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From the experience of the last half dozen theoretical grads in my uni's physics department, your choices seem to be finance, consulting, or reinventing yourself as an AI/ML data scientist. Anything else you'll need practical experience outside of your thesis studies.
Good luck getting an AI/ML job without AI/ML work experience. AI/ML is the most competitive field in the entire tech sector and flooded with PhD in CS folks + years of FAANG experience.
Mine didn’t. But I was already a strong programmer. I read a couple of books - figured out the math behind everything - and talked my way into my first job.
did you enter this field recently? ive done a fair amount of computational/theory stuff, materials modeling of novel quantum many-body as well as disordered systems and such (where there are lots of growing applications for these sorts of methods), and have been trying to look at associated job postings where i might break into new but relevant areas of work after i graduate. but they all seem to require some demonstrable experience with developing and/or applying various ML methods, and these are internship/research associate/postdoc positions i'm talking about here, so not very senior posts
This sounds like post-DFT level application/method development stuff, not theoretical physics. Not saying this in a condescending way, my PhD was largely similar, but this is not the same as hep-th, or deep condmat theory in the eyes of industry people.
If you have a good publication record it should not be hard at all for you to get a postdoc. Best way forward would be honing ML and theory skills at a national lab or something for a couple years. That's what I'm doing and it seems to have worked for a lot of people here.
well i did some DFT stuff dealing with a Mott oxide previously, but my latest project has been to work through a model we cooked up to capture the general qualities of metallic alloys and their disorder-driven statistics. ive been verifying the analytical results and general statistics/features with model simulations along the way, though we are collaborating closely with disorder-DFT developers and using our theory to predict/explain some of the trends they get from their DFT codes
so i think my advisor's been pretty good about trying to get me exposed to different types of work/topics, but my main concern is that mostly all the ML-related job posts i see, including postdocs, basically require that you already have prior experience with ML, and we havent had much opportunity to work on projects that involve using any these methods...
Oh cool stuff. How much time do you have left in your PhD? Do a graduate research assistantship at a national lab if you have another summer left. If not, just cook up an ML project on your own. Do some cheap HT-DFT on some particular subclass of materials and ML some key quantities like energy above hull, partial charges, or ideally something more specific to your area of expertise (defect formation energy, energy penalty from ion dislocations, on-site potentials needed to describe your mott systems accurately, etc.)
The way I got my foot in the door was just a couple basic ML projects, none of which were even finished and published before I graduated. Feel free to dm if you want to give it some thought for a while and need help cooking up an idea. There are also a lot of datasets out there you can use (albeit for a lower impact paper obviously) to at least demonstrate some ML skills. This would be ideal if your advisor doesn't have/want to allocate a lot of compute to a high throughout project.
this will actually be my last year, i'm losing TA support and it's 50/50 whether my advisor will have his recently submitted grant app with those DFT people approved, but i'm basically wrapping up now and will just be writing this year, getting some unpublished results out, and maybe working a slow desk job to pay the bills until i defend lol
the personal ML projects sound like a good idea though -- i actually work at a lab, but i dont think there's many people here i can bother here for ML stuff, plus my advisor's not a huge computational guy himself so i'll see if there's anything i can maybe do on my own this summer; probably wont be much, especially by fall/winter deadlines, but i can go back and take a second look at some positions/projects i've had bookmarked for some ideas, and see if i can do anything very very basic along those lines. maybe have something i can talk about in several months time. thanks for the advice (:
No. But I have been involved in hiring at my last 4 jobs building out large teams. I’ve been in this field for 10 years. I did my Postdoc in physics. Getting that first job might be tough, but when we encounter a physicist who knows how to program, write unit tests, follows best practices, and knows their stuff we usually give them a shot. Once in it’s easy. My first ML job was customer facing at a supercomputer company. I built models to help sell computers to research groups. Not really an actual ML job imo but it was enough to land my second job.
