I think I am your target audience in disposition (you are the first fellow slatestarcodex-reading bio person I've encountered, hello), though probably not aptitude. I was driven to go into experimental biology because I thought my enjoyment of math/cs problem-solving would translate to experimental methods development. The NGS, optogenetics, and cas9 waves were all huge when I was in college, and it seemed like that momentum would continue.
I worked at a metabolic engineering company for 3 years after college to get broader exposure, which was super eye-opening. There were ~50 PhDs there from all kinds of different areas, which was a huge contrast from the more focused nature of many academic labs.
While I enjoyed talking to the people in experimental biology, I didn't enjoy the experimental work itself. I found it pretty stressful and repetitive -- long hours, a single moment of inattention crushing a week of work, hard to translate one's skills to different roles... I wasn't super money-driven, but seeing random FAANG friends working flexibly and making 250k, conspired to get me out of experimental work. I didn't want to be 30 and not have employable computational skills.
I think the repetition of the work deters a lot of people. My swe friends would say that their work too, was repetitive, and complain about "protobuf plumbing." I felt they _fundamentally didn't understand_ how repetitive and time-consuming (and delicate!) doing westerns was just to collect a little bit of information.
I was further convinced not to pursue methods development when I saw a PhD-level job talk from a guy at Big Name Lab at our company whose PhD research had like... not fully worked out. Methods is high-risk high-reward. Interviewers had a positive impression of him and gave him an offer, but were skeptical of how his skills would translate to the company/role, and he also didn't have computational skills.
As you said, I think the lack of agency is another hard part. Since experiments are expensive, it's hard to work on your own ideas. I know lots of experimental grad students and post-docs who have only ever worked on PI's projects... another aspect of this is that since people are spending like ~50-60 hours a week *just doing the same lab protocols*, this leaves a lot less time for actually thinking. I think this probably colors the incentive structure of experimental vs computational fields.
Many people are repeating maybe a dozen protocols hundreds of times, not interacting a lot with people from people from other environments. I remember asking a protein engineering PhD how she thought some reaction worked, and she asked "well what does the active site look like?" It felt like a question out of left-field for me, because Actually Thinking About Structure Details felt like a totally different level of abstraction compared to what I was used to.
Tying into this is that many academic labs are pretty siloed. (I think the biology groups I've worked in have been some of the most intellectually vibrant / fun environments ever though, so not trying to knock everything.) But many people are spending 5-7+ years in a single lab with like <8 people, and conflate that with some kind of Broad View of Science and Society (not claiming to have this, lol). This also means that labs turnover more slowly than companies do, since people might churn in <2-3 years. So I think a company might give one more exposure to ideas, but the constraint of "this has to literally-actually make money in the immediate future" is quite different.
In industry there's a lot of people at the bench who have 20+ yoe. In academia... your PI doesn't pipette, and the most senior person in the lab might be like ~3rd year post-doc. I think this means there's like an entire arc of IC skill development that young academic scientists don't see.
At my old job, I would talk to people with ~20 yoe... every 10-15 minutes throughout the day, and we have a shared context and mission of what's going on. In an academic lab, you talk to your PI once a week-ish, and your labmates sort of know what you're doing, but not really. I felt like I learned _a ton_ from just off-hand technical convos throughout the day with people at the company, and found the academic model sort of isolating.
Another thing from working at a company you pick up is learning to sniff out when somebody with 20+ more years of experience than you... can still be wrong. If there's 50+ people with PhDs, you're going to have a lot of contrasting views, and you have a lot of experiences where Bob, who has a Genetics PhD and 20 years more experience than you, is trying to lecture you about something, but it turns out the other senior people disagree and your hunch of calling bs was right. I think this is relevant in grad school, because your PI is the only senior person you interact with, and while they know more than you, they're also a person with their own idiosyncrasies.
Hey, man. Really liked your post and thought I'd reach out. I found especially interesting that you make the point that 10x engineers are born out of freely tinkering their own ideas around, learning what works n all until they have enough of a system understanding that they become cracked at it. And how you then mention that this 'attempt-result Cycle' doesn't really work for bio stuff, but you're anyway at the "top 1% in 'amount of fucking around and trying stuff'". I myself will be starting university for a major in physics later this year, and hopefully eventually work with some biophysics stuff or neuroscience. In any case, I wanted to ask you if you had any tips, or some important things you learned along the way (and the challenges involved in them!) when it comes to just experimenting with stuff and ideas that you'd want to share for someone that'll be just starting this path to excelence in the field. Would be very much appreciated!
