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Details of Grant 

EPSRC Reference: EP/S022481/1
Title: UKRI Centre for Doctoral Training in Natural Language Processing
Principal Investigator: Lapata, Professor M
Other Investigators:
Lopez, Dr A Heafield, Dr K J Titov, Dr I
Keller, Professor F King, Professor S
Researcher Co-Investigators:
Project Partners:
adeptmind Amazon Web Services (Not UK) BBC
CereProc Limited dMetrics Emotech Ltd
Facebook (International) Fact Mata Ltd Microsoft
Mozilla Foundation Naver Labs Europe nVIDIA
Quorate Technology Limited RASA Technologies GmbH Sertis
SICSA Thomson Reuters Foundation To Play For Ltd
Toshiba
Department: Sch of Informatics
Organisation: University of Edinburgh
Scheme: Centre for Doctoral Training
Starts: 01 April 2019 Ends: 30 September 2027 Value (£): 6,802,748
EPSRC Research Topic Classifications:
Artificial Intelligence Computational Linguistics
Human Communication in ICT
EPSRC Industrial Sector Classifications:
Information Technologies Creative Industries
Related Grants:
Panel History:
Panel DatePanel NameOutcome
07 Nov 2018 UKRI Centres for Doctoral Training AI Interview Panel T – November 2018 Announced
Summary on Grant Application Form
1) To create the next generation of Natural Language Processing experts, stimulating the growth of NLP in the public and private sectors domestically and internationally. A pool of NLP talent will provide incentives for (existing) companies to expand their operations in the UK and lead to start-ups and new products.

2) To deliver a programme which will have a transformative effect on the students that we train and on the field as a whole, developing future leaders and producing cutting-edge research in both methodology and applications.

3) To give students a firm grounding in the challenge of working with language in a computational setting and its relevance to critical engineering and scientific problems in our modern world. The Centre will also train them in the key programming, engineering, and machine learning skills necessary to solve NLP problems.

4) To attract students from a broad range of backgrounds, including computer science, AI, maths and statistics, linguistics, cognitive science, and psychology and provide an interdisciplinary cohort training approach. The latter involves taught courses, hands-on laboratory projects, research-skills training, and cohort-based activities such as specialist seminars, workshops, and meetups.

5) To train students with awareness of user design, ethics and responsible research in order to design systems that improve user statisfaction, treat users fairly, and increase the uptake of NLP technology across cultures, social groups and languages.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.ed.ac.uk