Engineering Software Engineering and Astronomy/Physics

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At 26, the individual is pursuing a BSci in computer science and interning as a software engineer, with aspirations to develop software for the scientific community. They express interest in the potential need for graduate education, possibly a master's or PhD, to enhance their qualifications for scientific computing roles. A strong foundation in math and science is essential for writing software that addresses complex research problems, such as protein folding simulations. Familiarity with existing software frameworks like CHARM, NAMD, and MODELLER is important for contributing to advancements in scientific computing. The discussion emphasizes the significant learning curve involved in this field, but encourages pursuing this passion if it aligns with their interests.
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I am 26 years old and I recently went back to school to study computer science - I hope to graduate by 2019 with a BSci. I'm currently interning as a software engineer as well. I was curious what opportunities there are for software developers to work around physicists, astronomers, etc. My dream job would be developing software for the scientific community. Certainly there's more money to be made elsewhere, but I like the idea of contributing to the advancement of science and knowledge than deepening somebody else's pockets.

I assume I would need a graduate level education, but I'm wondering if it is worth it to go as far as getting a PhD. I know in the scheme of things I am still young, but it seems most people in the field are finishing their PhD at my age rather than half-way through their undergrad. In any case, I could see myself pursuing a masters at some point, but I don't know what I could specialize in coming from a Computer Science background that would help. Maybe high performance computing?
 
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If you want to get into scientific computing, the biggest hurdle will probably be getting a sufficient background in math and science. In order to write new software applicable to current research, you need to have a solid understanding of what the problem is, what has been done thus far, and what the limitations are for both hardware and current numerical methods.

As an example of some modern big-computing problems, take a look at protein folding. The molecular dynamics of protein molecules is a very difficult simulation for even the fastest super-computers. The software frameworks commonly used are CHARM https://www.charmm.org/charmm/?CFID=ed7f238d-065c-4379-9553-3b71e3299333&CFTOKEN=0 , NAMD http://www.ks.uiuc.edu/Research/namd/ , and MODELLER https://salilab.org/modeller/ . Developing software for scientific computing would generally mean that you would be working to improve platforms and libraries such as these. This means, you would have to understand the math and physics that goes along with these types of problems. No easy task!

If this seems interesting then go for it! Just keep in mind the amount of learning that would come with it.
 

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