[POSTDOC] Research Associate – Semantic Interpretation of Personal Health messages (Fixed Term), UK

Research Associate - Semantic Interpretation of Personal Health messages (Fixed Term)
Department of Theoretical and Applied Linguistics, the University of Cambridge
Full details: http://www.jobs.cam.ac.uk/job/11935/ 

Applications are invited for a post-doctoral Research Associate position in the University of Cambridge, working with Dr Nigel Collier on the Semantic Interpretation of Personal Health messages (SIPHS) project. The project is funded by the EPSRC and aims to develop high 
throughput natural language processing methods for automatically encoding social media messages using concepts of health interest. Responsibilities of the successful candidate include but are not limited 
to research into innovative semantic techniques that address the challenge of understanding public health language in social media text. The project will also require the post holder to take part in system 
architecture design and implementation, performance evaluation, paper/proposal/document/report writing and presentation of research findings.

For further information about the project, see: http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M005089/1
The project will involve close collaboration with University College London, Public Health England, the European Bioinformatics Institute, the University of Utah, Linguamatics and the CORDS network and take 
place in the Language Technology Lab at DTAL: http://ltl.mml.cam.ac.uk/. This arrangement provides an excellent environment for research and career development, as the post holder will benefit from the expertise
of both NLP and domain partners in this multidisciplinary project.

Candidates will have completed (or about to be awarded) a Ph.D. in a relevant field such as computational linguistics, information retrieval, artificial intelligence, machine learning, bioinformatics or computer 
science and be able to demonstrate an excellent track record of independent research and strong publications. Essential skills include: excellent programming (e.g. Web-programming, scripting languages, R), 
statistical natural language processing techniques, machine learning, as well as proven collaborative/communication/networking skills. Familiarity with biomedical ontologies will be an advantage. Previous 
experience with social media data is not necessary.

Fixed-term: The funds for this post are available for 36 months.
Informal enquiries can be made to Nigel Collier (nhc30 at cam.ac.uk). 
Deadline for applications: December 12th 2016
Interviews are likely to be held in mid December.
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