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