LINGUIST List 21.3086 Tue Jul 27 2010 Jobs: Comp Ling; Text Classification: Post Doc, Trinity College Dublin Editor for this issue: Christy Bird <christylinguistlist.org> The LINGUIST List strongly encourages employers to use non-discriminatory standards in hiring policy. In particular we urge that employers do not discriminate on the grounds of race, ethnicity, nationality, age, religion, gender, or sexual orientation. However, we have no means of enforcing these standards. Job seekers should pay special attention to language in ads regarding employment requirements and are encouraged to consult our international employment page at http://linguistlist.org/jobs/jobnet.html. This page has been set up so that people can report on the employment standards of various countries. To post to LINGUIST, use our convenient web form at http://linguistlist.org/posttolinguist.cfm Directory         1.    Carl Vogel, Computational Linguistics; Text Classification: Post Doc, Trinity College Dublin, Ireland Message 1: Computational Linguistics; Text Classification: Post Doc, Trinity College Dublin, Ireland Date: 27-Jul-2010 From: Carl Vogel <vogelcs.tcd.ie> Subject: Computational Linguistics; Text Classification: Post Doc, Trinity College Dublin, Ireland E-mail this message to a friend University or Organization: Trinity College Dublin Department: School of Computer Science and Statistics Job Location: Dublin, Ireland Web Address: http://www.cngl.ie Job Rank: Post Doc Specialty Areas: Computational Linguistics; Text Classification Description: [Apologies for Multiple Postings; Please pass on to colleagues and students as appropriate.] Please note that this position is distinct from another very recently advertized computational linguistics position at TCD on outlook analysis. Post-doctoral position in Text Classification and Automatic Labelling The Computational Linguistics Group at Trinity College Dublin is looking for applications for ONE Postdoctoral position in the area of text classification and automatic labelling of text streams. The position is part of a large research project 'Next Generation Localisation' (CNGL) involving a consortium of leading Irish Universities (DCU, TCD, UCD and UL) and Industry Partners, funded by the Science Foundation Ireland (SFI). The project focuses on Language Technology and Digital Content Management in Localisation. Localisation is the industrial-scale adaptation of digital content to domain, culture and language. Successful candidates will join a team of Postdoctoral researchers, PhD students and research advisors from academia and industry. Details of the advertised posts are as follows: POSTDOC.ILT3: Postdoctoral Position in 'Text Categorisation' - Description: The successful candidate will research and develop algorithms for automatic annotation of localisation metadata, and multilingual text type and genre classification. Candidates must have a strong background and research record in machine learning and data-intensive natural language processing, as well as good programming skills. - Starting date: 3rd quarter 2010 - Duration: 12-18 months. - Salary: Approx. 38,000-44,000 Euro per annum depending on experience and qualifications. For further details, please contact Martin Emms (mtemmstcd.ie) Carl Vogel (vogelcs.tcd.ie). To apply, please email a CV and contact details for two references by August 31, 2010 to Jean.Maypothercs.tcd.ie. Please include the job reference ('POSTDOC.ILT3') in the subject line of all email correspondence. See http://www.cngl.ie for details on the broader goals of the project. While the deadline is August 31, 2010, applications will be considered until the position is filled. Application Deadline: 31-Aug-2010 Email Address for Applications: Jean.Maypothercs.tcd.ie Contact Information: Carl Vogel Email: vogelcs.tcd.ie Phone: 353-1-896-1765 Read more issues|LINGUIST home page|Top of issue Page Updated: 27-Jul-2010       About LINGUIST    |   Contact Us       While the LINGUIST List makes every effort to ensure the linguistic relevance of sites listed on its pages, it cannot vouch for their contents.