This is a pretty common career path I think once people realize that finding a well paying physics gig is much much tougher than just becoming a developer. Every physicist has at least some programming experience and are generally adept at problem solving. Coding was always way more fun than doing 4th year/grad school level physics for me too. Also, it is especially tough to get a job if you're a mediocre physicist (like me) whereas there are very many jobs available for fair to middling programmers (like me).
Don't want to guess at numbers but my gut instinct & experience tells me that very few physicists end up doing physics and most end up in finance, software, and hardware.
The American Physical Society maintains numbers on career paths for their student members, and less than 5 percent end up with a Physicist job title. Most end up in the career paths you list.
On average, a tenured physics professor will graduate a bit more than 10 PhD students over the course of their career. Physics as a field is not growing, so at most 10% of PhD students become professors. If you don't become a tenured professor there are very few jobs that aren't postdocs, and even if you wanted to you can't keep doing postdocs forever.
once people realize that finding a well paying physics gig is much much tougher than just becoming a developer.
Unfortunately, becoming a developer is a short-term optimal choice that you pay for in the long term.
The 40-year-old physicist has tenure and can work on whatever he wants. As far as his peers are concerned, he's mid-career. The 40-year-old programmer is considering plastic surgery so he can still get hired in the Valley.
The people who become developers find out that they don't have permission to get a day older than 35 unless they can make it into management. And if you were going to be a manager anyway, you might as well have gotten an MBA in your mid-20s, and then you'd be making far more than the developer would even dream of.
Coding was always way more fun than doing 4th year/grad school level physics for me too.
Programming is a lot of fun, but most software jobs aren't programming intensive. The coding is trivial and a high school student could do most of the work. The hard part is dealing with tickets, PMs, and unnecessary meetings.
Definitely agree with the coding being more fun. I found refactoring my teams messy analysis code much more satisfying than the laborious data analysis + paper writing.
For me it was also that nothing truly new was being discovered in my area of physics, so it all felt a bit boring.
Plus the politics that comes when post docs have to fight and plot over rare tenured positions when they appear.
I'm a physics phd student, but I did my undergrad in cs+physics at well known school in the midwest.
I really regret going to grad school for physics, I gave up a lot of earning potential, time to develop new skills and I've forgotten a lot of my CS background. Most methods in my area have already been developed and the pressure to publish (pushy advisor, several projects not producing the intended results, and proposal writing) has always been hampering away at my free time to think. I really dislike this system. At the same time, I'm sure exists in industry too (never had a real job). I'm not going lie, I feel a bit trapped, but I'm still a fairly positive person.
In the sciences, grad school is sold as a necessity but I'm starting to think this is a way of fueling the ivory tower.
I realize that this is a bit incoherent/ranty, but whatever. :)
You don't have to stay. Look for development jobs or internships for the Fall semester. If you like it more than what you're doing now, don't go back. If you decide that you want to get into the physics, the go back. Plenty of grad students take a semester or two off and go finish their PhDs. If your advisor blows a gasket, well, you can probably do better somewhere else anyway.
I know a lot of graduate students and early professors who have a fear of private industry. I think they all know they can make more money outside of academia, but they don't realize they can work fewer hours and not have worry about a bad tenure committee screwing up their careers. A bad boss can make my work life suck, but he'll need to work hard to completely nuke my career.
Anyway, I understand how you feel. Despite my lackluster GPA, a couple professors want me to go on for a masters in math or statistics. You should see their faces contort when I tell them I don't want to go to graduate school or I don't want a career in academia.
You spent your life in academia, surrounded by people who spent their lives in academia, who have surrounded themselves with people who spent their lives in academia. Get some fresh air, fill your bank account, and then decide.
I was a Physics undergrad+ Physics / Materials Science PhD and I ended up just quitting 4 years into my PhD. You can do it too. You don't owe your advisor anything and you've definitely put in your indentured servitude. I ended up getting a job as a data analyst / scientist and never looked back. You can work on interesting problems, use the same experimental design knowledge and methods, and get paid $100k more than a grad student.
