Postdoctoral position on using data collected through online games to
support research in the linguistics and interpretation of

Applications are invited from outstanding computational linguists / NLP
researchers combining an excellent background in theoretical linguistics
(in particular semantics) with (ideally) research skills in the use of
machine learning methods for NLP/CL , for a 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 holder 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, and in the development of new
models of anaphora resolution / coreference, focusing in particular on
those aspects of anaphora resolution that are most overlooked in current
models (e.g., discourse deixis, plurals). 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.


Queen Mary University of London


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 are also essential;
experience with developing computational models of semantic/discourse
interpretation (especially of anaphora resolution or coreference)
highly desirable. 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.

Educational level:

Ph. D.

How to apply:

Please mention NLP People as a source when applying


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About Queen Mary University of London

Queen Mary University of London is one of the UK's leading research-focused higher education institutions. Amongst the largest of the colleges of the University of London, Our 4,000 staff deliver world-class degree programmes to 18,000 students. Our research specialisms cross a wide range of subjects in Humanities and Social Sciences, in Medicine and Dentistry and in Science and Engineering. As a London university, we are unique in being able to offer a completely integrated residential campus, with a 2,000-bed award-winning Student Village on its Mile End site.