So far, I've worked a bit in modeling, simulations and simple lab experiments, and I've really enjoyed all three research methods to approach a single research question. I can write tricky (in terms of implementation), bug-free code to simulate the models that my advisor and I tinker with and modify, based on theory, physical laws, and experimental data. My experimental skills in the lab are pretty much beginner, i.e. the experiments are already set up, designed, and debugged by my advisor, and a few of us run the experiments and take down measurements in our lab notebooks, watching for certain phenomena to unfold in the experiments.
With that said, here's my question:
I notice that I don't do much work in the area of numerical analysis, nor does my lab and its PIs -- and my PIs publish frequently in the top-tier journals. The solvers we use to simulate our models are standard and nothing fancy. Our model equations are simplistic, behave well, and aren't stiff. For Navier-Stokes stuff, we use pretty recent existing solvers that were published out of, say, the Journal of Computational Physics.
So, what kind of a researcher am I?
Which route should I be heading towards, if I love my type of work -- modeling, theory, simple experiments, or in other words "phenomenological" modeling -- but I don't actually spend time writing fancy, detailed solvers? All of my research enthusiasm and motivation is in seeing complex natural phenomena unfold in the lab experiments and simulations, giving us a mathematical framework and deeper understanding of some poorly-understood systems. My coding work is relatively "low tech", which I prefer -- and with the notion that if my research has a pretty generic approach, then the results can easily be extended or generalized in future work.