Pathos AI | Software Engineering | Full Time | Hybrid in LA or NYC preferred, Possibility of Remote elsewhere in USA | $(160-190)k
Pathos was founded to revolutionize precision medicine in cancer by harnessing the power of machine learning to transform drug development. Pathos aims to accelerate traditional oncology approaches based upon a comprehensive and integrated data-first strategy to discover and develop drugs for precise biological pathways. Pathos is currently pursuing co-development and in-licensing opportunities to build a portfolio of clinical stage oncology assets, applying its technology to find the right patients and indications, resulting in a highly improved probability of success and faster time to market.
I'm hiring for software engineers, with a focus on cloud infrastructure. We'll be developing infrastructure for data analysis and storage, processing and analysis pipelines, and internal applications. Engineering writes code mostly in Python, while our scientists prefer R. We use Google Cloud Platform for our infrastructure. Currently, the team is just me, but we are looking to hire at least 1 more full time engineer.
An ideal candidate will have at least 2 years of experience developing software in a professional environment, with at least 1 year of that working with Google Cloud Platform.
Nice-to-haves are experience with scientific computing, experience with bioinformatics tools and/or biological and medical data, and experience with Python, R, PostgresSQL, and containers. Experience securing data and applications would also be nice.
I was an experimental physicist, and I'd say that's a reasonable comparison to make.
The time scales are much longer, unfortunately. Instead of taking one or two years to get a company off the ground, it can be more like five for an experiment[1]. I'd attribute this to slower iteration. You end up throwing away or rebuilding a lot of physical things, many of them bespoke, on the way to a working apparatus.
Also, the compensation is much worse for experimental physics. For he first decade of your career, you work as a grad student, then a post-doc, for slightly above poverty wages. This does have the advantage of meaning you work with very motivated people, but you're giving up a lot for that.
[1] The XENON experiments from the article (10, 100, and now 1 Tonne) have been developed over about 15 years, for example
The Screen Actors Guild, and the players unions for most professional sports (NFL, NBA, MLB, etc). They recognize that their members have different levels of talent, and allow the stars to make more, while still ensuring basic rights for every member.
Presumably a maximum pay is set with the intention of allowing that money to go elsewhere in the sport? The NBA knows stars will get paid very well, but they want to ensure not all the money is spent on them so that lesser known players are fairly compensated as well. It seems a smart idea especially because an instituted max is still allowing stars to be paid 8 figures a year.
IMO, the maximum pay/salary caps are set to promote competition across the league. As an entertainment product provided by a monopoly supplier, that's exactly the right thing to do. As a (clearly hypothetical if you'd ever met me) top talented employee under such a scheme, it's terribly counter-productive to my individual situation.
You can't get a job in a SAG affiliated production until enough SAG members are hired, but you can't become a SAG member until you've been in a SAG affiliated production.
I'm not an actor, but on the outside that Catch 22 stinks of Old Boy Network tactics.
And how's that working out for them? The median SAG/AFTRA member makes less than $1,000 per year from acting. And the pro sports players associations are tiny -- they exclude the much larger group of athletes who try to make a living playing sports but don't make the big leagues.
SAG/AFTRA is a large union that represents actors in TV/film, as well as actors in theater, who generally make diddly squat because not many people watch theater performances in the US.
By way of comparison, the rate for a single background-role (i.e., as an extra) in a commercial at SAG rates is more than 3x the non-SAG rate for the same time. ($630 vs $200). If you live in a city like LA or NY, you could make a living wage working (as a background actor) just 45 days a year.
SAG's hourly rates are great on paper - well above market, in fact. The net result of this is that your typical SAG member who doesn't have the power to demand higher rates anyway based on their own reputation ends up with almost no work because so few productions can afford to hire them, which is why their actual income is so low. The way SAG maintains its power despite this is by requiring productions that want to hire more in-demand actors to only employ SAG actors, forcing everyone to sign up to SAG and commit to waiting tables rather than acting most of the time.
If you cast your mind back to the video game voice actor strike a few years ago, for example, you may recall that one of the justifications for that was that they needed more money because many of them were only getting something like one day's work a month on average. Mostly because no-one outside of the big triple-AAA games could afford to hire union voice actors. Back in the day, a lot of video game and anime voice acting was apparently done by union members under pseudonyms so the union didn't find out; that's probably harder to get away with these days.
The net result of this is that your typical SAG member who doesn't have the power to demand higher rates anyway based on their own reputation ends up with almost no work because so few productions can afford to hire them,
This is false. Pretty much every theatrical film, broadcast or cable TV show, and nationally aired commercial in the US is subject to union/guild scales (and even Netflix has begun negotiating with the unions and guilds.)
If you have a "reputation" in Hollywood then you are making above scale because your agent has the leverage to demand above scale. And if you don't, that generally means you are a background player and you're making minimum scale. And at that level, you have trouble finding work because there are hundreds of thousands of other actors competing for the same roles, not because the productions can't afford you.
If you cast your mind back to the video game voice actor strike a few years ago, for example, you may recall that one of the justifications for that was that they needed more money because many of them were only getting something like one day's work a month on average
Yes, because there isn't that much voice over work in video games, and AAA studios were paying minimum scale for games that ultimately grossed hundreds of millions of dollars.
