Thanks, I'm too small(16) to speak to 80000 hours, they refused me. Also, neurofeedback is like genetic engineering, the hardest part is bio ethics, I think. But it doesn't conflict with my goal because working at neuroscience require CS and bio skills, too.
I'm Taiwanese, maybe I'll have computer science and biology as my college major in Taiwan, and I'll go to US for a Bioinformatics master. My goal for now is to build a career in biology (probably Bioinformatics) professor or biotech companies scientists(such as cultivated meat). But, due to the immigration policy(you can't get H1B visa lottery if you're unlucky.), culture gap（I'm not good at socialising), economic situations... I have heard even non-EA aligned career opportunities (like Silicon Valley) are hard to get. If you fail to find a job, you have to go back to Taiwan in 3 months. Moreover, you often need to send 10+ resumes to get a job, but most career opportunities aren't that EA-aligned. So you'll probably get the first job in non-EA aligned company.(It can build career capital though) Does it mean I need to wait for an EA-aligned career until I get a green card and save enough money?
I don't know international issues or bio well, but fwiw I would resist the urge to spend a ton of time thinking about planning various possible career paths in the distant future as an young undergrad. The future is hard to predict. I'd focus on getting the skills that will give you options.
Respectfully, you may need to just "put your head down" for a couple years and just focus on studying really hard and not think too much about the distant future. I'd start by focusing your studies on foundational subjects like math and then gradually shift your coursework/time more to applied subjects (e.g. statistics -> bio) as you go through undergrad and beyond. Take hard stem classes (within your level) and try to learn as much math as possible. Don't worry about getting straight A's. B's in hard classes is better than A's in easy classes. If you can understand, say, scientific computing, MV calc, linear algebra, real analysis + functional analysis (optional), probability, bayesian statistics, and machine learning/deep learning, and you also you also background in bio (esp. if you have some research experience), you will likely be accepted to good phd programs (let alone masters) in U.S. and elsewhere. Private sector jobs or research assistantships will likely also be available.
Every once in a while come up for air and reorient your direction. But I think it's the long slow slog (through the textbooks, psets, coding assignments) that will bring you success rather than getting the perfect career plan from day one.
Hello Lixiang: Thanks ver much for your comment. Of course I'll study as much math as I can(I mentioned that I'll have CS for my college major). But, if the immigration policy didn't change from now, it's hard to get a job even with deep CS skills, (unless I become a CS professor). I don't want to go back Taiwan, because in Taiwan, you can only do engineers in big companies which aren't EA-aligned.
Actually,I was considering if I should study medicine in the college. We decide our major in freshman year. In Taiwan, med is the most popular major, CS the third popular. I can get both majors, too, but it's hard. I need to make the decision as fast as I can.(also persuade my parents) Pros on studying med： 1.If you fail to get a job/ be a professor aborad or get fired in the future（chance：unknown, but may be high）,you can go back Taiwan for doctor, which is more stable（won't get fired）, altruistic(if you're a better doctor than average) and easier to ETG than engineers. Good backup plan 2.I can consider pass through USMLE to be a doctor in America and get my green card. Which may be easier to settle down than working as engineer in USA. Then I can start to do EA-aligned careers. Cons 1.May waste 6 years to learn med if you didn't work as doctor or medicine-related bioresearch. 2.Its hard to learn medicine and CS at the same time if I'm not smart enough. I won't be that skillful in CS.