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Ask HN: Where are the hard programming challenges/jobs?

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Re: Ask HN: Where are the hard programming challenges/jobs?

#42
post #5

Try looking for bioinformatics jobs. It involves big data where the amount of data to be analyzed is growing exponentially every year, a lack of knowledge on what to research to provide meaningful results, and huge benefit when people come up with novel ways to interpret data successfully. It will involve acquiring some domain specific knowledge to be truly successful (what hard problem doesn't?), but you will be abl…

I second this. In computational biology we work on hard problems with real outcomes which potentially change or save lives. Some of the problems are probing at the fundamental mechanisms of life. We need more programmers who aren't afraid of hard problems.

Re: Ask HN: Where are the hard programming challenges/jobs?

#43

I don't know how you feel about working for the military-industrial-tech-surveillance-state but companies or universities that get DARPA or IARPA money work on stuff like flying and/or self driving cars, autonomous systems etc (Lockheed, Honeywell, Carnegie-Mellon, Raytheon, for examples). Of course these things will ultimately be used to crush humanity's soul, but they're interesting software and technical challenge…

I work in this industry, and have spent a number of years in R&D. In my experience, the vast majority of software R&D projects are not weapons/military related, and include things such as cyber security, healthcare, big data, cloud computing, etc. A lot of it is aimed at developing innovative approaches to reduce costs in various government/military processes both through automation and doing things more smartly and efficiently.

Re: Ask HN: Where are the hard programming challenges/jobs?

#45
Your attitude is common, but mistaken. It's another version of "the grass is always greener". Whether you're working on a self-driving car or implementing Microsoft Word 2014, the fundamentally hard parts are actually the same.

The self-driving car might sound sexier if you've never done something like that, but once you've learned the basics of how control loops work and the quirks of realtime operating systems, that's about it for novelty. What you'll actually spend your time on is the same old stuff: managing complexity. Debugging, testing, designing APIs, designing user interfaces, integrating disparate module, etc. You may actually find that it's more soul-crushing than a basic CRUD app, because in a safety critical project you'll probably have less autonomy, more oversight/bureaucracy, and a much slower pace.

The fundamentally hard part of any software project is complexity. It's easy to let even the simplest project spiral into unmanageable complexity, and it's deeply challenging work to prevent that. That's the meat of what any good software engineer does.

There's a better way to word your original question: in what kind of organization should I be writing software? That has a far bigger impact than the problem domain on your happiness, level of challenge, and autonomy.

Re: Ask HN: Where are the hard programming challenges/jobs?

#46
post #9

Follow the advice in http://steve-yegge.blogspot.com/2006/03/math-for-programmers... and learn math . Once you have the skills to do the interesting stuff, you start to see opportunities to do it in the oddest of places. For instance I've been paid to do things like statistics and machine learning on "simple CRUD apps". Maybe you won't be that lucky. But if you don't have the required skills, then you definitely won'…

Most machine learning work is the CRUD of math. It is plug-and-chug in standard toolkits.

Re: Ask HN: Where are the hard programming challenges/jobs?

#47
post #24
post #5

Try looking for bioinformatics jobs. It involves big data where the amount of data to be analyzed is growing exponentially every year, a lack of knowledge on what to research to provide meaningful results, and huge benefit when people come up with novel ways to interpret data successfully. It will involve acquiring some domain specific knowledge to be truly successful (what hard problem doesn't?), but you will be abl…

I'm slightly hijacking the thread here, but does HN have any recommendations on CS-heavy bioinformatics grad programs (not just US based)?

Threadjacking? This question should be a front page discussion, instead of gossipy crap.

I would love to know as well.

Re: Ask HN: Where are the hard programming challenges/jobs?

#48
post #5

Try looking for bioinformatics jobs. It involves big data where the amount of data to be analyzed is growing exponentially every year, a lack of knowledge on what to research to provide meaningful results, and huge benefit when people come up with novel ways to interpret data successfully. It will involve acquiring some domain specific knowledge to be truly successful (what hard problem doesn't?), but you will be abl…

+1 for bioinformatics - adding to that are the issues surrounding the complexity of the data (look up HL7 or CDISC to see how complex) and also the legal standards and ramifications (HIPPA, 21 CFR Part 11) of working with clinical research.

In short, getting domain knowledge in the above are essential to solve the tough problems at the big-pharma or national-bio-labs level.

(PS to the other poster looking for bioinformatics programs: I suggest you look in Boston - Tufts, MIT, Harvard etc)

Re: Ask HN: Where are the hard programming challenges/jobs?

#49
To be blunt, the simple problems are hard.

Concurrency. Locking. Cache invalidation. CAP Theorem for determining truth in distributed datasets. Feel free to solve any of them.

For the record, "I could do it if I had the time". Do it. It'll be awesome.

Reinventing the wheel is a great excercise, as long as you accept that your wheel will probably be inferior to the existing one. Or maybe it won't and it'll be the next big thing.

TL;DR, go write some code.

Re: Ask HN: Where are the hard programming challenges/jobs?

#50
post #5

Try looking for bioinformatics jobs. It involves big data where the amount of data to be analyzed is growing exponentially every year, a lack of knowledge on what to research to provide meaningful results, and huge benefit when people come up with novel ways to interpret data successfully. It will involve acquiring some domain specific knowledge to be truly successful (what hard problem doesn't?), but you will be abl…

I don't know, I still remember this from HN: http://madhadron.com/a-farewell-to-bioinformatics
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