LINGUIST List 29.2574

Mon Jun 18 2018

Jobs: Computational Linguistics; Semantics; Syntax: Post Doc, Queen Mary University of London

Editor for this issue: Sarah Robinson <srobinsonlinguistlist.org>


Date: 18-Jun-2018
From: Massimo Poesio <m.poesioqmul.ac.uk>
Subject: Computational Linguistics; Semantics; Syntax: Post Doc, Queen Mary University of London, United Kingdom
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University or Organization: Queen Mary University of London
Department: Computational Linguistics Lab, School of Electronic Engineering and Computer Science
Job Location: London, United Kingdom
Web Address: http://compling.eecs.qmul.ac.uk/
Job Title: Research Assistant

Job Rank: Post Doc

Specialty Areas: Computational Linguistics; Semantics; Syntax


Description:

3 years Postdoctoral Position on the (Computational) Linguistics of Anaphora/Coreference and Anaphoric Ambiguity

Applications are invited from outstanding computational linguists / NLP researchers combining an excellent background in theoretical linguistics (in particular semantics) with demonstrated exciting research skills in the use of machine learning methods for NLP/CL , for a three-year Postdoctoral Research Assistant position in DALI, a project funded by the European Research Council (ERC) on using games-with-a-purpose to collect very large datasets to support research in the linguistics and interpretation of anaphoric expression/coreference.

The main responsibility of the post will be analyzing the data about anaphora and anaphoric ambiguity already collected using the Phrase Detectives game (over 4.5 million judgments) and those that will be collected through a range of games under development, identifying the main sources of disagreement among our players, and use the insights thus obtained to push forward our understanding of the linguistics of anaphora and the state of the art in computational modelling of anaphora resolution. The chosen candidate will also be expected to provide input in the development of new games so as to improve the quality of the data collected. He/she will lead and co-author a range of outputs of the project; and contribute to the dissemination of research findings to a range of stakeholders and audiences.

The successful candidate will hold a PhD with a focus on computational linguistics / NLP, theoretical linguistics, or machine learning for NLP. A strong background in theoretical linguistics in general and semantics in particular, ideally with a focus on anaphora, is essential. Demonstrable skills in using computational and machine learning methods to analyse large amounts of linguistic data and developing computational models of semantic/discourse interpretation (ideally, anaphora resolution or coreference), also essential.

Strong programming skills, particularly in languages used in CL/NLP such as Python, Perl, Java, R. Familiarity with languages for building NNs such as Tensor Flow a definite plus. The candidate is also expected to have excellent analysis and abstraction skills, and an interest in working in a research environment.

The positions will be funded by the ERC Advanced Grant DALI; Details can be found at http://dali.eecs.qmul.ac.uk/

The successful candidate will join a team based in the Cognitive Science Research Group at Queen Mary University of London (see web address) but also including collaborators from the Games and AI research group at QMUL and from the Language and Computation Group at the University of Essex.

This is a full time post for 3 years or until 31 Aug 2021 (whichever is the shorter) starting 1 September 2018 or as soon as feasible after this date. The starting salary will be £36,677 -£43,152 per annum inclusive of London allowance. Benefits include 30 days annual leave, defined benefit pension scheme and interest-free season ticket loan.

Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. Where required this may include entry clearance or continued leave to remain under the Points Based Immigration Scheme.

Informal enquiries should be addressed to Massimo Poesio at the below contact email. For more information and how to apply, please visit the application link below.

Application Deadline: 30-Jun-2018

Web Address for Applications: https://webapps2.is.qmul.ac.uk/jobs/job.action?jobID=3294
Contact Information:
Massimo Poesio
Email: m.poesioqmul.ac.uk

Page Updated: 18-Jun-2018