Research Associate - Semantic Interpretation of Personal Health Messages (Fixed Term)

University of Cambridge - Department of Theoretical and Applied Linguistics

Applications are invited for one 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 public 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: and the Further information document (available at the link below).

Candidates will have a first degree in the area of Computer Science or a related discipline, and 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. Candidates must have strong experience with state-of-the-art statistical natural language processing techniques (semi-supervised/supervised machine learning, deep learning, distributed semantic representations) and software (e.g. R/Matlab/Weka), demonstrate research competence through a track record of independent research and strong publications in international quality venues, have strong proficiency in programming and systems skills (e.g. python, Java, Web-programming, LAMP etc.), excellent analytical skills, good academic writing and verbal communication skills and an ability to make progress on projects independently. Experience of working as part of a team and communicating effectively with project partners is essential. Prior experience in real-world deployment, knowledge of biomedical informatics and/or lifescience ontologies, knowledge of data privacy/anonymization methods and experience of working in interdisciplinary contexts are desirable. Previous experience with social media data is not necessary.

Fixed-term: The funds for this post are available for 36 months. 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 appointment will run from 1st February 2017 (or as soon as possible thereafter), 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 and to view further information about the role, please visit: This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form.

Applicants must provide the names and contact details of two referees who are familiar with your work in the relevant field whom we can contact for a reference once the vacancy has closed.

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

For queries about the post or application procedure, see the link above.

Please quote reference GZ10559 on your application and in any correspondence about this vacancy.

Share this job
  Share by Email   Print this job   More sharing options
We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:


South East England