The real story is a bit more complicated. Yes, MATLAB has decades of extra development time, wonderful documentation, a much better debugger (I helped write Julia's debugger so I'm not being mean when I say that), and other advantages. But Julia has many advantages in some of the areas you cite. JuliaHub has JuliaSim, and while I've never used it, there are use-cases where it leaves Simulink in the dust. On medical imaging, Julia is overall more capable than Matlab in seamlessly flowing between multimodality/2D/3D images of large size: try, for example, doing lazy processing on large datasets as explained and demonstrated at https://youtu.be/x4oi0IKf52w?t=2257 (start watching at 55:20 if you just want to see the demo without the explanations leading up to it). Matlab's polish is not to be underestimated, and you're surely right that there are domains where it can't be beat, but there are also domains where Julia is a much better and more productive ecosystem.
Note there's a distinction between "startup.jl" and "Startup.jl": the latter is a package, not a script. That's necessary to allow precompilation. But you can add `using Startup` to your "startup.jl" so that it gets loaded automatically. Fortunately, it's very easy to create these personal packages, see intructions at https://julialang.github.io/PrecompileTools.jl/stable/#Tutor...
