I was in the same boat as you, i.e. using the GPU during my studies. My premise is to optimise the most frequent use case, i.e., deep learning.
IMO going with NVIDIA will save you so much worries and frustration that it clearly outweighs the downsides of worse Wayland support compared with AMD.
When you have tough university assignments/projects, you want to focus on the actual problem instead of debugging/compiling libraries for use with AMD. I am sure that with a bit of work many libraries can be made to work with AMD, but apparently it is still a pain oftentimes.
So I strongly suggest choosing NVIDIA. Disclaimer: have not used AMD for deep learning yet, but have monitored the development of AMD support, because I would like to switch to AMD.
Btw. I found Pop!OS to be very nice for both “regular” university work and all computer science tasks.
Pop has not received feature updates for years, because the dev team focuses on implementing Cosmic.
Given the overall progress of Linux Desktop environments, this might have led many users to switch away from Pop.