24.2380, Jobs: Comp Ling; NLP: Post Doc, University of Edinburgh

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Mon Jun 10 18:54:52 UTC 2013


LINGUIST List: Vol-24-2380. Mon Jun 10 2013. ISSN: 1069 - 4875.

Subject: 24.2380, Jobs: Comp Ling; NLP: Post Doc, University of Edinburgh

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Date: Mon, 10 Jun 2013 14:52:57
From: Charles Sutton [csutton at inf.ed.ac.uk]
Subject: Computational Linguistics; Natural Language Processing: Post Doc, University of Edinburgh, Edinburgh, United Kingdom

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 University or Organization: University of Edinburgh 
Department: School of Informatics
Job Location: Edinburgh, United Kingdom 
Web Address: http://homepages.inf.ed.ac.uk/csutton
Job Rank: Post Doc

Specialty Areas: Computational Linguistics; Natural Language Processing


Description:

The School of Informatics at the University of Edinburgh is seeking an
excellent post doctoral research associate for a new EPSRC-funded project to
apply methods from statistical natural language processing and data mining to
find patterns in computer program source code. The project is supervised by Dr.
Charles Sutton.

Modern software developers often find it necessary to use software libraries
and programming languages with which they are unfamiliar, which can lead to
longer development times and lower reliability. However, on the Internet
billions of lines of open source code are readily available, code that
contains a large amount of implicit knowledge about good coding practice. The
goal of the project is to find patterns in large corpora of source code text,
which can be used to help developers to write better code, in effect
transferring knowledge from experienced developers to less experienced
developers.

Like natural language, programming languages are a means of human
communication: experienced programmers know that they are writing as much for
other programmers as for the computer. This raises the exciting possibility
that many aspects of programming language text can be just as amenable to
statistical analysis as natural language has been. But unlike natural
language, statistical analysis of programming language text is an area in its
infancy. This is a new domain for NLP, with many opportunities for developing
advanced new probabilistic models and machine learning algorithms.

The successful candidate will have a background in statistical language
processing or machine learning and a strong interest in the application area.
We will also consider applications from researchers in software engineering
who have strong interest in building their knowledge of techniques from
statistical NLP and machine learning. This is a new application area, so we do
not expect that candidates will have worked on both ML/NLP and source code.

The researcher will be a part of the School of Informatics at the University
of Edinburgh. This is an opportunity to work in a world-leading groups for
machine learning and NLP. More broadly, a recent international review
described the School as an "elite" department of computer science in Europe,
and in national research assessment exercises, the School of Informatics has
consistently ranked at the top in the UK for research quality.



Application Deadline: 19-Jul-2013 
	  
Web Address for Applications: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.display_form 
Contact Information:
	Charles Sutton 
	Email: csutton at inf.ed.ac.uk



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