I was 6 months into my PhD in physics - just been given assignment based on obscure Austrian codebase and a quick briefing based on nature article ("Let's discuss when you have something - seeya!") when an opportunity in software came about (a graphics gig - the last thing I wanted to do was write CRUD apps). Never looked back. I was ridiculously underequipped in theoretical as well as practical side beyond linear algebra and C++ but we had a great team and I had the chance to learn quickly.
One thing - if you decide to move to industry, make sure the first years you can learn from someone more talented than you - even if informally. This is critical, software is a craft.
I spent 7 years in grad school, then quit without a PhD. I don't regret it for a minute. I managed to spend 7 years studying topics that interest me, that I will not get to study had I gone straight into industry. Sure, while working you may have some spare time to study some math/physics. But nowhere near at the level you could/did in grad school. There's really no comparison.
If you're not happy in grad school, perhaps:
1. You don't like your research topic.
2. You don't like your advisor.
As an example, I did not have a very pushy advisor, so I learned what I did in a very relaxed manner. Bad idea if I were to end up in academia as a career, but it worked out great for me.
It does suck not finishing the PhD, but once I was in industry, I saw the jobs that most PhDs in my research topic would have ended up with - and most of those jobs are horrible. I worked with them for 4 years, and moved into programming. While the satisfaction of solving really challenging problems is no longer there, the programming job overall really is much better: More autonomy, more creativity, better work schedule, etc.
But bottom line: Grad school is for learning the stuff you are passionate about. If you're not doing that, either change your topic/advisor, or leave.
Don't feel trapped. There are lots of CS experts out there who are competent but have little domain knowledge expertise and therefor limited understanding of what they're writing software for. Just push ahead and see it through until you get bored with it. Being the person around who can write software and understand the underlying physics of this or that problem that you're seeking to model makes a world of difference and is a very valued skill in some fields.
Also a physics PhD student. I never touched CS as un undergrad, but I got very interested in writing software as an undergrad when I started in an experimental HEP group (I've never taken any formal programming courses). I don't completely regret going to grad school even though I often think about the likelihood that I leave physics when I graduate to get a job in software development. I also dislike the academic system - and that's the biggest contributor to that likelihood to leave for the software industry being high. The physics itself is no longer _incredibly_ interesting to me, but I can't shake the data analysis itch ;)
> Most methods in my area have already been developed and the pressure to s/publish/ship (pushy s/advisor/PM, several s/projects/products not producing the intended s/results/sales, and s/proposal/budgets writing) has always been hampering away at my free time to think. I really dislike this system.
Sounds like you have plenty of "real job" experience ;-)
While being a student a physics professor told me:
"Study physics now. Because later when you have a job, you might get paid to learn using some software tool or a new programming language. But no company will ever send you into a quantum mechanics lecture. "
Oddly enough, I received similar advice from my parents, 35 years ago when I started college. This was of course just at the dawn of the personal computer age. My mom was teaching programming at a nearby college, and she literally thought that programming was too easy to spend 4 years learning in the classroom. People were getting programming jobs after one year in her course. Also, nobody had any idea where the industry, or the economy, were headed.
Both of my parents started their careers as scientists in industry after getting graduate degrees in the 50s. They saw people with science background being able to go into practically anything, including programming, business, entrepreneurship, and so forth.
I learned programming in high school, and fell in love with it, but I had an internship at a computer facility, and also looked ahead at the typical CS curriculum. It all seemed terribly boring. So I majored in math and physics. Oddly enough, the people who were doing things with computers, that interested me, were in the physics department. I developed the ability to design computerized electronics for measurement and control systems -- which became my career. This was even before "embedded systems" was widely taught in EE departments.
But realistically, a large portion of the software industry today does not require people with a science background. What I don't know is if I'd still find it boring.
