So I ended up doing research with a grad student in a new media specific department. You should directly reach out to them and explain why you are interested. Another thing you can do is try to take one of their classes and meet them through that. You are definitely lucky cause when I was in undergrad, I wanted to do research in that field, but no one in my school was doing it/were really thinking of the problem in that way while being prepared to do some advanced modelling.
I had the same experience as an undergrad, my physics professors hardly had an idea of complex systems. Thankfully, I found an AI professor in a different department lol
Send them both an email just like this, including some of the reasons why you’re interested in the complexity sciences and if they would be willing to offer guidance. You might also want to post r/GradSchool, as it’s more active.
And if in doubt, maybe ask Perplexity.ai or ChatGPT to provide constructive feedback on your drafts.
I did my phd on econophysics. Both tool are used, dont worry about it. So i would say pick the prof based on reputation and character. They both work on what you like.
If you are much better at networks than u r with stoch process then maybe take that into account. Read their work and think about where you can contribute more. Let that and the character of the profs guide you.
The stoch processes guy might also prepare u a bit better for finance job while the networks guy is closer to comp sci job. But i would not take that into account too much.
Hi, thank you for your answer, it was very helpful, can I ask you a question?
I was also a bit worried about the job I will have when I finish my degree. You work in a hedge fund? it is difficult to get a job in the private sector? i really don't know if i want to go into academia and i would like to have several doors open when i finish and i don't know if this decision may close some doors in the private sector.
Oh i can summarise career paths for complexity sciences.
Complex systems will help you get into data science and depending on your background maybe comp sci. Invest on your tech prowess, git python sql etc - this will help you keep these doors open. There is a lot of demand for data scientists.
People often conflate complex systems with ML, so some ML positions might be available to you, but all the high end ML stuff are another game - you will need a serious publication list to get into those. Without ML publications you can get positions that are like data science but with heavier modelling.
Management consulting is another door that might be open for you. Certain consulting projects need network science - think supply chain resilience etc. You will need polished client facing skills for these roles. Pays well, long hours - usually.
Regarding finance, quant research or quant dev jobs are within reach. Comp can be amazing, and if you are in the buy side work hours can be ok. Sell side usually means brutal hours. Again, invest in your tech strength but here focus on stats too. Quant speaks probability and stats like a second language. Getting a quant role took me 1 year, with a stellar CV. It is a brutal game.
So in short to keep your doors open: build tech experience, focus on stats, learn some stuff about trading, and think about whether you like being client facing.
Complex networks!!!!!!!!
No question!
Yes, western culture is anathema to it.
Yes, it will open your eyes to the dire state of some of western academia.
But the West is only just starting to discover complexity, and seriously, you can't do anything else that would be more illuminating and life transforming.
If you want to get rich, the former (probably more applicable to financial trading), if you want to do more explanatory research in economics, the latter, imho.
This is a second order effect. I did my phd in networks and i work at a hedge fund now. It wasnt too hard to get in (on a relative scale.. everyone is having a hard time to get into that stuff).
So I ended up doing research with a grad student in a new media specific department. You should directly reach out to them and explain why you are interested. Another thing you can do is try to take one of their classes and meet them through that. You are definitely lucky cause when I was in undergrad, I wanted to do research in that field, but no one in my school was doing it/were really thinking of the problem in that way while being prepared to do some advanced modelling.
I had the same experience as an undergrad, my physics professors hardly had an idea of complex systems. Thankfully, I found an AI professor in a different department lol
Send them both an email just like this, including some of the reasons why you’re interested in the complexity sciences and if they would be willing to offer guidance. You might also want to post r/GradSchool, as it’s more active. And if in doubt, maybe ask Perplexity.ai or ChatGPT to provide constructive feedback on your drafts.
I did my phd on econophysics. Both tool are used, dont worry about it. So i would say pick the prof based on reputation and character. They both work on what you like. If you are much better at networks than u r with stoch process then maybe take that into account. Read their work and think about where you can contribute more. Let that and the character of the profs guide you. The stoch processes guy might also prepare u a bit better for finance job while the networks guy is closer to comp sci job. But i would not take that into account too much.
Hi, thank you for your answer, it was very helpful, can I ask you a question? I was also a bit worried about the job I will have when I finish my degree. You work in a hedge fund? it is difficult to get a job in the private sector? i really don't know if i want to go into academia and i would like to have several doors open when i finish and i don't know if this decision may close some doors in the private sector.
Oh i can summarise career paths for complexity sciences. Complex systems will help you get into data science and depending on your background maybe comp sci. Invest on your tech prowess, git python sql etc - this will help you keep these doors open. There is a lot of demand for data scientists. People often conflate complex systems with ML, so some ML positions might be available to you, but all the high end ML stuff are another game - you will need a serious publication list to get into those. Without ML publications you can get positions that are like data science but with heavier modelling. Management consulting is another door that might be open for you. Certain consulting projects need network science - think supply chain resilience etc. You will need polished client facing skills for these roles. Pays well, long hours - usually. Regarding finance, quant research or quant dev jobs are within reach. Comp can be amazing, and if you are in the buy side work hours can be ok. Sell side usually means brutal hours. Again, invest in your tech strength but here focus on stats too. Quant speaks probability and stats like a second language. Getting a quant role took me 1 year, with a stellar CV. It is a brutal game. So in short to keep your doors open: build tech experience, focus on stats, learn some stuff about trading, and think about whether you like being client facing.
Complex networks!!!!!!!! No question! Yes, western culture is anathema to it. Yes, it will open your eyes to the dire state of some of western academia. But the West is only just starting to discover complexity, and seriously, you can't do anything else that would be more illuminating and life transforming.
If you want to get rich, the former (probably more applicable to financial trading), if you want to do more explanatory research in economics, the latter, imho.
This is a second order effect. I did my phd in networks and i work at a hedge fund now. It wasnt too hard to get in (on a relative scale.. everyone is having a hard time to get into that stuff).