This is very true - I was a physics undergrad and learned to code working in a project at cern. While the underlying physics was the foundation of the project, the day to day work was all coding: processing and analyzing the huge amounts of data coming out of the experiment.

> a physics undergrad

Now imagine dozens of people with a PhD in physics doing the same. (Earning a degree in physics is hard.)

yes, that was one of the insights of the work. The people working alongside me were post-docs that were still having to put in their time as workers on other people's research projects. Particularly, in the area of experimental high-energy physics, where accelerators were needed to do the work, everyone had to jockey to get time on the accelerator (even nobel laureates like the leader of the project I worked on). It seemed like every experiment was a compromise of different people's goals in order to combine together to get enough collective clout to get access to the accelerator to even do the project. That meant the guys who had already completed PhDs at prestigious schools were still pretty low on the hierarchy (but ten years older than me). The time spent working with those guys definitely influenced my decision not to continue with a PhD...

> computing science ... is slowly but surely becoming an essential part of many areas of modern physics research.

Also, this means that fundamental assumptions and the calculations are hidden from view. Recently, some physicists questioned the findings of LIGO but if I understand correctly all is decided by data analysis software and outside teams have a disadvantage to decipher it.

The LIGO result is actually excitingly available as an IPython notebook, which provides a tutorial to verify the data yourself, using entirely open source software. https://www.gw-openscience.org/s/events/GW150914/GW150914_tu... The actual signal processing isn't that complex IMO.

I don't know how open the LIGO hardware is, but it's very unlikely you would build one yourself to verify.