I doubt that Julia is going to surpass R in a decade as you say. I use R because statisticians like it and contribute every obscure technique into it. Statisticians (for most part) don't seem to care about performance or elegance of the language from an engineering standpoint. R toolbox, for whatever reason, makes sense to them. For most people, R is used more as a statistical shell, rather than a programming language. Do I care whether BASH scripting is elegant or fast? No... just that everything is quickly available from it.
Julia will no doubt be valuable for a subset of statistical techniques where performance matters. I think Julia will become a good extension language for vectorized code. It will perhaps be the next NumPy/Cython, a general-purpose high-level, high-performance language/libraries that everyone can plug into, not just the Python community.
The one problem I had was that it still had a nasty startup time when I last evaluated it an year ago. Gadfly took way too long to import... something like a minute. Its not a problem for interactive use, but painful for scripts. It can be worked around of course. I hope the grant helps.