PieSquared

Karius | Menlo Park, CA | ONSITE, Full-time | Molecular Biology, Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies. We're hiring molecular biologists, computational biologists, software engineers and data scientists. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're a software engineer, we're looking for experience in front-end, back-end, intrastructure, devops, bioinformatics, and machine learning. We have a varied list of challenges; we build large data processing pipelines to analyze data from in-house DNA sequencers, separate the signal from the noise and extract what we need, and visualize this in ways that are helpful for scientists and doctor; we build web apps and tools for biologists and doctors to use to plan, conduct, and analyze experiments; we work closely with molecular biologists to analyze data generated by these experiments and develop novel computational biology methods. We mostly use Haskell (for many things), Python (for bioinformatics), and React/ES6 (for front-end interfaces), backed by infrastructure built on top of AWS and Docker.

If any of this sounds exciting to you, please don't hesitate to get in touch with us: gstock@kariusdx.com

Take a look at our job postings on AngelList for more detail: https://angel.co/karius/jobs

Hey folks, I'm the speaker in this video. Happy to answer any questions about IHaskell if you have any! You can install it using `cabal` or `stack` from Github [0].

By the way, if this stuff interests you -- Haskell, data analysis, interactive computing, science, visualization, etc -- please consider joining us at Karius. Karius is the biotech startup where I work, and we do a ton of really cool bioinformatics and high-performance data analysis and use Haskell for some of our infrastructure, and would love to hear from you. See our Who's Hiring post [1] for more info, or contact me!

Big thanks again to Joe for recording this, this was a fun talk to give and I hope you enjoyed it.

[0] https://github.com/gibiansky/IHaskell [1] https://news.ycombinator.com/item?id=10822842

Karius | Menlo Park, CA | ONSITE, Full-time | Molecular Biology, Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies. We're hiring molecular biologists, computational biologists, software engineers and data scientists. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're a software engineer, we're looking for experience in front-end, back-end, intrastructure, devops, bioinformatics, and machine learning. We have a varied list of challenges; we build large data processing pipelines to analyze data from in-house DNA sequencers, separate the signal from the noise and extract what we need, and visualize this in ways that are helpful for scientists and doctor; we build web apps and tools for biologists and doctors to use to plan, conduct, and analyze experiments; we work closely with molecular biologists to analyze data generated by these experiments and develop novel computational biology methods. We mostly use Haskell (for many things), Python (for bioinformatics), and React/ES6 (for front-end interfaces), backed by infrastructure built on top of AWS and Docker.

If any of this sounds exciting to you, please don't hesitate to get in touch with us: gstock@kariusdx.com

Take a look at our job postings on AngelList for more detail: https://angel.co/karius/jobs

Cool project! What advantages does this have over using CloudFormation?

I think that's the #1 question people coming to the repo will have, so maybe the repo README should provide a detailed comparison :)

Karius | Menlo Park, CA | ONSITE, Full-time | Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies. (We're still in stealth mode, so apologies for the lack of detail in this post. Come talk to us for more info!)

We're hiring software engineers for front-end, infrastructure, devops, bioinformatics and machine learning. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're an engineer who's willing to learn about biological problems, or have experience in next-generation sequencing, feel free to contact us: gstock@kariusdx.com

We currently use Python, Scala, Bash, Ruby, and Haskell. If any of this appeals to you, please get in touch!

Some of the things we’re looking for in people (not all required):

• Comfortable and familiar with backend and frontend technologies (MVC, Postgres / ORMs, React)

• Experience with building infrastructure and devops (AWS, Puppet / Chef / Ansible, etc)

• Able to glide across the stack as needed

• Algorithms development background and strong understanding of practical implementation issues

• Deep understanding of probabilistic modeling, statistics and data structures

Potential responsibilities:

• Designing and implementing robust and scalable compute infrastructure on top of AWS

• Creating pipelines for analyzing, storing and visualizing complex genomic data.

• Research, implementation, and testing of new analysis methods in computational genomics, in particular related to sequence analysis and metagenomics.

Apologies, the email should be gstock@kariusdx.com

Also, feel free to contact me directly at agibiansky@kariusdx.com

Karius | Menlo Park, CA | ONSITE, Full-time | Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies.

