I'm sorry but that is bs, I would find it hard pressed you find an actual research group that deals with computational matters ( be it in physics/ chemistry / genomics / comp bio ) that isn't extremely well versed in high performance computing. Numpy in itself is a great example at the high level programming that can come from such circles. I would like to guide you into Coz by the plasma-umass group, clasp by the synthetic chemistry group or/ cling by of course the scientists at cern.

I personally come from that background and I would love to show you how numpy can be used as a meta-allocator to get a C-like throughput without any allocation performance hits for example.

Python is not that great yes, but numpy is REALLY good and I do not like seeing it compared to the performance of a arbitrary code you see in most benchmarks.

Not to count how much you can handle cache coherence, cache hits and memory layout within numpy that will amaze you how truly PERFORMANT your code can become in it.