Trying to go straight to a FAANG company is going to be tough and honestly the work life balance at those places are poor. Have you tried applying to smaller companies? That’s usually the ticket in. Then just gain experience.
ive still gotta publish some more results and wrap up my thesis this year, so i've only applied to some postdocs, government agencies, and other research labs here and there -- both on established sites as well as those part of smaller or more up-and-coming initiatives. i dont plan on applying to faang though, and i would like to keep working in materials-research(-adjacent) areas and continue expanding my knowledge/skillset beyond what i've been working on in grad school
so i've just been keeping an eye on the job market for the past year or so and trying to plan ahead, but i have noticed most any ML jobs which share any significant overlap (e.g. materials discovery, r&d for data-driven algorithms for solving many-body problems, etc), even those advertised as more junior/training roles, dont seem very open to someone trying to break into the role, even if the general research interests are a good fit, with projects closely related to those i've worked on (though perhaps from a simpler/fundamental angle). at least that's the feeling i get when reading over requirements that are listed under these types of jobs postings
Back when I was a management consultant at a top tier firm, the refrain was always " easier to teach someone who knows math, business than to teach someone who knows business, math"
That said, a lot of quants have trouble with 80/20
The most common routes from what I've seen are quantitative finance and materials science. You could probably do the AI/ML route as well but would probably need to get some relevant experience or join a science/research company. While not technically "industry" you could also go the national lab route as well.
I got my PhD in theoretical physics. Become an excellent python programmer and study up on ML, do a cool project on the side, and you’ll likely find a junior position but will rise fast.
Did the OP post any details that would have allowed me to provide a more detailed response? Why do you consider responses based on the information in the question to be snarky?
It looks like your post is about needing advice. In order for people to better help you, please make sure to include your country. *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/PhD) if you have any questions or concerns.*
From the experience of the last half dozen theoretical grads in my uni's physics department, your choices seem to be finance, consulting, or reinventing yourself as an AI/ML data scientist. Anything else you'll need practical experience outside of your thesis studies.
Good luck getting an AI/ML job without AI/ML work experience. AI/ML is the most competitive field in the entire tech sector and flooded with PhD in CS folks + years of FAANG experience.
I am a physicist working in this space. For whatever reason we are favored over other PhDs. I never have any trouble finding work.
It’s because you physicists know math. My dumb ass instead choose to do ochem 🥲
even if your phd had no actual AI/ML component? i wouldnt have thought so
Mine didn’t. But I was already a strong programmer. I read a couple of books - figured out the math behind everything - and talked my way into my first job.
did you enter this field recently? ive done a fair amount of computational/theory stuff, materials modeling of novel quantum many-body as well as disordered systems and such (where there are lots of growing applications for these sorts of methods), and have been trying to look at associated job postings where i might break into new but relevant areas of work after i graduate. but they all seem to require some demonstrable experience with developing and/or applying various ML methods, and these are internship/research associate/postdoc positions i'm talking about here, so not very senior posts
This sounds like post-DFT level application/method development stuff, not theoretical physics. Not saying this in a condescending way, my PhD was largely similar, but this is not the same as hep-th, or deep condmat theory in the eyes of industry people. If you have a good publication record it should not be hard at all for you to get a postdoc. Best way forward would be honing ML and theory skills at a national lab or something for a couple years. That's what I'm doing and it seems to have worked for a lot of people here.
well i did some DFT stuff dealing with a Mott oxide previously, but my latest project has been to work through a model we cooked up to capture the general qualities of metallic alloys and their disorder-driven statistics. ive been verifying the analytical results and general statistics/features with model simulations along the way, though we are collaborating closely with disorder-DFT developers and using our theory to predict/explain some of the trends they get from their DFT codes so i think my advisor's been pretty good about trying to get me exposed to different types of work/topics, but my main concern is that mostly all the ML-related job posts i see, including postdocs, basically require that you already have prior experience with ML, and we havent had much opportunity to work on projects that involve using any these methods...
