I'm going to get a Master's in Artificial Intelligence, likely a PhD in Molecular Biology afterwards. I'm thinking I can do computer vision as a hobby while putting most of my energy toward understanding the big picture of cellular processes, because computer vision is something I can performance check. That's why I'm leaning towards Molecular Biology over AI even though I'll have years of research experience in AI.

The problem is that I want to know too much. I want to study Cell Signaling/regulation, Genomics, Molecular Biology/Biochemistry/Structural Biology, and disease during my PhD to do some interdisciplinary research in all of it. I want to develop computational data mining models that can take entire cellular systems into account.

Is it unheard of to fully specialize in two subfields during a PhD and associate my research topic to cancer later on in my PhD over 5-7 years? Or must I, for example, study a single new enzyme in an important pathway across various environments only in biochemistry?

Can you have a more general PhD that is still a successful contribution to the field? Say an analysis that studies an entire biochemical pathway from genetics through molecular biology to cancer if I have two committee members (one in each subfield)?


You say, "The problem is that I want to know too much." You don't want to know too much, but maybe you want to know too much all at once.

If you are going to pursue a PhD in molecular biology, you owe it to yourself, your department, your research adviser, and whomever is providing financial support to focus you energy on learning that material and writing a fine thesis roughly within the usual time expected by your department. Most serious PhD students don't have much time for 'hobbies' outside of their coursework and research, but if you do, you could consider AI as your hobby for now.

There seem to be unexploited connections between molecular biology and AI, so it is worthwhile to look forward to exploring those connections at an appropriate time.

If you can't bear to let a major connection to AI wait until you finish a PhD in molecular biology, then maybe you should re-think the order of your concentrations. Both fields are developing rapidly. Will it be easier to catch up on recent developments in AI after your PhD in molecular biology? Or would it be easier to learn about recent developments in molecular biology after getting a PhD in AI?

I have some idea how much biology an AI a person would have to know in order to make worthwhile applications to molecular biology. But personally, I have no idea how much you would have to know about AI to exploit opportunities in molecular biology. So I have no advice about the best order of concentration.

As a starting place for you to make the best decision on your own, do you see how study "of a single new enzyme ..." would make successful exploitation of AI techniques more likely? Or maybe you can find a molecular biology department that is already deeply committed to using AI.

I have done a lot of work in applications of statistics and probability modeling to biology with only self-taught biology (not even a high school biology class). My impression is that it is easier for me to catch the essence of the necessary biology ad hoc than it is for biologists to catch the the essence of the required statistics or probability. (Some of my collaborators may disagree on that.)

  • Thank you so much for investing the time into your response. I'll be reading it a few times over as I continue to consider everything you have said. – Kulgurae Mar 13 '18 at 0:19

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