I think I am your target audience in disposition (you are the first fellow slatestarcodex-reading bio person I've encountered, hello), though probably not aptitude. I was driven to go into experimental biology because I thought my enjoyment of math/cs problem-solving would translate to experimental methods development. The NGS, optogenetics, and cas9 waves were all huge when I was in college, and it seemed like that momentum would continue.
I worked at a metabolic engineering company for 3 years after college to get broader exposure, which was super eye-opening. There were ~50 PhDs there from all kinds of different areas, which was a huge contrast from the more focused nature of many academic labs.
While I enjoyed talking to the people in experimental biology, I didn't enjoy the experimental work itself. I found it pretty stressful and repetitive -- long hours, a single moment of inattention crushing a week of work, hard to translate one's skills to different roles... I wasn't super money-driven, but seeing random FAANG friends working flexibly and making 250k, conspired to get me out of experimental work. I didn't want to be 30 and not have employable computational skills.
I think the repetition of the work deters a lot of people. My swe friends would say that their work too, was repetitive, and complain about "protobuf plumbing." I felt they _fundamentally didn't understand_ how repetitive and time-consuming (and delicate!) doing westerns was just to collect a little bit of information.
I was further convinced not to pursue methods development when I saw a PhD-level job talk from a guy at Big Name Lab at our company whose PhD research had like... not fully worked out. Methods is high-risk high-reward. Interviewers had a positive impression of him and gave him an offer, but were skeptical of how his skills would translate to the company/role, and he also didn't have computational skills.
As you said, I think the lack of agency is another hard part. Since experiments are expensive, it's hard to work on your own ideas. I know lots of experimental grad students and post-docs who have only ever worked on PI's projects... another aspect of this is that since people are spending like ~50-60 hours a week *just doing the same lab protocols*, this leaves a lot less time for actually thinking. I think this probably colors the incentive structure of experimental vs computational fields.
Many people are repeating maybe a dozen protocols hundreds of times, not interacting a lot with people from people from other environments. I remember asking a protein engineering PhD how she thought some reaction worked, and she asked "well what does the active site look like?" It felt like a question out of left-field for me, because Actually Thinking About Structure Details felt like a totally different level of abstraction compared to what I was used to.
Tying into this is that many academic labs are pretty siloed. (I think the biology groups I've worked in have been some of the most intellectually vibrant / fun environments ever though, so not trying to knock everything.) But many people are spending 5-7+ years in a single lab with like <8 people, and conflate that with some kind of Broad View of Science and Society (not claiming to have this, lol). This also means that labs turnover more slowly than companies do, since people might churn in <2-3 years. So I think a company might give one more exposure to ideas, but the constraint of "this has to literally-actually make money in the immediate future" is quite different.
In industry there's a lot of people at the bench who have 20+ yoe. In academia... your PI doesn't pipette, and the most senior person in the lab might be like ~3rd year post-doc. I think this means there's like an entire arc of IC skill development that young academic scientists don't see.
At my old job, I would talk to people with ~20 yoe... every 10-15 minutes throughout the day, and we have a shared context and mission of what's going on. In an academic lab, you talk to your PI once a week-ish, and your labmates sort of know what you're doing, but not really. I felt like I learned _a ton_ from just off-hand technical convos throughout the day with people at the company, and found the academic model sort of isolating.
Another thing from working at a company you pick up is learning to sniff out when somebody with 20+ more years of experience than you... can still be wrong. If there's 50+ people with PhDs, you're going to have a lot of contrasting views, and you have a lot of experiences where Bob, who has a Genetics PhD and 20 years more experience than you, is trying to lecture you about something, but it turns out the other senior people disagree and your hunch of calling bs was right. I think this is relevant in grad school, because your PI is the only senior person you interact with, and while they know more than you, they're also a person with their own idiosyncrasies.
Hey, man. Really liked your post and thought I'd reach out. I found especially interesting that you make the point that 10x engineers are born out of freely tinkering their own ideas around, learning what works n all until they have enough of a system understanding that they become cracked at it. And how you then mention that this 'attempt-result Cycle' doesn't really work for bio stuff, but you're anyway at the "top 1% in 'amount of fucking around and trying stuff'". I myself will be starting university for a major in physics later this year, and hopefully eventually work with some biophysics stuff or neuroscience. In any case, I wanted to ask you if you had any tips, or some important things you learned along the way (and the challenges involved in them!) when it comes to just experimenting with stuff and ideas that you'd want to share for someone that'll be just starting this path to excelence in the field. Would be very much appreciated!
Terrific read. Looking forward to your future posts!