I'm a 22 year old final year Electronics and Computer Engineering student in India, graduating in June 2027, and I'm trying to figure out what direction to take for my master's.
I've always been fascinated by space and questions about the universe: how it began, why it behaves the way it does, black holes, gravity, and what we still don't understand about reality.
I'm interested in theoretical physics and cosmology, but my undergraduate background is in ECE. I also disliked the way physics was taught during JEE preparation, where we were expected to learn concepts quickly and immediately solve problems. I prefer asking questions and understanding things deeply, including the mathematics behind them. I'm not sure yet whether I'll enjoy doing physics professionally.
I'm considering theoretical physics, applied mathematics, computational physics/science, or an interdisciplinary master's such as Computational Science and Engineering. However, I don't want to end up merely writing code for other researchers; I'd like to contribute to the actual scientific questions.
I also care about having reasonable financial stability and career prospects. I'm willing to pursue a PhD if necessary, but I want to make an informed decision before committing years to a path.
I am good with C++ and data structures and algorithms , and currently learning python and machine learning ( just to show what i'm good at and what i know ) .
- What should I start studying to determine whether theoretical physics is right for me?
- Is transitioning from ECE to theoretical physics or cosmology realistically possible?
- Would an interdisciplinary master's be a good route, or would it leave me without sufficient physics foundations?
- Which textbooks, courses or research areas would you recommend exploring first?
I'd appreciate honest advice, including the difficulties and downsides of pursuing this path. I don't expect a guaranteed career; I just want to find a direction that genuinely interests me and gives me the opportunity to contribute to meaningful research in this world of AI .