Perhaps my parents' attitude was along the line of "you can do anything with a liberal arts education," but with the stipulation that the liberal arts include math and science.
This migration of physicists to the Silicon Valley and computer industry is not new. It has been true at least since the first big physics employment bubble crashed in the late 1960's, early 1970's. The post-Sputnik boom in physics degrees and grad students produced a huge surplus of physicists by the late 1960's. Dennis Ritchie started at Bell Labs in 1967. Back in the 60's, 70's, early 80's a fair number of physicists decamped for Bell Labs, mostly to work on computer and telecommunications related activities.
A high profile example is Emanuel Derman, author of My Life as a Quant (2004) and later books, who worked at Bell Labs from 1980 to 1985 before moving on to Wall Street. He mentions quite a number of other physicists at Bell Labs at the same time.
Most physicists end up in some sort of software development. The high profile "quant" jobs are actually rather rare and hard to get. The Wall Street firms are typically going after very strong physicists, especially theoretical physicists like Derman.
Nathan Myhrvold of Microsoft and Intellectual Ventures fame (or infamy) has a Ph.D. in theoretical physics from Princeton. Did not go to Wall Street. :-)
The Large Hadron Collider (LHC) produced a huge surplus of experimental particle physics (high energy physics) Ph.D.'s with no jobs in the field. Experimental particle physics involves large amounts of software development for data acquisition, instrument monitoring and control, and data analysis, mostly in C and C++, although there is still some "legacy" FORTRAN software. The heyday of FORTRAN in physics was a long time ago.
Although there have been attempts to use neural networks and other machine learning methods in particle physics, the workhorse of data analysis in the field is Ronald Fisher's maximum likelihood estimation and classification -- primarily estimation of parameters such as the mass and width of the Higgs Boson. The discovery of the Higgs was a maximum likelihood analysis.
Although it is undoubtedly possible to map maximum likelihood onto neural networks, in practice they are different. Neural networks are an attempt to simulate the low level structure of the neurons in the brain and solve problems by brute force fitting of data to models with huge numbers of adjustable parameters. In contrast, maximum likelihood involves attempts to understand the phenomenon under study and model it as a small number of functions corresponding to higher level concepts such as the Higgs Boson. A neural net could exactly fit the Higgs Boson peak yet never produce or confirm a physical model of what causes the peak.
This is a good summary, but we used both machine learning and maximum likelihood to discover the Higgs Boson. The difference is that we frequently use machine learning to identify the (already discovered) particles that the Higgs decays to.
Part of that is because there was only physics and math degrees up to around the 60s. There wasn't really EE or CS, and even when there was, most the professors were originally trained as physicists.
Since the '40s, as the article notes. Early on, science/engineering/math problems were one of the driving forces of computing, typically with a distinct separation from commercial/administrative side — for instance, scientific machines had floating point while commercial machines had decimal arithmetic. It wasn't until the First Dotcom Bubble that the commercial culture decisively ‘won’.
I was ahead of the curve - I did it in 1985. Never used any of the physics, either...
... until 20 years into my career, when I got hired by that medical instruments place that was doing 3D reconstructions of patient anatomy from a series of 2D X-rays. Then it was 3D coordinate transforms, Fourier transforms, some other calculus, plus radiation physics.
A lot of stuff you learn isn't relevant to your career - until it is.
I know a self-taught developer who was specifically getting a degree in physics because of the wide variety of fields that it could allow him to work in. If you insist on getting a degree, degrees in engineering fundamentals like math or physics are probably the best things to target.
Anderson left Harvard before getting his PhD because he came to view the field much as Boykin does—as an intellectual pursuit of diminishing returns. But that’s not the case on the internet. “Implicit in ‘the internet’ is the scope, the coverage of it,” Anderson says. “It makes opportunities are much greater, but it also enriches the challenge space, the problem space. There is intellectual upside.”
