There are many biotech startups and private research labs thriving and paying high salaries with excellent benefits for that specialty right now - focused on genetic testing, editing, and longevity. Before moving abroad, widening the search outside of academia and considering moving internally might be worthwhile.
I'm surviving on consulting income for a wide variety of clients right now in this space, and let me tell you it's brutal and extremely difficult to get entry to this space for people that don't have a wide network and lots of industry experience. Academic experience typically doesn't count.
In addition there's a severe "passion tax" for these sorts of jobs, the salary difference for a "Data Scientist, Computational Biology", and "Computational Biologist" is pretty big, and hiring is also brutal.
I know a ton of extremely talented people who have been locked out of employment for a long time now. The high interest environment means that biotech investing has been hit extremely hard, as biotech is even higher risk than most software and AI spending (thanks for the correction, Schlagbohrer). Pharma companiees with big hits, like Lilly with GLP1 agonists, are hiring a bit as they try to move into the modern era of pharma with lots of AI tools, but it's still brutal.
There is some history to why it is as grim as it is right now (sunny skies will return, don't worry!). A lot of funding was around ~2019 from the VC people, and biomed PIs were getting their startups funded and hiring from the recent PhD cohorts. The horrible environment in STEM academic hiring needs no introduction, so the talent pool was rich. Early stage drug development and biotech is horrendously risky, so most don't make it past ~5-7 years. Now there are lots of people looking for a job, and the only surviving companies are the extremely hiring averse ones.
Weird egos. I moved from academia to industry and constantly got told "In industry we just care that 'it works'". I thought that was a weird premise, given... you know... who doesn't? But the more time I spent in industry the more time I found that they in fact do not care if it actually works. What seems to matter more is the politics and about "working"[0] the right way using the right new buzzword[1]
Truth is that the work and complexity is not that divorced. Honestly, the work in academia felt harder, though more fulfilling. Industry work hasn't made me have to really think deeply. If anything, I've heard most of my coworkers (at multiple companies) say something along the lines of "we have to move so fast that there's no time to think." Given that (multiple) managers tell me I'm "too slow" just because I'm not producing tons of lines of code (I'm neck and neck with everyone on milestones), I understand what they're talking about. Industry has a working mode of "do first, think second" while academia often thinks first. The reason is really because it is a lot cheaper to think first.
[0] It works enough for some demo to some person
[1] One example is I beat a company's fancy giant transformer based image detector with a scrappy CNN that took only a few hours to train. They were excited for all of 1 day and then wouldn't let me do the same thing to the transformer model (which would have had a bigger impact). Fun fact, my boss also loved to tell me about how dumb academia is because they never do anything useful and how industry makes all the real advancements.
> Fun fact, my boss also loved to tell me about how dumb academia is because they never do anything useful and how industry makes all the real advancements.
It has always seemed clear to me that the world requires two types of people.
1. "Thinkers", those extraordinarily brilliant people who spend lots of time on a single problem, discovering the optimal and most performance theoretical solution
2. "Hackers", who assemble tools by implementing designs from "Thinkers"
Without Thinkers the Hacker could not possibly solve all required problems well a single tool/product requires
Without Hackers the Thinkers work would languish in the ivory tower it was conceived in
>If anything, I've heard most of my coworkers (at multiple companies) say something along the lines of "we have to move so fast that there's no time to think.
Anecdotally, the tide on this is changing—all the low-hanging fruit has been picked and I see/hear many of my older colleagues regret not having gone the whole way with a PhD. This on top of AI being able to answer many of the engineering questions you might have learned the answers to in a masters/bachelors.
>Fun fact, my boss also loved to tell me about how dumb academia is because they never do anything useful and how industry makes all the real advancements.
He's not entirely wrong though. Industry makes the advancements that actually supposed to sell and be profitable on the free market. Academia is all over the place, as not everything being researched there can be used commercially, often it's just to get grant money, push papers and raise their egos amongst their peers.
That's not the pipeline at all. Academia creates the foundation industry sits on. There's a lot more failure, yes, but hits are way more impactful. Innovations generate entire industries.
