Every time I speak to someone with a PhD at work (I work in top 10 tech companies in US), in 100% of the cases in my experience do not engage in anything related to their thesis.
So why is there this arbitrary blockade for having a PhD in R&D/Labs?
Every time I speak to someone with a PhD at work (I work in top 10 tech companies in US), in 100% of the cases in my experience do not engage in anything related to their thesis.
So why is there this arbitrary blockade for having a PhD in R&D/Labs?
This is missing the point of a PhD, which is to develop a capacity for doing science (or more generally hard thinking in relevant domain). Most of my colleagues in neuroscience are physicists
These days, it is more about the ability to publish. A few weeks ago I had a conversation with a friend of mine who is wrapping up his PhD. He pointed out that not one of his colleagues is concerned whether anyone can reproduce their work. They use a home grown simulation suite which only they have access to, and is constantly being updated with the worst software practices you can think of. No one in their team believes that the tool will give the same results they did 4 years ago. The troubling part is, no one sees that as being a problem. They got their papers published, and so the SW did its job.
(Should not be surprising to anyone who spends a lot of time in engineering PhD programs).
One interpretation of science is just making theories and testing them with experiments, no solid software engineering required. Another says reproducibility is important but the current incentive structure is not there yet.
There's such a shortage of STEM graduates that PhDs get hired to do stuff you can actually do with a MOOC (or to carry a pager at Google).
Just like how people check out your GitHub repository to see if you are a capable coder, people check out your refereed publication record to determine if you can do research. It's possible to build up a record of publications without a PhD, but it is a hard skill to acquire on your own.
I say this because most applied research is not done in a manner that would meed any kind of academic standards.
When you look at this history of the Valley, it has more to do with dropouts than PhDs - rather, it has more to do with 'those doing' than 'getting credentials'.
I almost feel that for the most part PhDs belong in Academia, and that whatever high-end work we do in industry should be called something else.
Having a PhD should mean that the person is capable of making consistent progress in ill-defined problems without much external support. Of course not all PhDs can do this, and you don't need a PhD to gain these skills, but they correlate strongly enough that it makes sense to just filter some jobs by whether or not someone has a PhD.
I think this is largely the reason, that a PhD is seen as a semi-reliable guide to general research ability, though of course it's neither necessary nor sufficient, but there is a rough correlation.
I feel like teaching research methods would be way more efficient - just without the experience. But we hire BS/MS engineers all the time without industry experience, so why would’nt having a research focus Masters not be sufficient?
That said, our department sends MAs into industry as well. Further our department as well as our University has been promoting undergraduates getting hands-on experience in doing research.
4+ years of PhD (incl. a track record of solid publications) prove that you have the intellect, motivation and discipline to pull off a multi-year research project, similar to the ones employers expect you to work on when they hire you. It seems like an excellent filter for a research job.
b) you could apply to phd programs and get a phd.
But yes, it's impossible to get into R&D labs if you've never done research. You can self-teach and publish in top conferences on your own (this is probably much harder than you think it is but is not impossible!), or you can defer income to get an education from one of the many structured educational programs designed to teach you how to do research.
I'm not sure why you expect industry R&D labs (as a researcher, that is) to hire people who do not already know how to do the job. They are companies, not guilds or universities. Software Engineering positions certainly require people to already know how to program, after all. How is this any different?
A person with PhD will typically like to invest huge chunk of time to digest much of the prior art. They want to systematically understand what worked and what didn't in the past. They then bring in their unique understanding of small set of techniques/cross-domain expertise to combine with prior art to attack the problem. It is important for them to craft well designed experiments and lean on tools like mathematics to guide their next steps. Their goal is to make sure anonymous reviewers of their work are satisfied with proof they present of their hypothesis.
A person without PhD typically doesn't want to take a lot of time going through years worth of prior art. Their approach usually boils down to developing intuition via initial random search and then iterative experiments to strengthen intuition. If this doesn't work out over a period of time, they will probably want to move on to something else instead of keep creating next little insignificant bump of progress. The frame of mind is get to near-instant gratification as opposed to possibly spending all of your life in to something that wouldn't make any impact in real world but might build useful steps for future generations.