Was thinking of pursuing masters/PhD in economics but have heard/read a lot along the same lines of an intellectual pursuit with diminishing returns both in terms of salary and real world impact.
The most useful thing I've done on Twitter is follow a bunch of economists and professors who are constantly debating current econ thinking/papers. There are a few I really respect, but for the most part both the academic environment for PhD level economists seems kind of toxic to me as an outsider.
Been thinking a lot recently about how my generation (I'm 24) is going to have to be a lot more practical due to economic realities...
Whoa! I am actually currently in a physics PhD program, in my last 1-2 years, and have been pursuing internship opportunities for the summer. For me, I've actually wanted to get my PhD in physics and then work in tech for as long as I can remember (so it's not primarily that I feel like the academic job market is too competitive for me, or doesn't pay enough, but those are pretty good reasons, too...) .
I actually have often found it awkward to fit into the usual computer science bins that companies organize projects into. In addition to a hefty amount of data analysis and software engineering, my PhD has required knowledge from a wide variety of different types of engineering, including optics, microwave engineering, and semiconductor fabrication. Combining everything into a 1-page resume, I've found it's not super obvious where my placement would be within most companies. I am currently in the team-matching phase for a google internship, for example, but haven't heard anything.
For those that are getting themselves in the door, do you have any tips?
Wow, too much data science/ machine learning hype into one article. If you are a Physicist that can make machine learning models doesn't that make you a coder also? Furthermore, they give two examples who weren't Computer Science students but I'm sure I can find a counterexample to this.
Physicists are one hell of science and engineering badasses.
I know many physicists who became hardware engineers and even software engineers when they needed it. I know no software/hardware engineer who became physicist.
Depending on what "being a physicist" means, I did. Went from EE undergrad to physics PhD. Then worked in s/w but still tinker on physics projects on the side.
Does anyone else think that general programming education (not necessarily computer science) is overrated?
I much rather hire people that I know can think in both in terms of fundamental logical principles, and who understand the scientific method, which comes up more than one expects in business. For example, I've seen physicists run much better marketing analytics than "growth hackers".
And who cares if someone can cross-off a list of generic programming language/frameworks? If you need that specific of a cog in your machine, the position probably isn't that innovative and you're better off outsourcing. Or hire someone smart and eager, pay them decently, and they'll learn what they need, if they're so inclined.
I'm studying physics because I want to help shed light on the mysteries of reality.
It might be hard to get a job in physics and achieve that, but it's a hell of a lot harder to get in a job in software development and achieve that.
Despite this, all I'm reading is optimism about how well-paying and interesting software development is for physicists. So what? If those were my primary concerns, I wouldn't have studied physics in the first place!
I get the hidden impression that the meaningfulness of science -- pursuing the truth, the nature of the universe -- is being swept under the rug because it's no longer paying the bills. That's a goddamn tragedy, not the cause for celebration this article is making it out to be.
There was a time before computer science degrees existed. Guess who were some the first folks to use computers and pioneer our field? Physicists and mathematicians!
Anecdata: As a software engineer who studied physics before C.S., it feels like I've had a massively unfair advantage my entire career. Served me very well.
I'm working on a Masters in CS right now and have been interested in heading into some form of 'Data Science', whatever that may entail.
Does this mean that only physics/math/stats majors are getting into this field? At my current place of employment this is the case for the data scientists; all have an academic background in one of these three fields, all have a Masters or PhD. I assumed this was because the head data scientist had a long history with academia and thus had a predilection for academics.
From my experience the data science concepts I have encountered thus-far seem pretty straightforward and I suspect that people are trying to make these concepts seem more difficult/arcane than they are by using notations/concepts only learned in academia. Am I wrong here? Is it actually a field which requires a PhD in Math to understand? My exposure has only been with toy examples (logistic regression, simple perceptrons, similarity algorithms, etc). How easy is it to get into the field without a heavy academic background?
move over javascript, matlab will soon rule silicon valley!
edit: this is just a tongue in cheek comment that physicists will rule silicon valley with about the same chance of success matlab will be used for enterprise dev.
