We are seeking applications from talented and highly motivated computer scientists and computational linguists for a PhD studentship as part of an Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership at the University of Cambridge.
Brief project description: The problem of integrating natural language texts and large-scale knowledge graphs has recently been gaining significant attention for several tasks including Information Extraction, Question Answering and Dialogue Generation. However a number of challenges exist including developing effective embedding methods to represent sparse and often incomplete relational data as well as handling word sense ambiguity.
The student will conduct innovative research exploring the fusion of running text with knowledge graphs, including the practical benefits for tasks such as Information Extraction and Fact Checking. The student will study under the supervision of Dr Nigel Collier, who has expertise in Machine Learning and Knowledge Representation.
The student will be a member of the Language Technology Lab (http://ltl.mml.cam.ac.uk). LTL was established in 2015 and is based in Theoretical and Applied Linguistics at the University of Cambridge. The lab is a vibrant research-led group of computer scientists and linguists and is part of a large community of NLP researchers in the University of Cambridge.
University of Cambridge
Successful applicants will have a good Master’s degree (equivalent of first-class distinction) in computational linguistics, artificial intelligence, computer science, or a related discipline, completed by 30 September 2019. He/she will have strong programming skills and previous experience in NLP, machine learning or knowledge representation. Previous experience with deep learning will be considered an advantage.
The grant covers university fees and maintenance for the period of three years.
About University of Cambridge
The University of Cambridge is a public research university based in England and is one of the oldest universities in the world.