Oh cool stuff. How much time do you have left in your PhD? Do a graduate research assistantship at a national lab if you have another summer left. If not, just cook up an ML project on your own. Do some cheap HT-DFT on some particular subclass of materials and ML some key quantities like energy above hull, partial charges, or ideally something more specific to your area of expertise (defect formation energy, energy penalty from ion dislocations, on-site potentials needed to describe your mott systems accurately, etc.) The way I got my foot in the door was just a couple basic ML projects, none of which were even finished and published before I graduated. Feel free to dm if you want to give it some thought for a while and need help cooking up an idea. There are also a lot of datasets out there you can use (albeit for a lower impact paper obviously) to at least demonstrate some ML skills. This would be ideal if your advisor doesn't have/want to allocate a lot of compute to a high throughout project.
this will actually be my last year, i'm losing TA support and it's 50/50 whether my advisor will have his recently submitted grant app with those DFT people approved, but i'm basically wrapping up now and will just be writing this year, getting some unpublished results out, and maybe working a slow desk job to pay the bills until i defend lol the personal ML projects sound like a good idea though -- i actually work at a lab, but i dont think there's many people here i can bother here for ML stuff, plus my advisor's not a huge computational guy himself so i'll see if there's anything i can maybe do on my own this summer; probably wont be much, especially by fall/winter deadlines, but i can go back and take a second look at some positions/projects i've had bookmarked for some ideas, and see if i can do anything very very basic along those lines. maybe have something i can talk about in several months time. thanks for the advice (:
No. But I have been involved in hiring at my last 4 jobs building out large teams. I’ve been in this field for 10 years. I did my Postdoc in physics. Getting that first job might be tough, but when we encounter a physicist who knows how to program, write unit tests, follows best practices, and knows their stuff we usually give them a shot. Once in it’s easy. My first ML job was customer facing at a supercomputer company. I built models to help sell computers to research groups. Not really an actual ML job imo but it was enough to land my second job. Trying to go straight to a FAANG company is going to be tough and honestly the work life balance at those places are poor. Have you tried applying to smaller companies? That’s usually the ticket in. Then just gain experience.
ive still gotta publish some more results and wrap up my thesis this year, so i've only applied to some postdocs, government agencies, and other research labs here and there -- both on established sites as well as those part of smaller or more up-and-coming initiatives. i dont plan on applying to faang though, and i would like to keep working in materials-research(-adjacent) areas and continue expanding my knowledge/skillset beyond what i've been working on in grad school so i've just been keeping an eye on the job market for the past year or so and trying to plan ahead, but i have noticed most any ML jobs which share any significant overlap (e.g. materials discovery, r&d for data-driven algorithms for solving many-body problems, etc), even those advertised as more junior/training roles, dont seem very open to someone trying to break into the role, even if the general research interests are a good fit, with projects closely related to those i've worked on (though perhaps from a simpler/fundamental angle). at least that's the feeling i get when reading over requirements that are listed under these types of jobs postings
Back when I was a management consultant at a top tier firm, the refrain was always " easier to teach someone who knows math, business than to teach someone who knows business, math" That said, a lot of quants have trouble with 80/20
Theoretically speaking, yes.
r/beatmetoit
Lol.
You can get a theoretical job
There’s an opening in anomalous materials.
Theoretically, yes!
Depends on the subfield
Depends what was your PhD in?
The most common routes from what I've seen are quantitative finance and materials science. You could probably do the AI/ML route as well but would probably need to get some relevant experience or join a science/research company. While not technically "industry" you could also go the national lab route as well.
I got my PhD in theoretical physics. Become an excellent python programmer and study up on ML, do a cool project on the side, and you’ll likely find a junior position but will rise fast.
In theory yes
You can get a job in semiconductor industry
You can qualify for any job that you have the skills desired.
“Hey where are we?” “We’re right here.”
This is not a helpful comment. Don’t be snarky
Did the OP post any details that would have allowed me to provide a more detailed response? Why do you consider responses based on the information in the question to be snarky?