<p>One quibble (though also pointed out by other posters): computational science is not “relatively new” (unless you are comparing it to something like mathematics). In fact, CS arguably came out of computational science. For example, the four founding members of the CS department at Stanford in 1962 were three numerical analysts (Forsythe, Golub, Herriott), and a mathematician-turned AI-researcher (and many other things): McCarthy.</p>
<p>There was an effort to rebrand the field 10-15 years ago, creating interdisciplinary programs (not departments) “staffed” by faculty from many different departments. As you can see from the number of programs, it has not been particularly successful. Computation however is critical in many fields, and the Federal government has set up fellowships to encourage graduate students to consider computational-oriented studies. (Search for Department of Energy Computational Science Graduate Fellowship.) When I was in graduate school, many of the best numerical analysts were engineers (aero-astro simulating flow around aircraft, EE studying how to improve the process of designing chips, civil/mechanical/… modeling fluid flow in a variety of situations or developing crash codes, etc. I went through a CS program, and came out with a CS-tinged background in numerical analysis (and currently work with computational science codes running on ‘supercomputers’).</p>
<p>Computational science is like applied mathematics in the sense that, while there is a common basis, it is applied to something, and what that something is determines what you end up doing as a career. Most technical fields have a strong computational dependence. Even in something like physics the viewpoint is that there are “three legs” to the field: experimentation, theory, and simulation (aka computation).</p>
<p>Going into academia as a computational scientist is not easy going - departments are pretty rigid and have established criteria for evaluating faculty productivity. Interdisciplinary work is not often valued highly (and may be considered a challenge to the existing structure). However, finding research funding is not necessarily harder. In government research labs (DOD, DOE, NOAA, NASA, …) computational science is valued highly, and I think that it is also in some industries (oil companies and automobile manufacturers, aircraft manufacturers, … though I do not know the raw numbers employed in those fields). </p>
<p>This doesn’t really answer the question as to whether the interdisciplinary programs make sense or not, or whether it simply best to focus on the computation from within a traditional department. Many departments will have a computational concentration.</p>