Doesn't really seem like the author spoke to a lot of actual physicists to write this article. Don't get me wrong, physics majors attract a certain type of intellect, but the vast majority of curriculum (quantum, EM, mechanics) are things THAT HAVE BARELY CHANGED IN THE PAST 50 YEARS. Meanwhile, CS majors come out much more prepared and hirable on the job market.
As far as the machine learning market goes, 90% of the projects require software engineering skills, the last 10% requires being able to go underneath the covers of linear algebra libraries, etc.
I just think the whole physics>cs degree for machine learning argument is not totally persuasive given my experience.
How is the notion that "the vast majority of curriculum (quantum, EM, mechanics) are things THAT HAVE BARELY CHANGED IN THE PAST 50 YEARS" relevant to this discussion?
Considering how competitive physics graduate programs are at top schools it is a shame to hear that so few are pursuing careers in physics and some appear to be calculating in advance their move to CS. I love CS but if I had a passion for physics I would be pissed to see someone that society, schools, mentors, peers have invested in to do physics go be quant at an investment bank. It is not that working for a bank is intrinsically bad, more the case that individuals should consider the opportunity they may have been taking from others in pursuing a specialized education they subsequently don't use.
I myself have only a CS background (BSc + MSc in CS), and I am working in IT for last 8 years. Initially, I used to have negative opinion towards people from other non-CS backgrounds able to get jobs as Software Engineers and as IT Managers/Directors.
Now for the past 5 years, I am highly appreciative of such people because each of them bring knowledge and interesting viewpoints from their respective academic/training backgrounds which serves to enrich the IT world. Thank you guys :-)
> In other words, all the physicists pushing into the realm of the Silicon Valley engineer is a sign of a much bigger change to come.
So this article comes all the way to this. Is there data that hiring of physicists speeded up in the recent years? And why roles they are taken? Presumably not all in machine learning, if I have to guess.
Until then, this is another effort to turn an otherwise good interview into an unsubstantiated editorial aiming for nothing but hype.
[+] [-] randlet|9 years ago|reply
Don't want to guess at numbers but my gut instinct & experience tells me that very few physicists end up doing physics and most end up in finance, software, and hardware.
[+] [-] jschwartzi|9 years ago|reply
[+] [-] throw_away_777|9 years ago|reply
[+] [-] atmaweapon|9 years ago|reply
Unfortunately, becoming a developer is a short-term optimal choice that you pay for in the long term.
The 40-year-old physicist has tenure and can work on whatever he wants. As far as his peers are concerned, he's mid-career. The 40-year-old programmer is considering plastic surgery so he can still get hired in the Valley.
The people who become developers find out that they don't have permission to get a day older than 35 unless they can make it into management. And if you were going to be a manager anyway, you might as well have gotten an MBA in your mid-20s, and then you'd be making far more than the developer would even dream of.
Coding was always way more fun than doing 4th year/grad school level physics for me too.
Programming is a lot of fun, but most software jobs aren't programming intensive. The coding is trivial and a high school student could do most of the work. The hard part is dealing with tickets, PMs, and unnecessary meetings.
[+] [-] walrus1066|9 years ago|reply
For me it was also that nothing truly new was being discovered in my area of physics, so it all felt a bit boring.
Plus the politics that comes when post docs have to fight and plot over rare tenured positions when they appear.
[+] [-] tmoot|9 years ago|reply
I really regret going to grad school for physics, I gave up a lot of earning potential, time to develop new skills and I've forgotten a lot of my CS background. Most methods in my area have already been developed and the pressure to publish (pushy advisor, several projects not producing the intended results, and proposal writing) has always been hampering away at my free time to think. I really dislike this system. At the same time, I'm sure exists in industry too (never had a real job). I'm not going lie, I feel a bit trapped, but I'm still a fairly positive person.