Mostly because no-one outside of the big triple-AAA games could afford to hire union voice actors.
This is false. The union scale for video game voiceover work was $825/session, no residuals no benefits. It usually takes less than 3 sessions to record all of an actor's lines, so you're looking at a total net outlay of less than $2500 for an actor's voiceover work in a video game. If your studio can't afford that for a game in which voiceover work is important enough to justify 3 sessions of recording, then you're not a studio, you're a hobby. (But on that note, a different, lower scale applies to low-budget games, just like it does to low-budget film and TV productions.)
I found this more readable and understandable than the Haskell post, although I can't quite say why. It might simply be the repetition.
I'm really interested in Futhark, though I haven't found a project where it would be make sense to use it. But I feel like it has the same potential to make GPU programming not feel overwhelming the same way Elm did with frontend work for me.
Since Futhark has sum types, I wonder whether we could transpile Elm syntax to Futhark. I'll have to dig into what's possible with Futhark and how well it would map...
The biggest problem would be the absence of recursion, but a recursion-free subset of Elm (with a different standard library) would be straightforward.
There are a few interesting things that we could get from looking at neutrino masses.
The first has to do more with the nature of the mass than the mass itself. In the standard model, electrons, muons, and taus get their mass from the Higgs field. There's a way for neutrinos to get their mass in other ways, but it requires them to be their own antiparticles. And this gives a satisfactory answer as to why their masses are so tiny, and suggests some new particles (although at electroweak unification scale, so not anything we're going to achieve with a collider any time soon). There are a number of double-beta decay experiments trying to measure the Majorana mass of neutrinos.
The other would be if the neutrino hierarchy is "inverted". The tau is heavier than the muon is heavier than the electron. Right now, with neutrinos, we can only measure the difference in masses. And so it's not clear if the neutrino with the most election portion[1] is the lightest or if the neutrino with the most tau portion is. The latter would be "inverted" from what we expect, and trying to figure out why might be interesting, though I don't know that it immediately implies new physics.
There're also other things related to masses that are interesting. Neutrino oscillations are determined by the differences in mass. Looking at these, we might be able to discover more generations of neutrino (beyond electron, mu, and tau), which would be new physics.
[1] the mass eigenstates of the neutrino (that is, the things with well-defined masses) are not weak force eigenstates, so they contain mixtures of the electron, mu, and tau neutrinos
Q. So, an atom decays and gives off some particles including a neutrino. So, we look at the mass-energy arithmetic before and after the decay and see that it all adds up but does need the tiny mass-energy of a neutrino.
That fact, that small difference, seems curious, maybe toward new physics? That is, somehow maybe the mass-energy amounts are, once again in science, whole number multiples of something small. If so, then we can look for how the other particles are whole number multiples??
I have to expect that 99+% of physics students have already thought of this.
Is there anything curious about that tiny bit of mass, e.g., why it has to be there at all?
It's a bit different than that. The decay of a neutron into a proton and an electron conserved charge, mass-energy (to an expected degree), and momentum. However, spin was not conserved. The neutrino was dreamed up as kind of a placeholder for the spin. However, it turned out that it was a real thing!
The mass-energy arithmetic should not be the thing you look at for a couple of reasons. First, it's quite difficult to measure with exactitude. Second, the binding energy for particles and their constituents plays a part that is easily within error bounds.
> First, it's quite difficult to measure with exactitude.
I wondered about something like that -- the mechanism really is exact to tiny accuracy, no fuzz, but it's super tough actually to measure that accurately, or some such. If my startup works, I'll return to physics!!! I promise!! Thanks.
If the CDC weren't explicitly prevented from studying gun violence[1], they might be able to look into these problems. It's too soon to know if the recent (2018) changes to the interpretation will make a difference.
We're in an investee's market right now. Investors are throwing large amounts of money at anything that might have a positive return. This gives the founders/CEOs/etc. a lot more power to get away with this kind of stuff. If their behavior scares off one investor, there will still be a line waiting to give them money.
When things swing the other way, and not as much money is floating around waiting to be invested, investors will be able to hold the investees to higher standards.
Pathos was founded to revolutionize precision medicine in cancer by harnessing the power of machine learning to transform drug development. Pathos aims to accelerate traditional oncology approaches based upon a comprehensive and integrated data-first strategy to discover and develop drugs for precise biological pathways. Pathos is currently pursuing co-development and in-licensing opportunities to build a portfolio of clinical stage oncology assets, applying its technology to find the right patients and indications, resulting in a highly improved probability of success and faster time to market.
I'm hiring for software engineers, with a focus on cloud infrastructure. We'll be developing infrastructure for data analysis and storage, processing and analysis pipelines, and internal applications. Engineering writes code mostly in Python, while our scientists prefer R. We use Google Cloud Platform for our infrastructure. Currently, the team is just me, but we are looking to hire at least 1 more full time engineer.
An ideal candidate will have at least 2 years of experience developing software in a professional environment, with at least 1 year of that working with Google Cloud Platform.
Nice-to-haves are experience with scientific computing, experience with bioinformatics tools and/or biological and medical data, and experience with Python, R, PostgresSQL, and containers. Experience securing data and applications would also be nice.
There's a small amount more about the company at: https://pathos.com/ Please send a resume to [email protected]