So weird argument. Academia isn't meant to be "profitable" because no one is measuring the indirect profits. But when you do it's comically large
>Academia creates the foundation industry sits on.
Depends on the industry. All the researchers I know in academia are just wasting government grant money not delivering anything useful. Their words, not mine.
Why are you conflating and equating "useful" with "sells for profit on the free market"?
There are many areas of research where profit is not a goal, and cannot be one. Understanding how and why climate changes is extremely important and useful, but cannot turn a profit. Researching different education methods, same. Hell, the researchers who won the 2024 Nobel prize in economics, who helped us understand how to build economically successful nations, something incredibly useful, cannot turn a profit with their research.
It's frankly absurd to expect everything useful to be profitable.
I really don't get why it's so commonly stated. It's so obviously dumb once you think about it for more than 5 seconds. It's like people arguing that improving the track or improving the shoes doesn't win races because at the end of the day it's the runner that crosses the finish line. Sure, but to discredit everything but the runner is so myopic. Let them run barefoot and run on glass shards, then watch them lose
> Understanding how and why climate changes is extremely important and useful, but cannot turn a profit.
That definitely is for profit. They aren't researching climate change for the love of the game, but because agriculture, oil futures, real estate development, insurance policies, all depend on predicting climate developments.
I'd phrase it as people are researching these things because they're important. The reasons they're important are pretty diverse but because of how our economy works the research all ends up being related to profits downstream. Problem is we only measure "profit" as one step back.
To make an analogy, let's pretend we're a company selling water. We measure profit by how many bottles of water we sell. But people like the gp are complaining that building aqueducts, water purifiers, weather machines, or even improving the bottling process "isn't profitable". It's a weird claim and I'm not sure why it's so prolific. It's incredibly myopic
Drug development is just a totally different game. The tools are the same but the difference between what the reviewers at your favorite high impact publication want and what the FDA wants are pretty different. People spend their whole careers getting good at the latter in the same way people get good at the former.
I've seen people come from academia and thrive and I've also seen the struggle. Some people also go to school with the goal of doing drug development, which sometimes academic folks don't realize.
- person who was good at microscope and ended up in early stage drug development ~10y
Biotech and academia have very different standards for data quality and reproducibility. Most of the biotech people I know view academic research as an interesting first draft at best.
If it's a constant offset like you say, and given academia publishes and industry often doesn't, that might suggest it's dependent on the rate of advancement in academic research. Not in this field so I may be wildly off.
That may depend on the field. My experience (in bioinformatics method development) is that people in the industry can't afford to work on state-of-the-art problems. But once a problem has become established and it's important enough to be worth their time, they will eventually come up with a better solution due to their superior resources.
Because the results from an acedemic paper are not, ever, going to be injected into a customer's arm. Developing products for sale in the real world is very different than designing lab experiments.
Sure, but it would seem the solution would be to hire the recently minted PhDs and teach them through more senior staff how to operate in the real world, just like in literally any other profession.
Instead you’ll just whine until they let you import a billion more Indians
I don't know if it's so much that talented people are being locked out, as much as it is that communities everywhere, not just industry, are requiring a level of people skills that academic people lack but nonetheless thrive without.
Academics do have a reputation that way, but only the 100% safe, tenured ones. The majority of academics are required to have a strong level of communication just to get their grants accepted. Imagine if, on top of working your normal job at maximum efficiency, you then had to make a presentation to the government every year about why you and everyone that depends upon you deserves to eat, while the government you make the presentation to becomes increasingly antagonistic and detached.
There's quite a lot of people skills involved in surviving as an academic in today's environment. Imagine if you had to teach calculus to 150 random, uninterested teenagers (barely adults) every 12 weeks. There's some serious people skills involved in doing a good job at that (most people do actually try to teach well, I've known multiple people this year refused tenure based on rate-my-teacher ratings).
It's a different set of skills for sure, but being an academic isn't as socially challenged as the zeitgeist appears to believe.