We're hiring software engineers for front-end, infrastructure, devops, bioinformatics and machine learning. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're an engineer who's willing to learn about biological problems, or have experience in next-generation sequencing, feel free to contact us: greg@kariusdx.com

We currently use Python, Scala, Bash, and some Ruby, and have growing codebases in Haskell. If building the future of bioinformatics and wetlab automation in Haskell appeals to you, please get in touch!

Some of the things we’re looking for in people (not all required):

• Comfortable and familiar with backend and frontend technologies (MVC, Postgres / ORMs, React)

• Experience with building infrastructure and devops (AWS, Puppet / Chef / Ansible, etc)

• Able to glide across the stack as needed

• Algorithms development background and strong understanding of practical implementation issues

• Deep understanding of probabilistic modeling, statistics and data structures

Potential responsibilities:

• Designing and implementing robust and scalable compute infrastructure on top of AWS

• Creating pipelines for analyzing, storing and visualizing complex genomic data.

• Research, implementation, and testing of new analysis methods in computational genomics, in particular related to sequence analysis and metagenomics.

The author has some commentary on that here:

https://www.quora.com/What-does-it-feel-like-to-be-fired-fro...

I found it pretty interesting.

Karius | Menlo Park, CA | ONSITE, Full-time | Software (Full Stack)

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies.

We're hiring software engineers across the board to help us with infrastructure, backend, frontend, and webdev. Join us on the ground-level for this exciting journey to shape our technology, product and company culture. If you're an engineer who's willing to learn about biological problems, or have experience in next-generation sequencing, feel free to contact me directly: agibiansky@kariusdx.com

Some of the things we’re looking for in people (not all required):

• Comfortable and familiar with both backend and frontend technologies

• Able to glide across the stack as needed

• Algorithms development background and strong understanding of practical implementation issues

• Development experience on mobile, especially iOS

Potential responsibilities:

• Designing and implementing robust and scalable compute infrastructure on top of AWS

• Creating pipelines for analyzing, storing and visualizing complex genomic data.

• Creating robust and beautiful user interfaces to our customers and lab biologists.

We want you to have strong opinions -- backed by proven experience -- on how good systems should be built, as well as the ability and desire to roll up your sleeves and build them yourself. We are a lean, ‘Navy Seal’ team and looking for someone with a similar mentality to join us on our mission. We are looking for someone who is excited by the challenge of conceiving, architecting, and most importantly, implementing the infrastructure we’ll need to enable lightning fast diagnosis pipelines at scale, as well as large scale data analysis on complex genomic data.

Karius | Menlo Park, CA | ONSITE, Full-time | Molecular Biology, Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies.

We're hiring molecular biologists, computational biologists, software engineers and data scientists. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're an engineer who's willing to learn about biological problems, or have experience in next-generation sequencing, feel free to contact me directly: agibiansky@kariusdx.com

Some of the things we’re looking for in people (not all required):

• Comfortable and familiar with both backend and frontend technologies

• Able to glide across the stack as needed

• Computational genomics / bioinformatics background

• Algorithms development background and strong understanding of practical implementation issues

• Deep understanding of probabilistic modeling, statistics and data structures

Potential responsibilities:

• Designing and implementing robust and scalable compute infrastructure on top of AWS

• Creating pipelines for analyzing, storing and visualizing complex genomic data.

• Research, implementation, and testing of new analysis methods in computational genomics, in particular related to sequence analysis and metagenomics.

Take a look at IHaskell -- it's a kernel for Jupyter for Haskell.

If you'd like to just take a look, go to try.jupyter.org and select the "Welcome to Haskell" notebook!

Try installing IHaskell with `stack`. `stack` is fairly new but it's solved all my `cabal` hell related problems. I put IHaskell in Stackage recently so you should just need to install stack, `stack install ihaskell` using a recent Stackage nightly resolver, and then `stack exec -- jupyter notebook` to start. Alternatively just `git clone` and run `stack install` from the resulting directory. If you end up trying it again but still encounter issues please file issues for me on Github so I can help!

Karius | Menlo Park, CA | ONSITE, Full-time | Molecular Biology, Software (Full Stack), Computational Biology, Wet-lab Automation, Machine Learning

We are a team of crazy biologists, engineers, data scientists and clinicians on a mission to change forever the way infectious diseases are diagnosed and treated. We face incredibly interesting challenges in software engineering, machine learning and molecular biology, as we push the limits of diagnostics and genomic technologies.