In the sciences, grad school is sold as a necessity but I'm starting to think this is a way of fueling the ivory tower.
I realize that this is a bit incoherent/ranty, but whatever. :)
[+] [-] StClaire|9 years ago|reply
I know a lot of graduate students and early professors who have a fear of private industry. I think they all know they can make more money outside of academia, but they don't realize they can work fewer hours and not have worry about a bad tenure committee screwing up their careers. A bad boss can make my work life suck, but he'll need to work hard to completely nuke my career.
Anyway, I understand how you feel. Despite my lackluster GPA, a couple professors want me to go on for a masters in math or statistics. You should see their faces contort when I tell them I don't want to go to graduate school or I don't want a career in academia.
You spent your life in academia, surrounded by people who spent their lives in academia, who have surrounded themselves with people who spent their lives in academia. Get some fresh air, fill your bank account, and then decide.
[+] [-] physcab|9 years ago|reply
[+] [-] fsloth|9 years ago|reply
One thing - if you decide to move to industry, make sure the first years you can learn from someone more talented than you - even if informally. This is critical, software is a craft.
[+] [-] BeetleB|9 years ago|reply
I spent 7 years in grad school, then quit without a PhD. I don't regret it for a minute. I managed to spend 7 years studying topics that interest me, that I will not get to study had I gone straight into industry. Sure, while working you may have some spare time to study some math/physics. But nowhere near at the level you could/did in grad school. There's really no comparison.
If you're not happy in grad school, perhaps:
1. You don't like your research topic.
2. You don't like your advisor.
As an example, I did not have a very pushy advisor, so I learned what I did in a very relaxed manner. Bad idea if I were to end up in academia as a career, but it worked out great for me.
It does suck not finishing the PhD, but once I was in industry, I saw the jobs that most PhDs in my research topic would have ended up with - and most of those jobs are horrible. I worked with them for 4 years, and moved into programming. While the satisfaction of solving really challenging problems is no longer there, the programming job overall really is much better: More autonomy, more creativity, better work schedule, etc.
But bottom line: Grad school is for learning the stuff you are passionate about. If you're not doing that, either change your topic/advisor, or leave.
[+] [-] ddebernardy|9 years ago|reply
[+] [-] avn2109|9 years ago|reply
[+] [-] ddavis|9 years ago|reply
[+] [-] tossractt999|9 years ago|reply
Sounds like you have plenty of "real job" experience ;-)
[+] [-] amai|9 years ago|reply
"Study physics now. Because later when you have a job, you might get paid to learn using some software tool or a new programming language. But no company will ever send you into a quantum mechanics lecture. "
He was right.
[+] [-] analog31|9 years ago|reply
Both of my parents started their careers as scientists in industry after getting graduate degrees in the 50s. They saw people with science background being able to go into practically anything, including programming, business, entrepreneurship, and so forth.
I learned programming in high school, and fell in love with it, but I had an internship at a computer facility, and also looked ahead at the typical CS curriculum. It all seemed terribly boring. So I majored in math and physics. Oddly enough, the people who were doing things with computers, that interested me, were in the physics department. I developed the ability to design computerized electronics for measurement and control systems -- which became my career. This was even before "embedded systems" was widely taught in EE departments.
But realistically, a large portion of the software industry today does not require people with a science background. What I don't know is if I'd still find it boring.
Perhaps my parents' attitude was along the line of "you can do anything with a liberal arts education," but with the stipulation that the liberal arts include math and science.
[+] [-] santaclaus|9 years ago|reply
I bet D-Wave has some interesting quantum mechanics lectures!
[+] [-] Camillo|9 years ago|reply
[+] [-] throwaway61AR|9 years ago|reply
[+] [-] NumberSix|9 years ago|reply
A high profile example is Emanuel Derman, author of My Life as a Quant (2004) and later books, who worked at Bell Labs from 1980 to 1985 before moving on to Wall Street. He mentions quite a number of other physicists at Bell Labs at the same time.
