Connectionists: Fully funded four-year PhD studentships: UKRI Centre for Doctoral Training in Natural Language Processing

[Frank Keller]

FULLY FUNDED FOUR-YEAR PHD STUDENTSHIPS

UKRI CENTRE FOR DOCTORAL TRAINING IN NATURAL LANGUAGE PROCESSING

Based at the University of Edinburgh: in conjunction with School of Informatics and School of Philosophy, Psychology and Language Sciences.

Deadlines:

* Non EU/UK:  29^th November 2019

* EU/UK:      31^st January 2020.

Applications are now sought for the CDTs second Cohort of students to start in September 2020.

                                 * * *

The CDT in NLP offers unique, tailored doctoral training comprising both taught courses and a doctoral dissertation.  Both components run concurrently over four years.

Each student will take a set of courses designed to complement their existing expertise and give them an interdisciplinary perspective on NLP. They will receive full funding for four years, plus a generous allowance for travel, equipment and research costs.

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 a team of over 40 world-class faculty and will benefit from cutting edge computing and experimental facilities, including a large GPU cluster and eye-tracking, speech, virtual reality and visualisation labs.

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.

A wide range of research topics fall within the remit of the CDT:

* Natural language processing and computational linguistics

* Speech technology

* Dialogue, multimodal interaction, language and vision

* Information retrieval and visualization, computational social science
         
* Computational models of human cognition and behaviour, including language and speech processing

* Human-Computer interaction, design informatics, assistive and educational technology

* Psycholinguistics, language acquisition, language evolution, language variation and change

* Linguistic foundations of language and speech processing

The second cohort of CDT students will start in September 2020 and is now open to applications.

Around 12 studentships are available, covering maintenance at the research council rate* (currently GBP 15,009 per year) plus tuition fees.  Studentships are available for UK, EU and non-EU nationals. Individuals in possession of other funding scholarships or industry funding are also welcome to apply -- please provide details of your funding source on your application.

Applicants should have an undergraduate or master's degree in computer science, linguistics, cognitive science, AI, or a related discipline. We particularly encourage applications from women, minority groups and members of other groups that are underrepresented in technology.

Further details including the application procedure can be found at: https://edin.ac/cdt-in-nlp


Application Deadlines

In order to ensure full consideration for funding, completed applications (including all supporting documents) need to be received by:

29^th November 2019 (non EU/UK) or 31^st January 2020 (EU/UK).


CDT in NLP Open Days

Find out more about the programme by attending the PG Open Day at the School of Informatics or by joining one of the CDT in NLP Virtual Open Days:

PG Open Day: 13^th November 2019

register via https://www.ed.ac.uk/studying/postgraduate/open-days-events-visits/open-days/programme

Virtual Open Day: 14^th November 2019

register via https://www.eventbrite.co.uk/e/75139952621

Virtual Open Day: 9^th January 2020

register via https://www.eventbrite.co.uk/e/75163007579


Enquiries

Any enquiries, please direct them to the CDT admissions team at: cdt-nlp-info at inf.ed.ac.uk.


*https://www.ukri.org/skills/funding-for-research-training/

-- 
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.