Post-Doctoral Research Fellow in Natural Language Processing Research Group in Computational Linguistics Research Institute of Information and Language Processing
Salary £32,267 - £38,522 (level of appointment dependent on qualifications and experience) Duration: 3-year position Deadline: 16th April 2014 The Research Group in Computational Lingustics at the University of Wolverhampton, UK (http://clg.wlv.ac.uk) is inviting applications for a 3 year Post-Doctoral Research Fellow in Natural Language Processing. The applicant should have a PhD in Computational Linguistics, Computer Science or Natural Language Processing and proven research experience in these fields. The applicant should have experience of language technologies. Publications in peer-reviewed conferences are essential and publications in good journals are desirable. Experience of project proposal writing is ideal. The applicant should have some teaching experience within the field of Computational Linguistics and good knowledge of machine learning is required. A solid background in programming is required. The position also requires that the appointed person supports principal investigators of EC-funded projects. Therefore, the post-holder will have good communication and interpersonal skills including the ability to communicate with staff at all levels, in person, by telephone or in writing. The ability to work well in a team, to meet deadlines and manage a varied workload by effectively prioritising tasks is essential. Experience with general management of projects is desirable as well as experience in producing technical reports, summaries and project outlines. For informal enquiries please contact Prof. Dr. Ruslan Mitkov at r.mit...@wlv.ac.uk or his PA Pam Loi at pam....@wlv.ac.uk or +44 1902 321630. To apply online please follow the following link: https://jobs.wlv.ac.uk/wd/plsql/wd_portal.show_job?p_web_site_id=3045&p_web_page_id=180574 The closing date for applications is 16 April 2014, with interviews shortly after that. The University is eager to attract larger numbers of applications from groups of people currently under-represented in the staff population, especially from women and people from ethnic minority groups.
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