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Now I'm doing aerospace vehicle modeling and simulation in MATLAB and C++ and primarily work with other physicists. This is by far the most enjoyable work I've done and the pay is excellent - my salary is 3-4x the average household income for the city I live in.
While my PhD did start out as supposedly being on Spin Glasses it quickly diverged to Complex Networks and what people would now call Data Science. Since then, I've worked on Social Science, Epidemiology, Human Behavior, etc... For the last year or so, I've been doing Data Science and Finance in one of the Big Banks.
Academic trends are ruled by money. In theoretical physics, computer simulations is where the money is. For the students, that means they are doing computer science related work, frequently the physics part is lacking. The route to leaving physics and using the data science capabilities is then a straightforward one.
This kind of reminds me of what Jeff Hawkins once claimed was the issue with making sense of how the brain works: > So why don't we have a good theory of brains? People have been working on it for 100 years. Let's first take a look at what normal science looks like. This is normal science. Normal science is a nice balance between theory and experimentalists. The theorist guy says, "I think this is what's going on," t…
Most parts of the Standard Model are verified to 5σ at all energy levels that are accessible to us in everyday life and in contemporary particle accelerators, so it's increasingly unlikely that we've missed any obvious mechanisms.
If we're going to find some completely new physics (in the same way that quantum theory and relativity theory were completely new at the turn of the 20th century), it's probably going to be at energy levels that contemporary particle accelerators cannot yet explore.
EDIT: That's not to say that we know everything that is to know about the accessible energy levels. There's so much in our theory that's yet unexplained, e.g. for all I know, we still don't have any idea why time works the way it does.
Working on my thesis analysis (collider based HEP), squeezing in time for OSS development and prepping for a jump to software dev.
I love physics, but academia is in a rough place right now. Almost everyone I know pursuing the academic career path has nightmare stories.
Academic trends are ruled by money. In theoretical physics, computer simulations is where the money is. For the students, that means they are doing computer science related work, frequently the physics part is lacking. The route to leaving physics and using the data science capabilities is then a straightforward one.
This kind of reminds me of what Jeff Hawkins once claimed was the issue with making sense of how the brain works: > So why don't we have a good theory of brains? People have been working on it for 100 years. Let's first take a look at what normal science looks like. This is normal science. Normal science is a nice balance between theory and experimentalists. The theorist guy says, "I think this is what's going on," t…
The reason for is just how damn good all the Physics Theory is. People keep having to look closer and closer to try to find a place, any place, where the theory "fails" (in a sufficiently spectacular fashion) hoping that that might point the way to new phenomena and new theory. There's a giant multibillion dollar hole on the ground in Switzerland who's main purpose was to find a chink in the armor of HEP or help point the way to new theories. It failed spectacularly, but they're already talking about building a bigger one :)
Though theory groups in general tend to use computational simulations as a tool to complete calculations, groups that develop novel computational methods and techniques tend to be headed by younger, more junior professors. These groups are typically well-funded and do very exciting (trendy? cutting edge?) work with distributed computation, machine learning, neural networks, etc, so they tend to pull quite a few students.
While these computational groups tend to bring in funding and are well-staffed by excited grad students, the junior professors leading them tend to be marginalized by the more traditional, seniority-focused establishment. Which is to say, a new PhD might have a lot of trouble landing a prestigious postdoc because a) their adviser might have been too young to have high name recognition outside their field and b) departments might place limits the amount of staff for these more junior professors/young groups doing exciting computational work. This is, of course, on top of the overall scarcity of jobs in academia.
But there's no such job scarcity in industry-- especially not for stats-smart programmers with years of experience a) wrangling data in python, b) writing fortran that runs on distributed clusters, or c) designing algorithms to solve /approximate hilariously expensive problems. Advisers know this and point some of their students who might thrive more in industry than academia towards that route.
(Anecdote: And of course, as a physicist who builds models/simulations in industry, I can speak a personally a little re: thriving. If you're someone in love with solving disparate problems, you're unlikely to find that in academia. Some of us learn in graduate school that we can't spend our whole lives-- or in my case, more than a few months-- solving one problem. Academia just... didn't seem like something that would be worth fighting for.)
I assume that this will gradually change as there's turnover within physics departments and we get more computational-first professors with seniority (or even in leadership). There are a few departments with better-known professors you can see it happening now. Universities are spinning up incubators and institutes for computational research. Physics departments are just slower to adapt to new developments, and the hierarchy of theorists can have more to do with seniority and internal politics than it does with technology.
The reason was I sucked in physics, did not find my PhD position motivating and loved computer graphics.
13 years later I'm a valued technical contributor in a team in an ISV creating a valuable global software packages in the CAD field.
Middle class income, could probably make lot more in US with my skillset but family situation really is not awesome for expatriation.
I'm doing OK.
With physics skillset you can pretty much make your career what you want it to be. You just need a proactive attitude to read on other fields. You need to understand the other guys mindset so you understand the overall game going on. It's usually not nefarious (although it can be), but most of the time the rules that are used are not the vocalized ones. In this empirical physics is a wonderfull philosophical background. Organizations have certain dynamic rules which half of the people are not aware of. You don't need to "play the game", but you need to understand the rules so that when the wind blows into the direction you want to go into you can grab the opportunity.
I had a pretty good idea where I wanted to be 13 years ago (R&D in a position that values quality over quantity and speed with a great team) and that's pretty much where I am now.
You need to know where you want to go, and go there. No one will guide your path. Physicists are an outlier but that math and mindset is really an asset. Just don't get stuck in fixing bugs in some legacy monstrosity, that is absolutely soul crushing. But such a position can function as a stepping stone if you are operating in the industry you want to work in.
Earlier quoted context omitted.
My first degree was in physics as well, and I also ended up in IT. At SAP, to be exact. Urban legend among German SAP employees has it that SAP expands to "Sammelplatz arbeitsloser Physiker" (gathering place for unemployed physicists).
I know a few people at SAP (NL/DE) who are overqualified for the job they are doing and seem bored/uninterested. What's an insiders perspective of this?
Then again, I guess I value stability and predictability in my day job a bit more than most Silicon Valley startup employees.