Thinking about making a transition from a Biomedical Engineering background to a more machine learning focused PhD -- trying to understand what kind of a theory/implementation split I should be going for. • /r/MachineLearning

So basically... I've spent the past several years of my life working in biology and biomedical engineering, but I've always felt very called by math and computer science. I find biology interesting, however... academic jobs are absurdly competitive, and in industry... because biology is so fickle, and the whole point of industry is naturally to make money, the level of difficulty of the problems that most biotech companies I see are facing are not fundamental research questions. So... I'm planning on starting a PhD program in Fall of 2017, and I have the opportunity to do a computational only PhD, that might be sort of a... machine learning-y data science-y kind of gig. But it would largely be implementation/analysis, probably no theory at all. I'm trying to get a feel for the extent that a mostly analysis/implementation PhD hinder my career goals after graduate schools.