I too have a PhD in Biology, and also write code for biological problems. I would suggest that the distinction approaches to thinking you're seeing is rather b

I too have a PhD in Biology, and also write code for biological problems. I would suggest that the distinction approaches to thinking you're seeing is rather between theorists and application driven people, regardless of domain. The same difference would apply between, say, an astrophysicist, and an engineer who develops a space telescope. People at the cutting edge of research appreciate that they're at the 'edge', and that their deep domain knowledge can only ever serve as a starting point for answers that may not even exist. Scientists working in applications aren't interested, nor need to worry about the ontological limitations of deep knowledge. If, for example, my concern is development of ML based high throughput cancer screening, I already know this is a doable problem (with varying levels of success), and just requires my deep knowledge + smarts. If instead I'm a researcher working on a unified theory for all cancers, I would (ideally) be self aware enough that this is something that might not even exist. I imagine the same dichotomy exists in CS between researchers (i.e., cryptography, AI, quantum computing) and developers.