4 ms·

Some tasks aren't fit for a single person: why can't one post-doc do the prep shift and a second post-doc do the enzyme work? The way we structure our research

by zimzam 10y ago

Some tasks aren't fit for a single person: why can't one post-doc do the prep shift and a second post-doc do the enzyme work? The way we structure our research institutions is arbitrary: we can and should restructure them if they aren't working.

cshimmin 10y ago
Often times at the bleeding edge of research, that one postdoc is literally the only person in the world who can do both tasks. Also, most research projects are short enough on funding as it is. So what if you declare that this lab either has to 1) hire two people do to this job in shifts or 2) simply not do the research at all? You get back to the same situation dnautics mentioned where the truly passionate/competitive researchers are going to be doing whatever it takes to get it done (or, with strict enforcement, the science just doesn't get done).
- projektir 10y ago
  > Often times at the bleeding edge of research, that one postdoc is literally the only person in the world who can do both tasks. I thought we just said earlier how easily replaceable this post-doc is. Not buying it. Bleeding edge of research doesn't really exist, it just doesn't move fast enough to have any sort of "bleeding edge". It's slowed down by lack of money and poor management and too much bureaucracy far more than it is by someone not working long hours. As has always been true with these things. This is why startups will, sadly, end up beating academic science over time. Because startups are bleeding edge. "It has to be this way!" is a very difficult claim to verify, you can't expect others merely to accept it, you must prove it, and I have seen very little evidence so far, including from my own experience with people who did research at university.
  - johncolanduoni 10y ago
    > Not buying it. Bleeding edge of research doesn't really exist, it just doesn't move fast enough to have any sort of "bleeding edge". It's slowed down by lack of money and poor management and too much bureaucracy far more than it is by someone not working long hours. As has always been true with these things. You're thinking of bleeding edge as "new drug that at least shows up in some pop-sci stuff". People working in labs come up with new methods of doing X in situation Y all the time because X and Y can both be crazy specific to a certain line of inquiry. A thousand of those lines of inquiry will likely be explored before anyone outside of their extremely specific area of study notices. Your sampling bias is pretty irrelevant to the process. As a concrete example, maybe you need to apply a novel algorithm to a high frequency data source (e.g. a single photon counting module). So you need to program an FPGA with a deserializer to do the processing (in lieu of wasting money on a DAQ that can pump data into your computer at a few GHz sampling rate), and only one postdoc understands the algorithm and FPGAs well enough to do it. Does that sound like a crazy, unusual, made-up scenario? > This is why startups will, sadly, end up beating academic science over time. Because startups are bleeding edge. Have you seen how hard it is for startups that actually work on bleeding-edge scientific work to take off? Is that not something that Y-Combinator (for example) has specifically been looking for a more hybridized model for? Most research done at university is a very risky bet even for startups, especially if you want not just a result but a marketable result. Want some concrete examples of the system working? Take a look at the envelope that quantum information research has pushed in the last 5 years. On the theoretical computer science side, you've got people like Scott Aronson answering significant open questions at a dizzying rate (read his blog for some basic, well-explained evidence). Meanwhile you've got groups like Martinis'[1] making the first quantum computer that can accurately simulate a different quantum system. All with a huge amount of collaboration in a social network of scientists that spans the globe. Where's your evidence that startups are the hammer-screwdriver-impact-driver combo that solves all of humanity's intellectual problems with but one institution? Because that's a much stronger claim than "academia does moonshot research that wouldn't get done otherwise and its not the scientific equivalent of another day another CRUD app". [1]: http://web.physics.ucsb.edu/~martinisgroup/publications.shtml http://web.physics.ucsb.edu/~martinisgroup/publications.shtm...
    - projektir 10y ago
