| More Information: | An open internship position on a mix of string algorithms, grammatical inference
and statistical machine learning
Description
We are looking for a motivated intern for a project involving the use of
sequential patterns for the inference of grammars.
The Smallest Grammar Problem is the problem of finding the smallest context-free
grammars that generates exactly one given sequence. We plan to generalize this
in order to find grammars which generate a set of natural language documents
with a strong but hidden structure. This structure will then be converted into
additional features (through tree kernels for example) in our analytics pipeline
or alternatively as a starting template for existing multilingual authoring
tools.
Requirements:
Research-oriented master student or PhD candidate in computer science
Knowledge of standard text algorithms and data structures
Knowledge of formal grammars (a course covering the Hopcroft & Ullman book or
equivalent for example)
Knowledge in statistical machine learning applied to text is a strong plus
Fluency in either C, C++ or Java is a plus
The intern will work closely with researchers in a very international
environment, and will be strongly encouraged to produce scientific
publications.
Duration: 5-6 months
Start Date: March-April 2014
Application instructions
Informal inquiries are welcome and can be made at matthias.galle@xrce.xerox.com
.
To submit an application, please send your CV and cover letter to both
xrce-candidates@xrce.xerox.com and matthias.galle@xrce.xerox.com .
Ideally, you will also include in your CV people we can contact for letters of
recommendation.
link:
http://www.xrce.xerox.com/About-XRCE/Internships/Grammatical-Inference-with-sequential-motifs
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