I have worked on a lot of projects that involve science related stuff and Django.
Directly in the web app backend was relevant mostly for GIS apps that could take large raster data, process it based on the user's wishes, apply the right projections, apply a colormap and return an image to be shown on a map. Python has great tools for that sort of thing and it doesn't have to take much longer than rendering a HTML template does.
Other than that, the CPU intensive science-related stuff usually ran in background tasks, with Celery or otherwise. But those would still need access to the database, so why not use the same Django models for the web backend and the background tasks.
I find that once Django is part of your Python code it tends to find its way to all parts of it, through the ORM, settings files, handy admin interfaces, management commands as scripts, and so on.