Common Lisp + Machine Learning Internship at Google (Mountain View, CA) | Hacker News Reader

Common Lisp + Machine Learning Internship at Google (Mountain View, CA)

45 pointsmoshe16 comments

I am seeking an intern to work on the open-source probabilistic learning of programs project over Summer 2009 at Google in Mountain View, CA. Probabilistic learning of programs (plop) is a Common Lisp framework for experimenting with meta-optimizing semantic evolutionary search (MOSES) and related approaches to learning with probability distributions over program spaces. Possible research topics to focus on include:

* Learning procedural abstractions

* Adapting estimation-of-distribution algorithms to program evolution

* Applying plop to various interesting data sets

* Adapting plop to do natural language processing or image processing

* Better mechanisms for exploiting background knowledge in program evolution

This position is open to all students currently pursuing a BS, MS or PhD in computer science or a related technical field. It is probably better-suited to a grad student, but I'm open to considering an advanced undergrad as well. The only hard and fast requirements for consideration are a strong programming background (any language(s)) and some experience in AI and/or machine learning. Some pluses:

* Functional programming experience (esp. Lisp, but ML, Haskell, or even the functional style of C++ count too)

* Experience with evolutionary computation or stochastic local search (esp. estimation-of-distribution algorithms and/or genetic programming)

* Open-source contributor (esp. Maxima)

* Interest in artificial general intelligence (i.e. building a thinking machine)

More info on plop at http://code.google.com/p/plop/, more info on the Google internship program at: http://www.google.com/jobs/students

Please contact me directly (email: madscience at google) with your info, so I can watch for your resume.

Thanks! Moshe Looks

P.S. Disclaimer: I can't promise anyone an internship, you have to go through the standard Google application & interview process for interns, yada yada ...

P.P.S. Any Googlers reading this and looking for a cool 20% project should contact me as well ;->

I am qualified, but I happen to be majoring in Economics. Why do you care about the degree?

"Currently pursuing a BS, MS or PhD in computer science or a related technical field." is verbatim from the intern job listing (http://www.google.com/support/jobs/bin/answer.py?answer=1262...), and I suppose it is there because the target audience for Google Engineering internships is students who are aiming to work some place like Google Engineering after graduating - not exactly the same category as "technically qualified students". So if you'd consider working at some place Google Engineering post graduation, then you should definitely apply.

For the record, I would consider economics to be a related technical field (cf. John von Neumann, cf. "Evolution of Cooperative Problem-Solving in an Artificial Economy" - http://www.whatisthought.com/hayek32000.pdf)...

The clearest description of what CS researchers talk about when they talk about "intelligence" (see http://www.vetta.org/definitions-of-intelligence/) is probably a production function from economics.

Related only to this comment... I happen to be an Economics major as well. I'm graduating soon and am getting nervous about having to search for jobs/internships in this field because it seems most employers are looking for CS degrees. I have taken courses on Java and web programming in the CS department as electives, but most of what I know I've learned on my own. I don't really know much about theory.

Should I just be working on building my portfolio? I feel like the more I concentrate on my projects, the more my GPA suffers. I'm caught in a dilemma where I'm split between school and career aspirations, and that doesn't seem normal to me... or is it?

If I could do college over again, I would major in CS, but it's too late to change my major now. I had a horrible CS teacher in high school that initially scared me away from the subject.

I was originally an economics major, but I've managed to switch out into a major in math and a minor in CS (the study of AI was just too seductive). One area of CS theory that is pretty straightforward to pick up for an economist is algorithmic game theory: (http://www.amazon.com/Algorithmic-Game-Theory-Noam-Nisan/dp/...). There are also some strong connections to reinforcement learning and multi-agent systems (indeed much new research in computational economics is focused on multi-agent systems).

"The only hard and fast requirements for consideration are a strong programming background (any language(s)) and some experience in AI and/or machine learning."

Damn. I wish I went to a university that Google takes seriously.

If you think you're qualified, apply.

I don't think it is open to international students, is it?

It is, actually.

Neat stuff! One thing you might want to look into (if you haven't already) is Probabilistic Incremental Program Evolution (PIPE) by Schmidhuber.

Nevermind, you cited it in your paper... :P

I'm thinking of applying(what can I loose) but I've just started self teaching myself Functional Programming so maybe next year. :)

I have gotten plenty of great applicants - thanks guys! Please stop sending me your application info at this point...

Whoa, sounds interesting.

:(

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