Research Associate in Natural Language Processing (Fixed Term) University of Cambridge, Department of Theoretical and Applied Linguistics

Research Associate in Natural Language Processing (Fixed Term)

 


Applications are invited for a three-year Research Associate post on the project LEXICAL: Lexical Acquisition across Languages. The project is funded by the European Research Council (ERC) in the form of a Consolidator Grant awarded to Anna Korhonen. The aim is to develop a novel computational modeling framework for learning and transferring lexical and semantic information across languages without the need for parallel resources. The project will cover a variety of typologically diverse languages and language domains and will demonstrate the usefulness for NLP applications such as machine translation.

 

Responsibilities of the successful candidate include research into novel techniques for learning lexical and semantic information from multilingual text data, drawing from recent advances in the areas of lexical acquisition, computational semantics, multilingual NLP and machine learning (in particular, deep learning and joint learning and inference). The post holder will also take part in performance evaluation, and dissemination of research findings.

 

The successful applicant will have completed a Ph.D. degree in computational linguistics, artificial intelligence, machine learning, computer science, or a related discipline and will be able to demonstrate an excellent track record of independent research and strong publications. Essential skills include: excellent programming skills, statistical natural language processing techniques, machine learning, as well as proven collaborative/communication/networking skills. Previous experience with deep learning and/or joint learning and inference may be considered an advantage.

 

The RA will work with Anna Korhonen as part of the ERC project team. He/she will be a member of the vibrant and highly research-active Language Technology Lab at the Department of Theoretical and Applied Linguistics (http://ltl.mml.cam.ac.uk) and the larger community of researchers who conduct cutting-edge research into NLP and human language technologies within the University of Cambridge (http://www.languagesciences.cam.ac.uk/directory/research%20themes/language%20technologies).

 

Fixed-term: The funds for this post are available for 36 months in the first instance. This is a 100% FTE post. Salary for this post will be in the range of £29,301 - £38,183 per annum (points 39 to 48). Salary will normally rise annually by one point on the anniversary of appointment. The funds for this post are available for 3 years in the first instance. The appointment will run from 1st September 2017 for 36 months, and is subject to satisfactory completion of a probationary period of six months. The post is pensionable, and is based in the city of Cambridge.

 

To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

 

In order for your application to be considered, please upload a covering letter, two academic references, a detailed curriculum vitae, a list of publications (if not included in your CV) and one sample of a recent publication.

 

The closing date is midnight (BST) on 30th April 2017. Interviews are likely to be held during the week commencing 8th May 2017, subject to confirmation. The post is intended to start on 1st September 2017.

 

Informal enquiries may be made to Dr Anna Korhonen (alk23@cam.ac.uk). For questions of procedure, please contact the Personnel Administrator, at personnel@mml.cam.ac.uk or on 01223 760810.

 

Please quote reference GZ11749 on your application and in any correspondence about this vacancy.

 

The University values diversity and is committed to equality of opportunity.

 

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


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