Theoretical HEP or neuroscience?

[upigdir]

ever since my first year in undergraduate, I wanted to pursue a degree on theoretical high energy physics. so I took a lot of theoretical classes and started a double major in math (I dropped it after I took some classes I was interested in). however now I have only one year left, I began to consider neuroscience as an alternative. I've always been interested in human mind (it is the most complex structure we know so far after all) and I find the area very promising. but then, I don't think the main research methods and general approach to problems is as challenging as physics. besides, it lacks the "elegance" of physics. and then I will have to take a lot of classes in graduate school to make up my lack of knowledge in biophysics.

Is there anyone took a sharp turn towards neuroscience? any ideas or suggestions are welcome.

 

[Crass_Oscillator]

Do you want to do experiment or theory? Some of the theory is heavily inspired by theoretical condensed matter/statistical physics and has applications in machine learning (Neural Networks) and doesn't necessarily currently care about connections to experiments in, say, humans. There's also the statistical/computer science side which involves developing statistical/computational techniques to make inferences from data (Sebastien Seung does cool stuff here). Both can involve a lot of gnarly math and theory.

The former is more for dealing with fundamental problems and does not relate to experiment very well these days IIRC. The latter is more for uncovering the nature of complex, messy, low quality experimental data.

I don't know anything about experiment.

 

[upigdir]

Do you want to do experiment or theory? Some of the theory is heavily inspired by theoretical condensed matter/statistical physics and has applications in machine learning (Neural Networks) and doesn't necessarily currently care about connections to experiments in, say, humans. There's also the statistical/computer science side which involves developing statistical/computational techniques to make inferences from data (Sebastien Seung does cool stuff here). Both can involve a lot of gnarly math and theory.

The former is more for dealing with fundamental problems and does not relate to experiment very well these days IIRC. The latter is more for uncovering the nature of complex, messy, low quality experimental data.

I don't know anything about experiment.

very helpful! yes, i want to do theory. never been good at experimenting tho. I've been gathering information about schools, and I think I will give it a shot, along with my HEP applications :) thank you.