We're hiring molecular biologists, computational biologists, software engineers and data scientists. Join us on the ground-level for this exciting journey to shape our technology, product and company culture.

If you're an engineer who's willing to learn about biological problems, or have experience in next-generation sequencing, feel free to contact me directly: agibiansky@kariusdx.com

Some of the things we’re looking for in people (not all required):

• Comfortable and familiar with both backend and frontend technologies

• Able to glide across the stack as needed

• Computational genomics / bioinformatics background

• Algorithms development background and strong understanding of practical implementation issues

• Deep understanding of probabilistic modeling, statistics and data structures

Potential responsibilities:

• Designing and implementing robust and scalable compute infrastructure on top of AWS

• Creating pipelines for analyzing, storing and visualizing complex genomic data.

• Research, implementation, and testing of new analysis methods in computational genomics, in particular related to sequence analysis and metagenomics.

To clarify: are interesting blog posts that double as job ads still allowed? It's fairly common for companies to post good technical blog posts that are also meant as a "look at this fascinating stuff we're doing – you could be doing it too!"

Sadly I'm not in the Bay Area for the next 3-4 weeks and missed the original message :) Also I'm not really the one organizing the BioCurious funding, so maybe not the right person to speak to on that matter...

Nonetheless I'd be delighted to meet you at some point, Experiment.com sounds like a pretty great organization :)

The SF Bay Area community bio labs (BioCurious and Counter Culture Labs [0]) are considering using this platform to try and fund their iGEM team, researching inducing UV resistance in E. Coli and then optimizing it with directed evolution. Community labs have effectively no funding to operate with, so these types of platforms (Experiment, Kickstarter, etc) are incredibly important for them.

If you'd like to support the SF Bay Area community labs and hobbyist biologists trying to do real research without academic and commercial funding, watch the Experiment.com biology section [1] over the next week or two!

[0] http://biocurious.org/ and https://counterculturelabs.org/ [1] https://experiment.com/discover

My main "side project" lately has been trying to get a job in the engineering side of biotech in the Bay Area. Meeting people is exciting! And part of this has been augmenting my blog [0] with some biology writing.

Other than that I've been helping my Google Summer of Code student with IHaskell [1] – soon we're going to have full widget support, supporting all the same widgets as IPython. Although I don't do most of the coding (the student is quite skilled and incredibly productive) I get the satisfaction of seeing something awesome being implemented for IHaskell!

[0] http://andrew.gibiansky.com [1] http://www.github.com/gibiansky/IHaskell

Are all of these companies actually hiring? And hiring through TripleByte?

Parsec is what originally got me interested in Haskell. I had played around with it via LYAH [0] before, but never really got into it. I wanted to write a compiler for a language I was playing with, and seeing Parsec convinced me I should dive in and learn Haskell, as it just lets you write parsers in an incredibly intuitive and quick way; for me at least, parser combinator libraries are much easier to use than parser generators, and are also a lot more modular.

Even if you're familiar with parsec and parsing in Haskell, this post includes a fairly good explanation of De Bruijn indices. I've seen them a few times already but this explanation made it click particularly well.

[0] Learn You a Haskell: http://learnyouahaskell.com/

It may also interest people here that the guidance system is written in Haskell. I originally saw this on Reddit, where one of the authors provides a bit more information on the technical aspects of the system [0].

[0] http://www.reddit.com/r/haskell/comments/3959r0/haskellbased...

I quite liked the application process, it was very smooth. I'm interested to see how the rest of the process goes – since the two interviews are just chatting about projects I've worked on and having someone watch me code, it doesn't seem to stressful. (Let's be honest – it's sometimes hard to get me to shut up about projects I've worked on or want to work on...)

I'm particularly interested in this as a startup filter. There are a lot of startups out there, many that I don't know about. I'm wondering if Triplebyte could help me find something I'm interested in by filtering out startups that I'm unlikely to be interested in. If they can do that, I'll be a huge fan, and if they can't (because I'm too picky), then it's not too time-consuming or stressful a process to have tried it.

Quick Note: I clicked on "careers" from your homepage and got an error [0].

It's really great seeing you on HN – great to see more and more Haskell jobs available!

[0] http://www.soostone.com/careers/application-engineer

For one thing, it's much harder to pay your own way through college now (impossible, depending on who you are). [0] [1]

[0] http://www.theatlantic.com/education/archive/2014/04/the-myt... [1] http://www.randalolson.com/2014/03/22/its-impossible-to-work...

