The Natural Language Processing Group at the University of Edinburgh (EdinburghNLP) is a group of faculty, postdocs, and PhD students working on algorithms that make it possible for computers to understand and produce human language. We do research in all core areas of natural language processing, including morphology, parsing, semantics, discourse, language generation, and machine translation. EdinburghNLP also has a strong track record of work at the interface of NLP with other areas, including speech technology, machine learning, computer vision, cognitive modeling, social media, information retrieval, robotics, bioinformatics, and educational technology.

With 11 core faculty members, EdinburghNLP is one of the largest NLP group in the world. It is also ranked as the most productive group in the area, according to Our achievements include the award-winning neural machine translation system Nematus and the high-performance language modeling toolkit KenLM. EdinbughNLP faculty have a strong record of getting high-profile grants, and have so far won a total of five European Research Council (ERC) grants.

We are looking for new PhD students! Join us. Also, please check out the new UKRI Centre for Doctoral Training in Natural Language Processing!


🗣️Want to know more about the UKRI CDT in NLP @InfAtEd? Register for one of our 'Virtual Open Days' being held for potential Cohort 2020 students:
⏰Non EU/UK applicants: 14.11.19
⏰EU/UK applicants: 9.1.20
Details available here:

Applications very welcome for the UKRI Centre for Doctoral Training in Natural Language Processing @Edin_CDT_NLP at University of Edinburgh @InfAtEd! Details to apply:
⏰- non EU/UK applications: 29.11.19
⏰- EU/UK applications: 31.1.20

For the last talk of the day, @RicoSennrich sheds light on what Transformers learn, using pruning techniques among others.
@eurnlp #EurNLP


The Institute for Language, Cognition and Computation, part of @InfAtEd, is excited to announce 10 fully funded studentships in Computational Linguistics, Speech Technology and Cognitive Science. Details at

Next, Bonnie Webber talks about implicit relations in discourse. A nice example of discourse coherence:
The explicit and implicit inferences people make when following a recipe. @eurnlp #EurNLP2019

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