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
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 (off-list) if you are interested.
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 ...