It is hard to say one approach is better than other for all classes of problem. However using the first approach requires certain training, rigor, discipline and, most importantly, frame of mind - we call PhD. It is only recently and in few fields like AI that research careers have become desirable from financial perspective. However in most of the fields, things are very different and you would rarely see anyone demanding to be theoretical mathematician or quantum physicist, for example, without a relevant PhD while also receiving modest income with no promotions or stock options.
However, it has become clear that for many advanced problems the random search approach typically maxes out quickly because search space becomes prohibitively large and developing correct intuitions requires climbing knowledge pyramids of epic proportions. For example, invention of transistors, GPS or techniques like initialization or dropout in deep learning wouldn't have been possible without PhD style multi-generation approach and concrete mathematical understanding.
Having said that, I'm against hard liners who create rules that being researcher requires PhD and one without it cannot innovate or do creative work. Many complex and most valuable innovations have been done by non-PhDs such as Faraday, Edison and Wright Brothers - interestingly in all of these cases people with academic degrees gloriously failed working on same turf, for longer time and better funding (Davy, Langley etc).
I.e., they are actually doing the exact job that they are now being hired to do.
> Is it the ability to conduct research - methods, process, analysis, discipline? Or is it the fact that they have knowledge in that particular field?
When you apply to R&D labs, you are competing against people who spent at least five years:
* building research infrastructure (which includes, but is not limited to, knowledge about "methods, process, analysis, discipline"),
* a concrete track record of producing publishable research,
* a professional network and some amount of respect for you previous research output, and
* experience designing a multi-year research project (from writing/helping write a convincing proposal all the way through publishing, evangelizing, and managing relationships with people who want to build on your work).
Do you have 5+ first author publications in good conferences? Have you contributed to R&D software? Do you have multiple influential collaborators who have a high opinion of you and are likely to help popularize/contribute to/build upon your research goals? Have you written and followed through on grant proposals?
If "yes" to all those things, you should apply for these research positions! Even without a phd, you are a good candidate.
If all you have is a six month MOOC, or some R&D software development but no experience with the full research process, then sorry, but there are people with who have already demonstrated they can successfully design and execute on research agendas. You might still be a good candidate, but preferring strictly more experienced and better qualified candidates who have demonstrated, empirically, that they can perform the full job, is not an "arbitrary blockade".
> Every time I speak to someone with a PhD at work (I work in top 10 tech companies in US), in 100% of the cases in my experience do not engage in anything related to their thesis.
"people I have worked with" is a huge selection bias.
IME, in CS this is almost always either a) not true, or b) a conscious choice on the part of the phd holder (and is more of a pivot than a "totally unrelated thing"; you just might not see that there's a deep connection between the thing that the person was doing before and what they're doing now).
Maybe Intel, but then there are arguments there as well.
The kinds of 'R' that PhD's are trained to do is fairly academic and pure. It takes so long for that research to meet applied reality in the competitive sense. I know that Google has made some improvements with voice recognition etc. but it's not hugely material, it hasn't changed their business one bit.
I can't even think of a single important startup these days that was founded on key research.
Of course these people are important, and fairly pure 'R' is important, but the world is far, far more applied than most people like to think.
The kinds of 'professional' aspects you describe simply aren't necessary in most scenarios.
Also - remember that a lot of what researchers churn out isn't necessarily valuable, a lot of the results are not reproducible, and that 'publishing, giving talks, having a network' are not in and of themselves hyper relevant to making progress.
In many ways I feel that PhD's are to 'applied R&D' what 'MBA's' are to business - it's all very academic :)
Major R&D research labs exist to do the "R" in R&D. Many of them are explicitly not doing research that is intended to become a new business/product.
There are many models here, but the important point is that if you want to start a new business (unit), an industrial research lab is probably not a good fit. They mostly exist for other reasons.
If parent wants to start a new company or business unit, he should do that. But in that case, why is he applying to industrial R&D labs? He should be applying to y combinator instead...