      Bleeding edge means time is important. Because time being important is the only thing that would make the argument. Since time is not important, it's not bleeding edge. So there's no actual rush, and any claimed one is artificial. There's no justification for rushing in science in general, in fact, and all the rushing for publications and other rubbish is going to make all the research worse, not better. It should be a careful, deliberate process. If you are working 16 hours and are constantly worried about what your professor thinks of you, I am forced to be wary of your science. > only one postdoc understands the algorithm and FPGAs well enough to do it. I'm not going to go into problems of poor knowledge transfer obviously present here (bus factor 1?), but if this was the case, the post-doc would have negotiation power and this entire situation wouldn't be an issue. Clearly the post-doc is extremely replaceable, as the letter in the article implies, so you should have like 10 of those. If not, why are you threatening the post-doc? This sounds like a situation of not enough people, not too much people. This asymmetry concerns me, and I am rather confused by it. > Have you seen how hard it is for startups that actually work on bleeding-edge scientific work to take off? It's hard, and overall, I would say it's worse (hence the sadly). But it's a lot better than the nonsense that academia is engaging in right now. It at least provides some competition and puts pressure on academia. If academia doesn't fix its act, eventually, private will have to take over. It's the same situation as it'd be nice if all the big, well-equipped companies would create and promote the electric car, but if they won't, someone else will have to do it, even if it's less preferable. Something tells me that the big name post-docs can actually dictate their own terms and are not the same post-docs we're talking about. I'm having a hard time imaging that post-doc getting emails like this. There's lots of ML research on the startup side right now, I wouldn't be surprised if the demand for quantum research will rise with time. The main advantage academia has isn't the system, but the government money... which is not at all indicative of the system working well. ahem government contractor companies ahem And seems like private can also grab government money. We got a lot of good results from the "guy just goes on his own and is left alone by everyone and just sits there and studies alchemy for a bit" system, too. Consider how much was accomplished before with very little effort and how much people are working now, and how many people. I understand the problems are harder now, you need better equipment, etc., but that doesn't mean I'm not going to call a spade a spade. I've seen the time of so many post-docs wasted that I'm not going to just ignore that. You can't expect everyone to just accept that, it needs to be justified. That's what I mean by "not buying it". It may be true, but the evidence is not there, not there at all.
dnautics 10y ago
well, when you do that, the second post-doc does the enzyme work, and doesn't notice one little thing that the first post-doc does that messes up the experiment, 30% of the time. It's like why do hospitals make doctors and nurses pull long shifts? One of the major sources of errors is handoff error, where passing a patient from continuous care by one person to another results in loss of experiential knowledge accumulated over that time, which is why medical staff tend to pull 16 hour shifts instead of 8 hour shifts (which would double the handoff error).
- Tannic 10y ago
  Interesting...seems short-sighted though. Presumably handoff errors could be reduced by staggering shifts so that important information has the proper time to be relayed.
- projektir 10y ago
  Yet we have a movement toward shorter hours for hospital staff right now due to all the errors committed by overworked people and burnout issues. Expecting mere humans to keep track of logistical things is already a mistake - use computers, use checklists, etc., medical issues due to expecting a human to remember things is already a problem. It's not like these policies are chosen by nurses themselves, they're chosen by those whom it does not affect. I very much doubt that this reason you claim has been properly looked at. Every single time I look at a situation like this it never happens for a good reason, but because someone was greedy and was trying to cut costs somewhere. The main reason this gets written off as OK is because nobody cares about nurses, or post-docs, or whatever other group of exploited people. They're replaceable and interchangeable and are just thrown through the grinder because it's cheaper than figuring things out properly. The cost of burnout is never considered because the implementers can get away with not bearing it.
  - dnautics 10y ago
    16 hours is shorter than the past. I mean your exploitation rhetoric is very facile. For what it's worth, I think there are more postdocs exploiting the system than get exploited by the system. My personal feeling is that the median postdoc is worth negative science.

