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Author here! Would love to answer any questions and get your feedback. We think that intersection of systems and ml has a lot of potential and would love those thoughts as well. Thanks!

Parker Institute for Cancer Immunotherapy | San Francisco, CA | Software Engineer & Data Scientist | full time, ONSITE

Parker Institute for Cancer Immunotherapy (http://www.parkerici.org/) is a new organization formed to accelerate the cancer research effort. We are focused on immunotherapy - leveraging the patient's own immune system to fight disease.

We are building software engineering and data science teams. Software engineers will focus on data storage and retrieval, compute frameworks, and bioinformatics algorithm implementation.

To apply, email us with a description of your best programming project.

Data scientists will focus on:

1) building pipelines to process a wide range of biological data types and

2) leveraging bleeding edge machine learning and visualization algorithms to identify promising research directions, in very close collaboration with Parker Institute scientists. Working knowledge of basic biology and strong communication abilities are key.

To apply, tell us about a time you had to work with a large messy biological data set.

Get in touch: ccary@parkerici.org

Parker Institute for Cancer Immunotherapy | San Francisco, CA | Software Engineer & Data Scientist | full time, ONSITE

Parker Institute for Cancer Immunotherapy (http://www.parkerici.org/) is a new organization formed to accelerate the cancer research effort. We are focused on immunotherapy - leveraging the patient's own immune system to fight disease.

We are building software engineering and data science teams. Software engineers will focus on data storage and retrieval, compute frameworks, and bioinformatics algorithm implementation.

To apply, email us with a description of your best programming project.

Data scientists will focus on:

1) building pipelines to process a wide range of biological data types and

2) leveraging bleeding edge machine learning and visualization algorithms to identify promising research directions, in very close collaboration with Parker Institute scientists. Working knowledge of basic biology and strong communication abilities are key.

To apply, tell us about a time you had to work with a large messy biological data set.

Get in touch: ccary@parkerici.org

Parker Institute for Cancer Immunotherapy | San Francisco, CA | Software Engineer & Data Scientist | full time, ONSITE

Parker Institute for Cancer Immunotherapy (http://www.parkerici.org/) is a new organization formed to accelerate the cancer research effort. We are focused on immunotherapy - leveraging the patient's own immune system to fight disease.

We are building software engineering and data science teams.

Software engineers will focus on data storage and retrieval, compute frameworks, and bioinformatics algorithm implementation.

To apply, email us with a description of your best programming project.

Data scientists will focus on:

1) building pipelines to process a wide range of biological data types and

2) leveraging bleeding edge machine learning and visualization algorithms to identify promising research directions, in very close collaboration with Parker Institute scientists. Working knowledge of basic biology and strong communication abilities are key.

To apply, tell us about a time you had to work with a large messy biological data set.

Get in touch: ccary@parkerici.org

Duplicated and lost messages will happen in practice - TCP attempts to build reliable communication on an unreliable medium. Not clear from the paper if this matters.

I think the larger misunderstanding of the paper is the requirement that paxos have a leader - lamport's synod algorithm does not require a leader, the leader is an optimization!

Paper's network assumptions:

"We assume a model of reliable communication—messages cannot be lost (only delayed). This is a reasonable assumption if we consider a reliable protocol, such as TCP."

Paxos network assumptions:

"Messages can take arbitrarily long to be delivered, can be duplicated, and can be lost, but they are not corrupted." - http://research.microsoft.com/en-us/um/people/lamport/pubs/p...

Parker Institute for Cancer Immunotherapy | San Francisco, CA | Software Engineer & Data Scientist | full time, ONSITE

Parker Institute for Cancer Immunotherapy (http://www.parkerici.org/) is a new organization formed to accelerate the cancer research effort. We are focused on immunotherapy - leveraging the patient's own immune system to fight disease.

We are building software engineering and data science teams.

Software engineers will focus on data storage and retrieval, compute frameworks, and bioinformatics algorithm implementation. To apply, email us with a description of your best programming project.

Data scientists will focus on: 1) building pipeline to process a wide range of biological data types 2) leveraging bleeding edge machine learning algorithms to identify promising research directions 3) communicating these results to clinical and biological researchers. To apply, email us about a time you had to work with a large messy biological data set.

Get in touch: ccary@parkerici.org

Parker Institute for Cancer Immunotherapy | San Francisco, CA | Software Engineer & Data Scientist | full time, ONSITE

Parker Institute for Cancer Immunotherapy (http://www.parkerici.org/) is a new organization formed to accelerate the cancer research effort. We are focused on immunotherapy - leveraging the patient's own immune system to fight disease.

We are building software engineering and data science teams.

Software engineers will focus on data storage and retrieval, compute frameworks, and bioinformatics algorithm implementation.

Data scientists will focus on bioinformatics.

Get in touch: ccary@parkerici.org

Hey, could you msg me to talk about this. Thanks!

If you think stuff like this is cool, and you'd like to be a part of the software engineering effort at Parker Institute for Cancer Immunotherapy, msg me. ccary@parkerici.org

We are building out our platform for bioinformatics. Some engineering topics:

* Large scale data processing (Cloud & on-prem HPC based)

* Bioinformatics / ML algorithms

* Data storage & retrieval (File systems & databases)

i dig it

I really like this.

Is that a challenge?

yes, we need macros, more macros. Then it will be good.

In all seriousness though, it's basically supposed to teach about function pointers.

I would never, ever recommend programming like this.

In response to the macros, i think that would make the program particularly hard to reason about because part of the program would be rewritten at compile time.

I would discourage the use of macros. I believe that Brian Kernighan would agree with me.

As a rule of thumb, it is better to use enums over #defines and avoid macros like death. Stick to the most standard, simple parts of the language and your programs will be most readable and likely elegant.

Does anyone else find the section "Don’t use someone else’s file system" a bit confusing? It starts off by convincingly saying O_DIRECT shouldn't be used and then goes on to say O_DIRECT works very well.

We are looking for feedback.

thanks for the answers everybody. I'll do a little bit of reading now. Nicely surprised about how much info got compiled here. Cheers!

Thanks for the suggestions everybody.

True. Do you know how that compares performance wise to other DNS servers?