Most physicists end up in some sort of software development. The high profile "quant" jobs are actually rather rare and hard to get. The Wall Street firms are typically going after very strong physicists, especially theoretical physicists like Derman.
Nathan Myhrvold of Microsoft and Intellectual Ventures fame (or infamy) has a Ph.D. in theoretical physics from Princeton. Did not go to Wall Street. :-)
The Large Hadron Collider (LHC) produced a huge surplus of experimental particle physics (high energy physics) Ph.D.'s with no jobs in the field. Experimental particle physics involves large amounts of software development for data acquisition, instrument monitoring and control, and data analysis, mostly in C and C++, although there is still some "legacy" FORTRAN software. The heyday of FORTRAN in physics was a long time ago.
Although there have been attempts to use neural networks and other machine learning methods in particle physics, the workhorse of data analysis in the field is Ronald Fisher's maximum likelihood estimation and classification -- primarily estimation of parameters such as the mass and width of the Higgs Boson. The discovery of the Higgs was a maximum likelihood analysis.
Although it is undoubtedly possible to map maximum likelihood onto neural networks, in practice they are different. Neural networks are an attempt to simulate the low level structure of the neurons in the brain and solve problems by brute force fitting of data to models with huge numbers of adjustable parameters. In contrast, maximum likelihood involves attempts to understand the phenomenon under study and model it as a small number of functions corresponding to higher level concepts such as the Higgs Boson. A neural net could exactly fit the Higgs Boson peak yet never produce or confirm a physical model of what causes the peak.
[+] [-] dguest|9 years ago|reply
[+] [-] batbomb|9 years ago|reply
[+] [-] andrepd|9 years ago|reply
Ahh, how I wish that were true...
[+] [-] KKKKkkkk1|9 years ago|reply
[+] [-] circlefavshape|9 years ago|reply
Degree in physics, working software for 20 years and still feel like an impostor ... not that I remember any physics at this stage
[+] [-] kps|9 years ago|reply
[+] [-] AnimalMuppet|9 years ago|reply
... until 20 years into my career, when I got hired by that medical instruments place that was doing 3D reconstructions of patient anatomy from a series of 2D X-rays. Then it was 3D coordinate transforms, Fourier transforms, some other calculus, plus radiation physics.
A lot of stuff you learn isn't relevant to your career - until it is.
[+] [-] cookiecaper|9 years ago|reply
[+] [-] roymurdock|9 years ago|reply
Was thinking of pursuing masters/PhD in economics but have heard/read a lot along the same lines of an intellectual pursuit with diminishing returns both in terms of salary and real world impact.
The most useful thing I've done on Twitter is follow a bunch of economists and professors who are constantly debating current econ thinking/papers. There are a few I really respect, but for the most part both the academic environment for PhD level economists seems kind of toxic to me as an outsider.
Been thinking a lot recently about how my generation (I'm 24) is going to have to be a lot more practical due to economic realities...
[+] [-] asafira|9 years ago|reply
I actually have often found it awkward to fit into the usual computer science bins that companies organize projects into. In addition to a hefty amount of data analysis and software engineering, my PhD has required knowledge from a wide variety of different types of engineering, including optics, microwave engineering, and semiconductor fabrication. Combining everything into a 1-page resume, I've found it's not super obvious where my placement would be within most companies. I am currently in the team-matching phase for a google internship, for example, but haven't heard anything.
For those that are getting themselves in the door, do you have any tips?
[+] [-] zitterbewegung|9 years ago|reply
[+] [-] thesz|9 years ago|reply
I know many physicists who became hardware engineers and even software engineers when they needed it. I know no software/hardware engineer who became physicist.
[+] [-] musgravepeter|9 years ago|reply
GRTensorIII (https://gitlab.com/grtensor/grtensor/wikis/home)
An iOS/Android app for Three Body simulations (Three Body) and a Unity gravity simulator (Gravity Engine).
