I wanna take the chance asking this question while having so many physicists present in this sub: is the 'first principle thinking' approach to problem-solving somewhat helpful outside academia? Is it a thing in the first place? Seems super interesting as a non-physicist, however it's hard to judge from the outside. Thanks for some insights.
It is for me. Product development and technology development with a deep understanding of thermodynamics and energy efficiency can be valuable. Heat kills a lot of things :)
(PhD 2010 in Nuclear Physics) I stayed in Academia, right now I'm trying to survive the first year as an Assistant Professor. Teaching is a lot more fun than I thought it would be. My research is two fold: One half of my research is focused on precision measurements of the proton form factors (proton radius puzzle, form factor ratio puzzle), the other half on streaming readout for next-gen experiments.
Interesting research... I hadn't given much consideration to the interior structure of protons and neutrons before.
So I work in experimental particle physics and our daily tasks involve using particle collision simulation tools(mg5+pythia+delphes), distribute them on clusters, construct jet images using ROOT and finally experiment with neural networks on those jet images. So as people pointed out, what we do had a lot in common with the industry (where we learn from as well), which explains why many people involved in this kind o…
Any tips for a hobbyist who needs to do some simulations of a novel device? Much of what I've looked at requires writing a lot of the simulation code from scratch.
To be entirely fair, people not educated in physics would likely have a very hard time at your job because we don't know the terminology or what makes sense for your field. If I tried to do what you do, I'd likely have no clue what half of the pigeon-scratch is because I flat out do not even know what the words or concepts are.
That's a fair point. Still, I feel I could take any of my students and in one month have them up to speed on what to look for and what things mean. And I don't mean to suggest that finding challenging work is any sort of failing of my employer. I have been able to diversify the position to include doing graphics in R and some stats things and, along with some other people, I think we can sell some sexy Bayesian thing…
I think you could swing some academic or national lab position if you put some time into it.
Is there anything even tangentially related to your dayjob that you could mine for ideas? Or maybe take some time to come up with some research direction?
A places like Oak Ridge could have something interesting available.
(PhD 2010 in Nuclear Physics) I stayed in Academia, right now I'm trying to survive the first year as an Assistant Professor. Teaching is a lot more fun than I thought it would be. My research is two fold: One half of my research is focused on precision measurements of the proton form factors (proton radius puzzle, form factor ratio puzzle), the other half on streaming readout for next-gen experiments.
Interesting research... I hadn't given much consideration to the interior structure of protons and neutrons before.
It is! If you look around you, essentially all the mass you see is generated dynamically by QCD inside the nucleons. And while we believe we can write down all the rules for QCD, we can not solve the equations well enough that we can reliably predict outcomes (emergent properties, like the masses, size etc), except if we do lattice QCD, which is essentially a brute-force numerical solution.
Condensed matter physics PhD (2016) now working in the software industry as a data scientist. Focused on modelling/simulating materials during my thesis and realized that I loved the software aspect of things and did not love working on the same problem for many months at a time. As others mentioned, transitioning to data science is not that hard if you have a physics background and there are many interesting problem…
The two body problem (2 professionals in academia finding jobs close to each other, for some value of close that is reasonable for daily life) is famous in science in general. It is, unless one of you has a Nobel Prize, unsolvable without one person making a change of career.
I think many places have seen this problem and are actively trying to solve it. I know several spousal hires.
(Current PhD Student) Although the case for building new and more powerful hadron accelerators doesn't look good, accelerator physics is flourishing with other types of machines. Particularly interesting to me is ultrafast electron diffraction (UED)[1,2]. UED is cool because you can create atomic resolution movies with speeds that can (in the near future) resolve chemical reactions as they occur. (eg. imagine being a…
I was recently reading about single pixel cameras and went further deep into UED cameras. The promise of what potentials they can unlock is amazing.
I currently work on the software that runs Google's quantum computers. To paraphrase the Talking Heads: How did I get there? PhD 2001 in physics, working on quantum computation. Postdocs at Caltech and Santa Fe Institute, then landed a research faculty position at the University of Washington. Yeah, raise your own funds! Jumped ship in 2011 (burnout, quality of life, university not caring about quantum computing) and…
> I run the team that builds software for Google's quantum computers
Is there any significant difference to payscale and hierarchical autonomy in these non AI research teams? I am assuming distributed privacy preserving ML team (is this team close to federated learning one?) also falls under more non AI research teams right?
I'm not a physicist, but a physics drop-out. However, I am still in touch with many of the people I studied with. Only a few stayed in physics in the end. One thing I noticed is that because physics has multiple decades more experience with dealing with big data compared to just about every other scientific field, a lot of physicists who jump ship tend to end up in a position where they can apply that expertise. I wo…
BioPhysics was all the rage in my university few years ago. I haven't heard much after, but genetics and big data have been at the forefront for a while now. There have been a bunch of recent YC companies in this intersection as well.
Got a PhD from the University of Toronto, went straight into founding a company. Went through YC last year (W18). If I could do it over again, I'd have dropped out of grad school in Year 1. As an aside - there are way more physicists on HN than I expected.
> If I could do it over again, I'd have dropped out of grad school in Year 1.
Haha. I can see how you are trying to take on the current education system itself. To some extent, the education system has failed us to some extent.