Research Associate – Corpus-computational linguistics and second language acquisition, University of Cambridge

A Post-Doctoral Research Associate position is available at the University of Cambridge to work with Dr Dora Alexopoulou and Professor Ianthi Tsimpli on the Leverhulme Trust grant “Linguistic typology and learnability in second language”.

The project aims to measure the impact of linguistic distance between L1 and L2 on the learning success of learners from different linguistic backgrounds. The empirical research will consist of a comprehensive corpus analysis exploiting the EF-Cambridge Open Language Database (EFCAMDAT) and the International Corpus of Learner English (ICLE). The main responsibility of the postdoctoral researcher is to conduct the corpus investigation and work with the investigators for the analysis of data and research publications.

The ideal candidate will have strong background in corpus linguistics and proven ability to work with NLP tools for extracting grammatical features and structures and to apply statistical analyses to the data. Experience with learner corpora and second language learning research is particularly welcome. Candidates will have completed a PhD in a relevant field.

The postdoctoral researcher will join the EF Research Lab for Applied Language Learning, the Processing and Language Acquisition Group and the Language Technology Group and become part of a multidisciplinary research community within Linguistics, and, more widely, within Cambridge Language Sciences.

This position is 100% FTE and funds for this post are available for 30 months in the first instance, starting on 16th of July 2018 or as soon as possible thereafter. The successful candidate will be a member of the Linguistics Section of the Faculty of Modern and Medieval Language.

The closing date for applications is midnight (BST) on 31st May 2018. Interviews will be held on 18 June 2018 at the Faculty of Modern and Medieval Languages, University of Cambridge, subject to confirmation.

For further information please visit

http://www.jobs.cam.ac.uk/job/17168/

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