I'm almost done my PhD in a comp bio program. I have been doing research that I think is cool in terms of scientific value, and has been my own independent work in computational biology, but is not really mathematically/machine learning oriented. I really want to do a postdoc in a more rigorous stats machine learning lab (still in comp bio, but under someone from the cs world) and move my research more in that direction. My undergrad was in cs but not machine learning, and my grad coursework was not very useful. I'm kind of consumed with insecurity that my math/cs background is not enough to be taken seriously by those people. I've been teaching myself from a statistical inference text, and want to follow it with studying cs229, graphical models, optimization. But all this is going to take some time, and obviously I've got a lot else on my plate as I'm defending. Is it better to learn all this before applying to places like that, so that I'm not ruled out as a candidate? Or do you think my "domain knowledge" of computational biology could make up for this weakness? Should I try to get a postdoc somewhere less math heavy and bring those skills into my work on my own? Also if there's a better place to post this q, please let me know.