Postgraduate Research Studentship in Natural Language Processing and Artificial Intelligence

Aston University - School of Engineering and Applied Science

(4 years)

Applications are invited to apply for a four year Postgraduate Research studentship, supported by the School of Engineering and Applied Science, to be undertaken within the Computer Science subject group at Aston University. The successful applicant will join the System Analytics Research Institute (SARI).

This studentship is combined with a teaching assistant role. The successful candidate will be required to provide up to an average of 6 hours per week of teaching support for a distance learning programme; therefore the student must be capable of teaching on an undergraduate course in Software Engineering. Details of teaching responsibilities and a list of taught modules can be found here.

The position is available to start in July 2018 (or earlier by agreement)

Financial Support

This studentship includes a fee bursary to cover the Home/EU tuition fee rate plus a maintenance allowance of £15,500 in 2017/18.

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, currently this is £12,005 for the 2017/18 academic year. 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

Option 1: Propositional Representation for Text Understanding

Although much advancement has been witnessed in machine comprehension (MMN, DMMN, EntityMMN; QA Tasks, TriviaQA), there is still a huge gap between machines’ computational way of “understanding” texts and how comprehension emerges in the human mind, which originates from the missing link between computational methods and psycholinguistic and cognitive models of text understanding (CI, Situation Model, Landscape Model, Review). This project therefore will explore the synergy of both the computational and cognitive/psycholinguistic models for towards machine comprehension of texts. (detailed version)

Option 2: Fine-Grained Scientific Knowledge Claim Extraction

Scientific discovery has been becoming more and more difficult due to the increase in the amount of scientific literature. This information overload problem has never been relieved due to an  inability to understand the semantics of the networked scientific papers. To facilitate scientific discovery, this project aims to enhance the current citation indexing with semantic searching facilities by automatic extraction of fine-grained scientific knowledge claims (AZ, CISP, CoreSC, Semantic Relation Typology, Scientific Argumentation) and identification of the evolution of science domain (Genealogical Tree, Main Path, Conceptual Trajectory). (detailed version)

Person Specification

The successful applicant will have a strong undergraduate (first class or upper second class) and/or Master’s degree in computer science, engineering, mathematics or a related discipline as well as strong interests in artificial intelligence, excellent programming abilities and good analytical/mathematical skills. Applicants from non-English speaking countries will need to satisfy Aston’s English language entry requirements.

Enquiries about this project contact Dr. Xiaorui Jiang by email:

Details of the online application process can be accessed here.

Applications should also be accompanied by a brief review of relevant research literature, and an explanation of how your knowledge and experience will benefit the project.

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