Your post is a bit like saying that it's reasonable for a personal trainer to get a job as a doctor at a hospital because exercise is more important than surgery to most people's health. I.e., you're saying true things but kind of completely misses the point of the sorts of organizations we are talking about (research labs in large companies).
(I'll leave aside the ridiculous irony that you included Google in that list... in any case, each of those companies has benefited significantly from their internal R&D orgs.)
We're talking about the value of Phd's to high tech companies, so it's relevant.
Tell me how Facebook, AirBnB, Uber, Microsoft, Salesforce have materially gained from their R&D labs? They would be essentially the same companies without 'research style' R&D. Windows and MS Office do not require PhD's to design, though surely there are material contributions made by those who hold a PhD, but the more classical R&D aspects have not been hugely relevant.
For some silicon companies it's probably true, and possibly in the medical field, wherein clinical research etc. is essential part of the product approach ... but for most of Silicon Valley style companies - it's not.
Companies tend to hire lots of PhDs after they are rich and flush with cash - not the other way around.
"it's reasonable for a personal trainer to get a job as a doctor at a hospital"
No - you need to be a doctor to do 'doctoring'; training to be a doctor is 100% relevant to the practice of actually being a doctor. But you definitely do not need to be a doctor, or even have PhDs on staff to make companies or products that are material relevant to people's wellbeing or fitness.
PhD level, near pure R&D is not essential to the vast majority of even tech startups.
We're on HN, i.e. a Y Combinator site - an entity that is really at the nexus of early stage investment. Care to run down the list of YC investments and see which ones are based on some kind of materially relevant PhD level research - and that are also successful? Because unfortunately there are very few.
I know of one, off hand, Lyrebird - one of the more popularly significant investments that YC has made in AI, they make a really cool product that can take maybe a minute or so of your speech, and then re-create a text-to-voice simulator voice that sounds similar to the pre-recorded device. It's pretty cool, but not that great. It's been a while now, they have no real product that anyone cares about aside from it's novelty, they don't have any real revenue, and they probably won't. Sadly, they will be acquired by some BigCo R&D shop and hopefully make some money for themselves. They are making great contributions to science, but they might as well be doing it out of U. Montreal from whence they came.
Most R&D done by BigCos is just a little more applied than such research done at Universities, but the results of such work benefit the commons as much as they do the companies anyhow. In a way, it's almost benevolent spending on the part of BigCo's, somewhere to park their cash, maintain prestige. It's important in the 'general' context, but often not very directly related to the bottom line of said companies.
Again, research labs are not hiring people to build products. They are not even hiring people to do advanced development in most cases (and when they do, those supporting engineer roles typically don't require phds). They are hiring people to do heavy-R research.
> We're talking about the value of Phd's to high tech companies, so it's relevant.
No, we are talking about whether these companies should hire phds into their already existing research labs. Not even generally, but specifically (e.g., Intel Labs and Amazon).
The decision that these labs should do heavy-R research was already made for us by VPs or C-level folks. These labs already exist, their mandate is already spelled out, and now the question is "why won't they hire me to execute on that mandate?"
If parent disagrees with that mandate, why would he be interested in getting a job in one of these labs?
The question of whether these places should have heavy-R research labs in the first place is entirely orthogonal to this thread. Why? Because parent already stated he wants to work within these existing research organizations.
It sounds like you think typical industrial research labs are bad investments. That's fine. I disagree. More importantly, presumably, the parent commenter disagrees. After all, if he did agree with you, why the hell would he want to work in an R&D lab?
If parent agreed with you, why the hell would he be pining for a job in one of these labs? He wouldn't. He would just apply to YC.
So, again, litigating whether or not these heavy-R research labs should exist in the first place is an important topic but is not relevant to this thread, which is about the question: "why don't research orgs that have a corporate mandate to do heavy-R research hire non-phds?".
Extremely off-topic, as I've stated multiple times now, but maybe it will help: YC has HARC and (indirectly) OpenAI. Those are much more analogous to corporate research labs than YC investments. Are they wastes of money? Good question; but one thing is certain: if you think so, then you probably don't want a job at one :-)