They might co-occur, but they aren't the same thing. It's easy to communicate something in a way that (a) the recipient understands clearly; and (b) the recipient refuses to acknowledge despite understanding it. And in the other direction, you can persuade people to do things without them ever understanding what you want or why the things should be done.
okay... here's another way of thinking about it: claude, gemini and chatgpt are very good at communicating. but, would you marry claude? would you want claude to be your boss? would you want claude to be your coworker? a lot of people are choosing claude to be their intern, which is something.
what i am saying is, having people skills are the answers "yes" to all those questions. you can cynically call getting a job nepotism, or you can call it, well people like to work with their friends at the cost of measures of competency. and maybe, the core competency is being pleasant to work with or work for.
another place people struggle with this is executive compensation. if i told every DoD employee they could get a 10x better boss for only $20/y, every single one would, which is $58m in executive compensation. but the DoD CAN'T do that, and its leadership is TERRIBLE, so... do you see?
Regardless of the implementation, claude causes concepts to enter my brain, so it is at least one-way communication. Human brains have mundane implementations as well: chemical signals firing across neural synapses. No magic special sauce, at least not that we can detect
I would say you communicate to the model and you interpret the model's outputs. I would not say the model communicates back though.
I'm not sure that models are complex enough to have a consistent internal representation of a concept the same way that organic brains can to communicate. I'm not sure of any quantitative science backing this up though. Models don't know anything across iterations yet.
Most models do not have any persistent state or output that is separate from their input. They consume a stream of tokens and then output a probability distribution. The probability distribution will always be the exact same for that particular stream of tokens. There is no internal state, thoughts, mood etc., only prediction based on the input. "Memory" is usually just something injected into context by the harness and updated by usually a tool call from the model.
I'm sure there are research prototypes that work differently from this but I haven't seen any enter the mainstream yet.
Also, diffusion language models have a different evaluation order but I think they also do not really have internal thoughts or feelings because they also do not seem to have any sort of hidden state that encodes anything like that.
Academic's, FTR, have to have a huge amount of people skills. Their job isn't just to discover, it's to share.
You cannot share (effectively) if you cannot communicate in a way that others can understand.
Further the entire ecosystem that academics rely on to get what they need to do for their research (grants, and other funding, resources, and so on) necessitate them to convince people who control those, who do not necessarily understand the purpose of the work
> The high interest environment means that biotech investing has been hit extremely hard
I don't think this reasoning can work. To the extent these things are directly related, the relationship would have to be: returns on investment are at an all-time high --> more investing than usual.
When interest rates are low, capital is willing to go to riskier enterprises like biotech in order to get a larger return compared to the alternatives.
When interest rates are high, capital shifts to yield-generating, interest-bearing investments. They give higher returns with less risk.
So basically the ROI of biotech becomes less competitive compared to alternatives. You have the same number of people/firms chasing a smaller supply of investment dollars.
High interest rate environment usually means the government specifically is paying a better rate on its debt. Then other interest rates are downstream from that. Government interest rates aren't connected to returns on investment (or only very indirectly).
Tech investments don't come with interest payments usually, so if interest rates go up it pulls money into government and corporate bonds which are much lower risk. Why take a gamble on new tech that might lose you everything to get 10% ROI, if you can get 6% "risk free" in bonds?
We are not convinced that we will be happy in the industry and part of it is the visa issues. She currently has a valid visa until 2029 but she just doesn't want it anymore.
how exactly did you jump to the conclusion that American ?citizen? taxpayes are propping these two people up financially? They are presumably both paying income tax in the United States as well, probably a lot of it based on his wife's profession.
I happily had a job in academia in the US. Probably what most would call “successful” after exiting a startup and getting a PhD I was US engineering faculty for 8 years.
We picked up our keys to our new house in another country a few days ago and I start next month with a faculty promotion. Many of my colleagues are or are looking to follow.
You are a fool if you think these companies are hiring enough to meet the labor needs. So many Phds I know are looking for work and yes they’ve applied to probably 500 jobs mostly in industry.
A lot of people in academia are mission driven - they don't care about the money, they care about the application of their work to benefit humanity and don't want to exist as a cog in a private corporation's profits. I think this mentality of "scientists just want to get paid a lot of money" is contributing to the anti-science views that are so pervasive in America these days. Some people are motivated by more than just profit.
