Deep Learning for Text Understanding

Applications are invited for a three-year Postgraduate research studentship, supported by the School of Engineering and Applied Science, to be undertaken within the System Analytics Research Institute at Aston University.  The successful applicant will join an established experimental group working on natural language processing and machine learning.

The position is available to start in January or April 2017 (subject to negotiation).

Financial Support
This studentship includes a fee bursary to cover the home/EU fees rate plus a maintenance allowance of £14,296 in 2016/17.

Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees each year of the course; currently this is £11,729 in 2016/17.  As part of the application you will be required to confirm that you have applied for, or, secured this additional funding.

Background of the Project
Deep learning has gained significant interest in recent years due to ground breaking results in various areas including natural language processing, computer vision and speech recognition.  Deep learning approaches employ many-layered neural networks that automatically learn hidden semantic structures at different levels of abstraction from the raw data such as text, images, video and audio signals. This project aims to explore novel deep learning architectures/algorithms for text understanding such as sentiment analysis, opinion mining, question answering, reading comprehension, etc.

Person Specification
The successful applicant should have a first class or upper second-class honours undergraduate degree or a relevant Masters Degree or equivalent experience in Computer Science, Mathematics, Statistics or a related discipline. Preferred skill requirements include knowledge/experience of machine learning, natural language processing or statistical modelling.

For informal enquiries about this project, contact Dr Yulan He email: [email protected], web: https://sites.google.com/site/yulanhe8/

The online application form, reference forms and details of entry requirements, including English language are available here.

Applications must also be accompanied by a research proposal giving an overview of the main themes of the research, and explaining how your knowledge and experience will benefit the project.

Details of how to write your project proposal are also included in the How to Apply section.