics I should focus my study on and provide some resources that cover those same topics. I’m trying to define a path forward that would make this transition efficient and not spend hours learning stuff that is important but not essential