Biomedical superstars are signing on with Google
nature.com
nature.com
My hunch is that Google has a oncology/immunology platform which they're not talking about but trying to actively develop in order to help fuel Calico's pipeline and maybe sell off some other generated IP. There's almost certainly a "big data" angle as well, potentially describing the polymorphisms in majorhistocompatability (MHC) molecules between people. Having a large dataset of this kind of information would provide a lot of predictive power for infectious disease resistance and also disease progression.
Google is new to this space and enjoys young talent, so I can tell that their approach will be to hire the people graduating from the top biomedical PhD programs. This is a hiring market that they can easily dominate by offering salaries of 50k-90k, though they may bump this range up to ensure loyalty. Nobody else will offer a better game in town to fresh PhDs in the current (extremely hostile benefits-wise) science employment environment. Google gets in on the ground level, and the fresh PhDs avoid wasting 5 years on their postdoc-ing. Once the platform is established using the young talent, Google will spend a lot of money bringing in older mid-level people from prestigious organizations to mainstream-ize development and provide more credibility.
There is too much talent, too much willingness to self-sacrifice, too much competition, and far too much enthusiasm. Many scientists (myself included) wouldn't stop if they were limitlessly wealthy... and because of this fact, we are not wealthy, and many have severe doubts about continuing onward because of the poor quality of life.
I love programming in my day job but I can't figure out if you're being sarcastic.
It's like saying, who doesn't want to work in hard math problems while extremely time constrained all day? There are people who would love it, but I don't understand how can there be an overabundance of them.
You could easily pick up web dev stuff or something similar for a few years to save up and then go back to your passion.
Or even do it on the side
I got really bored working on e-commerce checkout funnels and A/B testing and constantly learning about new Javascript frameworks that churn out every year that does the same things over and over. With Coding Bootcamp churning out more CRUD people year by year, and JS frameworks and Agile automating web dev work to be like assembly-line; I found it to be both increasingly less financially secure and spiritually filling.
Genomics (for me personally) is more interesting; you get to learn a lot of statistics, biology and backend pipeline code. Also work environment in a lab is different, you have a lot more autonomy and you get to present your work and learn more about things in an academic/journal club/talks setting vs. the typical IT/Software Agile morning standup's. Not to mention the field is constantly changing, new sequencing technologies and new search algorithms are published constantly.
The salary for post-doc's is at that range. A research scientist or a software developer at least if you land at a well-funded place or BigPharma is about the same as a software developer (100-130K). I got out of the web-dev game a year ago; and I think while I am no longer on the cutting edge of the latest React.js/Node technology, I picked up new skills in concurrency, messaging system and machine learning (HMM, SVM, clustering etc) building whole genome annotation/analysis pipelines.
It has worked out for my personality but I have plenty of friends who get excited about doing new iOS and JS languages/frameworks so I respect that too (but not for me).
It basically depicts in stark contrasts what our true priorities are. Not what we pretend we value, but what we do value in reality.
Sorry if it sounds cynical, but I see no other conclusion.
You can have relatively unskilled labor paid a lot if there aren't many people and very skilled labor paid little if there are a lot of them. It shouldn't be surprising.
As a society, we sure have interesting priorities ...
It seems to be a little random if GLS wants you or not, but if they want you they really want you. From my own experience and that of friends working in science-based startups, Google salaries are a major impediment right now for hiring. We're still able to get great people, but it certainly slows things down.
I'm guessing that the higher salaries are for people who are experts in (did their dissertation on) extremely narrow subfields of subfields which Google has an intense (but probably only capricious) interest in-- they want THAT person because they're one of a dozen on earth who specialized on that particular thing. This would drive the salaries up quite a bit, but only as blips. From the outside, this would also explain the "seemingly random" criteria used to select people-- it's not random, just very focused on an otherwise obscure/esoteric item.
Edit: Worth clarifying is that the cases I know of first-hand for this got their PhDs in "bioengineering" or something similar, not a traditional biology or chemistry.
The researcher I knew was definitely not an engineer, so I assume he was on a lower payscale. Biomedical engineers typically get paid a bit better than the researchers everywhere.
This is an interesting observation, particularly when considering the engineering vs. science distinction that you mentioned. The value traditionally produced by life scientists is less predictable than it is for engineers, due to the more unpredictable nature of the business. To some degree, Google has probably overshot in terms of estimating the likelihood of success (the 'Andy Grove fallacy'). They've hired a lot of ex-biotech people though, so that's surprising. Perhaps they just want to ensure they attract the best life scientists despite the lack of a track record in the industry.
Yes. Most of academia pays as per NIH guidelines -- http://www.niaid.nih.gov/researchfunding/paybud/pages/salary...
Even 60K will get them a PhD with 5 years of experience anyday
For reference, PhD plus 7 years experience is a total of 12-14 years experience, depending on how long the PhD took.
As an MD, soon to have a PhD in oncology immunology, I always wonder what project Google could be working on in this area. After all they are a company and most probably try to develop products that will yield a return in the future. So why would someone chose to work for a Google firm that has no real track record in the Life Sciences versus the many life-science companies that already have amazing logistics/experience in place (Novartis, Biogen, Takeda to name just a few in Cambridge, MA). Outside "data-science" projects like genomics, or very technical project like lab-on-a-chip devices, I wouldn't see a big advantage moving to the bay area. However, I guess offering huge salaries always helps convincing people to join your company. And the winters in the Mountain View are probably warmer than the Boston area.
https://cloud.google.com/genomics/gatk?hl=en
They also have a project with Novartis (I think not with NIBR however) to do glucose testing via contact lenses.
http://www.reuters.com/article/2015/09/05/us-novartis-ceo-id...
If I have to guess, I don't think Google plan to build a HTS facility for drugs R&D or a huge lab foot-print to do wet-lab work. They probably want to leverage their existing compute/engineering infrastructure to get involved in the next phase of informatics needs in health care and life science (e.g., cloud storage and compute needs for clinical genome sequencing, analysis workflows like 23andMe for academia/industry/clinical).
Also i wouldn't be surprised they have(or are investing in) specialized search engines for innovations. Something that scans tons of research papers and finds interesting things. Maybe something like this:
http://www.technologyreview.com/news/520461/software-mines-s...
But sure, they would definitely be looking into automated discovery engine that including both intelligence and experimentation.
[0] http://techcrunch.com/2014/05/07/google-ventures-leads-130m-...
Perhaps this is the evolution of that effort...
Novartis pays their fresh PhDs 70-90k DOE, as does my current startup; formerly at my lab in academia postdocs started at 35-50k.
Where's the big data angle on MHC polymorphisms? Aren't they mostly succinctly summarized by HLA type (which is an awfully small piece of data, even if catalogued for every human alive)?
I can't wait for the personalized ads...