I hope that the Rust devs end up doing the "right thing", which from this article seems like going back and fixing Rc, instead of just marking mem::forget as safe. They're still pre-1.0, and anything they do now they will be stuck with for a long, long time, especially if Rust succeeds as much as I hope it does.

Delaying 1.0 by a few weeks may seem like a big deal, but ultimately it is a self-imposed deadline. It's great to have those, but following them dogmatically might not be the best strategy. In cases like this, I generally lean towards slowing down and doing things right: otherwise you will pay the price ten times over later.

(That said, while I understand this issue, I don't know very much about the context in the Rust community, so I'm not actually sure that mem::forget should be unsafe. It was just the impression from the article and from previous Rust code I've read/written.)

Just released IHaskell 0.6, which supports and requires IPython 3.0 and higher! So you may now be able to use Hackage to install, and use with new IPython.

(That said if you have problems I still recommend the Github route; especially the bit about filing an issue with your problem!)

I recommend installing IPython 3 with pip, cloning the repository, and then running ./build.sh ihaskell. If that doesn't work, file an issue and I'll be happy to help figure out the installation woes. (Note that ihaskell install must be run for IPython to know about the kernel! Updating the documentation is the last bit before release... :) )

Hey all! Author of IHaskell and Kronos here. Feel free to ask any questions :)

Sadly Kronos is outdated now, because it is based on IPython 2. IHaskell now supports IPython 3 / Jupyter only, as of the release that I'm going to try to put on Hackage today. I strongly recommend installing from Github master now - we have two easy to read installation scripts for Linux and Mac (so no need to trust them blindly, you can just read their source to see what they do).

Someday when I have the time Kronos will get an overhaul. The Python version will become free - it makes no money, unsurprisingly - and you will be able to download kernels from the app, perhaps including Julia and others, instead of installing separate apps.

Both of those rely on having proper cabal/ghc or python/virtualenv preinstalled on the host computer; you could ship cabal/ghc and python/virtualenv and then use a sandbox or virtualenv, but at that point you might as well just use separate package databases. (This at least was the original motivation for the split – I suspect you could do similar things with virtualenv/sandboxes, it's certainly not the only point in the design space.)

Hey all! I'm really excited to announce this first release of Kronos Notebook, which is just IPython [0] packaged as a Mac app totally independent of any external environment. It comes with its own Python interpreter and package database, so the installation should consist literally only downloading the zip file, unzipping it into /Applications (or anywhere else you want to put it), and double clicking on it to run it.

If you'd like to see some of the cool things it can do, I recommend typing in the examples on the website (apologies – for now they're images...). In particular, the last example on the website demonstrating interactive widgets is my favorite :)

It includes a number of built-in packages and is capable of installing (through a dialog) many others – should work on most PyPi packages, though not ones that require linking to C libraries that aren't installed. You can export created notebooks to HTML and do all the other nice stuff IPython usually lets you.

This was created along the way to Kronos Haskell [1], which is my IHaskell IPython kernel [2] packaged together with GHC and Cabal by building on top of ghc-dot-app [3]. I took this as an opportunity to experiment with delivering a final, product ready Mac app, including the website, pricing, billing, etc. As a result, I'd love to have any feedback you have on anything, whether it's the application itself, the pricing, the website, or anything else. Happy to answer questions about anything, of course.

As an aside, note that there are some other alternatives to this, such as [4]. I think that Kronos is a bit more polished and self-contained – I really tried to go from "proof of concept" stage to "finalized application" stage. Those alternatives, however, were definitely a source of inspiration in coming to do this (though not in any code or structure or anything), so I think they're worth mentioning.

If you have any issues, please let me know. This is still a work in progress!

[0] http://ipython.org/notebook.html [1] http://www.kronosnotebook.com/haskell [2] https://github.com/gibiansky/IHaskell [3] https://github.com/ghcformacosx/ghc-dot-app [4] https://github.com/mangecoeur/ipython-desktop

I'm a big fan of the style used here, specifically the extra CSS on top of default IPython notebooks. If you're curious, like me, as to where the special styling is coming from – take a look at the last cell of the notebook. It imports some custom CSS into the notebook by reading it from a file, and this gets carried over to nbviewer since the output is stored in the notebook.