I would have loved to make a living wage in physics but the post-doc path is badly paid.
[+] [-] adrianN|9 years ago|reply
[+] [-] mac01021|9 years ago|reply
For many, it's because they never needed it.
[+] [-] madengr|9 years ago|reply
Sure, due to the premise of the article; no pay in it.
[+] [-] BeetleB|9 years ago|reply
[+] [-] zxcvvcxz|9 years ago|reply
I much rather hire people that I know can think in both in terms of fundamental logical principles, and who understand the scientific method, which comes up more than one expects in business. For example, I've seen physicists run much better marketing analytics than "growth hackers".
And who cares if someone can cross-off a list of generic programming language/frameworks? If you need that specific of a cog in your machine, the position probably isn't that innovative and you're better off outsourcing. Or hire someone smart and eager, pay them decently, and they'll learn what they need, if they're so inclined.
[+] [-] ExcessiveAccts|9 years ago|reply
I'm studying physics because I want to help shed light on the mysteries of reality.
It might be hard to get a job in physics and achieve that, but it's a hell of a lot harder to get in a job in software development and achieve that.
Despite this, all I'm reading is optimism about how well-paying and interesting software development is for physicists. So what? If those were my primary concerns, I wouldn't have studied physics in the first place!
I get the hidden impression that the meaningfulness of science -- pursuing the truth, the nature of the universe -- is being swept under the rug because it's no longer paying the bills. That's a goddamn tragedy, not the cause for celebration this article is making it out to be.
[+] [-] emcq|9 years ago|reply
Von Neumann, Feynman, Metropolis, Vapnik, Babagge, Lovelace, Turing, Church, Hopper, Brooks...
[+] [-] redsymbol|9 years ago|reply
[+] [-] rubidium|9 years ago|reply
AIP does many nice studies of where physics PhD's end up.
One of the hardest challenge as a Physics PhD in industry is finding interesting problems. See fig 2.2 for reporting on that: https://www.aip.org/sites/default/files/statistics/phd-plus-...
[+] [-] renlo|9 years ago|reply
Does this mean that only physics/math/stats majors are getting into this field? At my current place of employment this is the case for the data scientists; all have an academic background in one of these three fields, all have a Masters or PhD. I assumed this was because the head data scientist had a long history with academia and thus had a predilection for academics.
From my experience the data science concepts I have encountered thus-far seem pretty straightforward and I suspect that people are trying to make these concepts seem more difficult/arcane than they are by using notations/concepts only learned in academia. Am I wrong here? Is it actually a field which requires a PhD in Math to understand? My exposure has only been with toy examples (logistic regression, simple perceptrons, similarity algorithms, etc). How easy is it to get into the field without a heavy academic background?
[+] [-] princeb|9 years ago|reply
edit: this is just a tongue in cheek comment that physicists will rule silicon valley with about the same chance of success matlab will be used for enterprise dev.
[+] [-] elliott34|9 years ago|reply
As far as the machine learning market goes, 90% of the projects require software engineering skills, the last 10% requires being able to go underneath the covers of linear algebra libraries, etc.
I just think the whole physics>cs degree for machine learning argument is not totally persuasive given my experience.
[+] [-] woah|9 years ago|reply
[+] [-] vitaminbandit|9 years ago|reply
[+] [-] bondolo|9 years ago|reply
[+] [-] m23khan|9 years ago|reply
Now for the past 5 years, I am highly appreciative of such people because each of them bring knowledge and interesting viewpoints from their respective academic/training backgrounds which serves to enrich the IT world. Thank you guys :-)
[+] [-] eva1984|9 years ago|reply
So this article comes all the way to this. Is there data that hiring of physicists speeded up in the recent years? And why roles they are taken? Presumably not all in machine learning, if I have to guess.
Until then, this is another effort to turn an otherwise good interview into an unsubstantiated editorial aiming for nothing but hype.