Programme

We have witnessed the rapid evolution of a wide range of natural language processing (NLP) systems that translate text, recognize or produce speech, answer questions, retrieve documents or facts, respond to commands, summarise articles, and simplify texts for children or non-native speakers. NLP is transforming the way humans communicate with each other and with machines. The rapid proliferation of online news, social media, and scientific articles has created an exploding demand for NLP systems that enable people to derive critical insights from massive streams of data in many languages.

The Centre for Doctoral Training (CDT) in Natural Language Processing is jointly run by the School of Informatics and the School of Philosophy, Psychology and Language Sciences. Its aim is to equip students with the fundamental skills for advanced research in NLP and language science, giving them foundations in: linguistics; machine learning, statistics, algorithms; programming; working with other modalities such as vision; and design, ethics, and responsible innovation as they apply to NLP systems.

The four-year training programme will give you a solid foundation in the challenge of working with language in a computational setting and its relevance to critical engineering, scientific, and ethical problems in our modern world. It also offers training in the key software engineering and machine learning skills necessary to solve these problems. The programme aims to have a transformative effect as we train and on the field as a whole, by developing future leaders and producing cutting-edge research in both methodology and applications.

The CDT brings together researchers in NLP, speech, linguistics, cognitive science, and design informatics from across the University of Edinburgh. Students will be supervised by over 40 world-class faculty and will benefit from cutting edge computing and experimental facilities. The CDT involves over 20 industrial partners, including Amazon, Facebook, Huawei, Microsoft, Mozilla, Reuters, Toshiba, and the BBC. Close links also exist with the Alan Turing Institute and the Bayes Centre.

Each student will take a set of courses tailored to complement their existing expertise: Students with previous degrees in computer science or maths will take more linguistics courses, while students with previous linguistics or cognitive background will take more programming and machine learning courses. In the first year, they will also undertake both an individual and group research project with different supervisors, to gain breadth and experience with different working styles.

Students will receive full funding for all four years, plus generous funding for travel, equipment, and research costs.