Ask HN: Physicists of HN, what are you working on these days?

(PhD, 1996 in general relativity)

Embedded graphics drivers for real-time systems.

I keep the physics part of my brain alive by developing physics based Unity assets (nbodyphysics.com) and supporting a package for GR on github (grtensor).

I still buy WAY too many physics books. Current aspiration is to work through “Modern Classical Physics” Thorne/Blandford.

When I got my PhD (1999) the American Physical Society said that you had a 2% chance of getting a permanent job in the field with a PhD. At that point you are not being judged on your merits but on your connections, ability to navigate politics, etc. (The job is way too valuable compared to the value you can give to it.)

I saw a postdoc who is now rather well known struggling with anxiety over his career even though he had written half a book and done a lot of great work. When we were both at Cornell I’d come to the conclusion that many papers involving “power law” distributions were bogus because nobody knew how to test for them with any rigor. It was years later, after he had tenure, that he published something about it in a statistics journal.

Seeing that made me run for the exit after my first year as a postdoc.

> I’d come to the conclusion that many papers involving “power law” distributions were bogus

> after he had tenure, that he published something about it in a statistics journal

If I’m reading you right, you’re saying he struggled for awhile doing bogus things only to question those things outside the relevant field?

(Also, can you say more about power law papers..?)

I read the comment as implying that the colleague had published a paper on power law distributions in order to publish (pressure) while the poster knew that the colleague did not believe in the subject.

I did my undergraduate in Aerospace Engineering and Astrophysics, then graduate work in Space Systems Engineering and regular Systems Engineering. I also did plasma physics research at Princeton.

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.

(PhD, 2008 in Complex Systems)

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.

I work with a few PhD physicists, one is a technical program manager in applied optics and ML; one is an individual contributor in optics and ML, and the other one is pretty straight stick ML. I bailed on physics after my bachelor’s, ended up in medicine and now … work in ML, with them. I don’t think I ever heard anyone tell me, or any of my classmates “you should get a PhD in physics”. It was something one did to do it. Because it’s there. But even 20 years ago, the guidance was to look for jobs in finance or computers.

>20 years ago, the guidance was to look for jobs in finance or computers

It was 2003 when the company I was working for acquired InterBiz from Computer Associates. By the time we were integrating teams from both companies I met this guy who were the guru, the #1 product manager from one of the most profitable lines of business that the company had. I remember the shock in people’s faces when he, a Portuguese guy, said he’s got a PhD in Physics, in Germany, in a second language to his own, but then ended up developing Warehouse Management Systems (WMS).

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,” the experimentalist says, “You’re wrong.” It goes back and forth, this works in physics, this in geology.

> But if this is normal science, what does neuroscience look like? This is what neuroscience looks like. We have this mountain of data, which is anatomy, physiology and behavior. You can’t imagine how much detail we know about brains. There were 28,000 people who went to the neuroscience conference this year, and every one of them is doing research in brains. A lot of data, but no theory. There’s a little wimpy box on top there.

Not that physics has no theories, but I dropped out of studying physics myself over a decade ago, and at that time it felt a lot like the balance in physics has shifted towards having to measure and process disproportionate amounts of data with so much precision that has to be automated, or like you said do a ton of really complicated modelling. It feels a bit “stuck” that way.

[0] https://www.ted.com/talks/jeff_hawkins_on_how_brain_science_…

I think you’re seeing this in physics because, in terms of experimental accessibility, the low-hanging fruit are mostly picked.

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.

Is it really bad that most time is invested in simulations? Seems like a very potent low-hanging fruit (not to mention how many cool things could come out of it).

I have a degree in physics and work as a software dev (c++). No one cares for physics in the industry, but it’s indirectly taken as a sign that people aren’t morons. I never used anything I learned at university at work. About half of my colleagues have physics or Math degrees, other half EE or CS.

I’m not a physicist but studied physics before jumping to programming.

A surprising amount of people whom I studied with ended up as programmers themselves, after finishing the physics degree.

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?

I worked in numrel before and was even offered a tenure track job focused on teaching. I didn’t want to work 70 hour weeks though. Now I focus on my family and data pipelines seem like a nice hobby.

I am about to defend my thesis in physics and will probably start a data science job afterwards (have had a few second round interviews, waiting for offers/rejections). Note that my thesis work did not contain big data or machine learning, but I have completed a couple of outside projects. I am in the US and in a top tier university/program.

My perspective is that there is just not many academic positions available. I realized I could do a couple of post docs for a few years and hope that something opens up, or not delay the most probable outcome and start an industry career sooner rather than later.

When I still pursued my PhD in physics, I worked on all-optical amplifiers with phase noise reduction for fiber communication.

Now I develop software for a medium-sized ISP and IT outsourcing company.