by zimzam 10y ago

cshimmin 10y ago

Often times at the bleeding edge of research, that one postdoc is literally the only person in the world who can do both tasks. Also, most research projects are short enough on funding as it is. So what if you declare that this lab either has to 1) hire two people do to this job in shifts or 2) simply not do the research at all? You get back to the same situation dnautics mentioned where the truly passionate/competitive researchers are going to be doing whatever it takes to get it done (or, with strict enforcement, the science just doesn't get done).

projektir 10y ago
> Often times at the bleeding edge of research, that one postdoc is literally the only person in the world who can do both tasks. I thought we just said earlier how easily replaceable this post-doc is. Not buying it. Bleeding edge of research doesn't really exist, it just doesn't move fast enough to have any sort of "bleeding edge". It's slowed down by lack of money and poor management and too much bureaucracy far more than it is by someone not working long hours. As has always been true with these things. This is why startups will, sadly, end up beating academic science over time. Because startups are bleeding edge. "It has to be this way!" is a very difficult claim to verify, you can't expect others merely to accept it, you must prove it, and I have seen very little evidence so far, including from my own experience with people who did research at university.
- johncolanduoni 10y ago
  > Not buying it. Bleeding edge of research doesn't really exist, it just doesn't move fast enough to have any sort of "bleeding edge". It's slowed down by lack of money and poor management and too much bureaucracy far more than it is by someone not working long hours. As has always been true with these things. You're thinking of bleeding edge as "new drug that at least shows up in some pop-sci stuff". People working in labs come up with new methods of doing X in situation Y all the time because X and Y can both be crazy specific to a certain line of inquiry. A thousand of those lines of inquiry will likely be explored before anyone outside of their extremely specific area of study notices. Your sampling bias is pretty irrelevant to the process. As a concrete example, maybe you need to apply a novel algorithm to a high frequency data source (e.g. a single photon counting module). So you need to program an FPGA with a deserializer to do the processing (in lieu of wasting money on a DAQ that can pump data into your computer at a few GHz sampling rate), and only one postdoc understands the algorithm and FPGAs well enough to do it. Does that sound like a crazy, unusual, made-up scenario? > This is why startups will, sadly, end up beating academic science over time. Because startups are bleeding edge. Have you seen how hard it is for startups that actually work on bleeding-edge scientific work to take off? Is that not something that Y-Combinator (for example) has specifically been looking for a more hybridized model for? Most research done at university is a very risky bet even for startups, especially if you want not just a result but a marketable result. Want some concrete examples of the system working? Take a look at the envelope that quantum information research has pushed in the last 5 years. On the theoretical computer science side, you've got people like Scott Aronson answering significant open questions at a dizzying rate (read his blog for some basic, well-explained evidence). Meanwhile you've got groups like Martinis'[1] making the first quantum computer that can accurately simulate a different quantum system. All with a huge amount of collaboration in a social network of scientists that spans the globe. Where's your evidence that startups are the hammer-screwdriver-impact-driver combo that solves all of humanity's intellectual problems with but one institution? Because that's a much stronger claim than "academia does moonshot research that wouldn't get done otherwise and its not the scientific equivalent of another day another CRUD app". [1]: http://web.physics.ucsb.edu/~martinisgroup/publications.shtml http://web.physics.ucsb.edu/~martinisgroup/publications.shtm...
  - projektir 10y ago
    Bleeding edge means time is important. Because time being important is the only thing that would make the argument. Since time is not important, it's not bleeding edge. So there's no actual rush, and any claimed one is artificial. There's no justification for rushing in science in general, in fact, and all the rushing for publications and other rubbish is going to make all the research worse, not better. It should be a careful, deliberate process. If you are working 16 hours and are constantly worried about what your professor thinks of you, I am forced to be wary of your science. > only one postdoc understands the algorithm and FPGAs well enough to do it. I'm not going to go into problems of poor knowledge transfer obviously present here (bus factor 1?), but if this was the case, the post-doc would have negotiation power and this entire situation wouldn't be an issue. Clearly the post-doc is extremely replaceable, as the letter in the article implies, so you should have like 10 of those. If not, why are you threatening the post-doc? This sounds like a situation of not enough people, not too much people. This asymmetry concerns me, and I am rather confused by it. > Have you seen how hard it is for startups that actually work on bleeding-edge scientific work to take off? It's hard, and overall, I would say it's worse (hence the sadly). But it's a lot better than the nonsense that academia is engaging in right now. It at least provides some competition and puts pressure on academia. If academia doesn't fix its act, eventually, private will have to take over. It's the same situation as it'd be nice if all the big, well-equipped companies would create and promote the electric car, but if they won't, someone else will have to do it, even if it's less preferable. Something tells me that the big name post-docs can actually dictate their own terms and are not the same post-docs we're talking about. I'm having a hard time imaging that post-doc getting emails like this. There's lots of ML research on the startup side right now, I wouldn't be surprised if the demand for quantum research will rise with time. The main advantage academia has isn't the system, but the government money... which is not at all indicative of the system working well. ahem government contractor companies ahem And seems like private can also grab government money. We got a lot of good results from the "guy just goes on his own and is left alone by everyone and just sits there and studies alchemy for a bit" system, too. Consider how much was accomplished before with very little effort and how much people are working now, and how many people. I understand the problems are harder now, you need better equipment, etc., but that doesn't mean I'm not going to call a spade a spade. I've seen the time of so many post-docs wasted that I'm not going to just ignore that. You can't expect everyone to just accept that, it needs to be justified. That's what I mean by "not buying it". It may be true, but the evidence is not there, not there at all.

dnautics 10y ago

well, when you do that, the second post-doc does the enzyme work, and doesn't notice one little thing that the first post-doc does that messes up the experiment, 30% of the time. It's like why do hospitals make doctors and nurses pull long shifts? One of the major sources of errors is handoff error, where passing a patient from continuous care by one person to another results in loss of experiential knowledge accumulated over that time, which is why medical staff tend to pull 16 hour shifts instead of 8 hour shifts (which would double the handoff error).

Tannic 10y ago
Interesting...seems short-sighted though. Presumably handoff errors could be reduced by staggering shifts so that important information has the proper time to be relayed.
projektir 10y ago
Yet we have a movement toward shorter hours for hospital staff right now due to all the errors committed by overworked people and burnout issues. Expecting mere humans to keep track of logistical things is already a mistake - use computers, use checklists, etc., medical issues due to expecting a human to remember things is already a problem. It's not like these policies are chosen by nurses themselves, they're chosen by those whom it does not affect. I very much doubt that this reason you claim has been properly looked at. Every single time I look at a situation like this it never happens for a good reason, but because someone was greedy and was trying to cut costs somewhere. The main reason this gets written off as OK is because nobody cares about nurses, or post-docs, or whatever other group of exploited people. They're replaceable and interchangeable and are just thrown through the grinder because it's cheaper than figuring things out properly. The cost of burnout is never considered because the implementers can get away with not bearing it.
- dnautics 10y ago
  16 hours is shorter than the past. I mean your exploitation rhetoric is very facile. For what it's worth, I think there are more postdocs exploiting the system than get exploited by the system. My personal feeling is that the median postdoc is worth negative science.