I want to apply machine learning to Biostats. Should I focus on a PhD in ML or Biostats?
If Biostats is the best route, what are some good schools? University of Washington, John’s Hopkins, and VCU are my top three.
Same for ML? Haven’t heard much about the PhD programs for machine learning. I was thinking UW, Stanford, and maybe Carnegie Melon since it’s one of the only school’s with an actual department instead of a concentration.
If it matters any, I’m a Statistics major pursing minors in CS and Math… Hoping I made the right choice majoring in Stats instead of CS. But yeah, I’m only a Sophomore so I can change if need be.
Probably either. You could major in biostatistics and take a lot of classes in CS and machine learning, and have a ML expert as a secondary (or even primary) advisor. Or you could do the opposite - get a PhD in ML but have a secondary or primary advisor in biostats who does research in the area. PhD programs are very flexible in this regard. With a major in stats it might be easier for you to get into PhD in biostatistics programs.
You don’t need a full-out ML department to get a PhD in this area - or maybe it’s just that you only apply to three ML PhD programs and then you apply to some other biostats departments. You really don’t need to apply to a metric ton of departments anyway. 6-9 is a good number, if you’re a competitive applicant.