After grad school I got some very good advice from a mathematician:
If you are good at math, don't go where they are good at math.
He convinced me (and a few other phd physicists) to help him tackle the problem of industrial controls for heavy industry (think large refrigerated warehouses, steel refineries, food processing, etc.). We we're all graduating so we decided to give the startup route a try. Since then we've been designing/deploying cloud-based control software to regulate the energy of these huge power consumers.
https://www.crossnokaye.com/
In the day-to-day its more data science/computer science than physics but the core models we design are physics based so our white boards always have some derivations on them.
> After grad school I got some very good advice from a mathematician: If you are good at math, don't go where they are good at math.
^This. LOL.
IMHO a lot of opportunities arise at the borders between fields. This helped me put my finger on it; physics and its related math are a great basis for interdisciplinary work. Selling that idea to SW-company HR and hiring managers can be hard, in my experience, but startups more often benefit from versatile employees early on. Cool business idea BTW!
He convinced me (and a few other phd physicists) to help him tackle the problem of industrial controls for heavy industry (think large refrigerated warehouses, steel refineries, food processing, etc.). We we're all graduating so we decided to give the startup route a try. Since then we've been designing/deploying cloud-based control software to regulate the energy of these huge power consumers. https://www.crossnokaye.com/
In the day-to-day its more data science/computer science than physics but the core models we design are physics based so our white boards always have some derivations on them.