UKRI Centre for Doctoral Training in Natural Language Processing PhD
Study modes: Full-time
Programme website: UKRI Centre for Doctoral Training in Natural Language Processing
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.
Most students will undertake at least one internship during their PhD, working with companies such as Facebook, Google, Amazon, or Microsoft, or with or non-profits such as the Allen Institute for AI.
This is an essential aspect of your training, providing team working, project management, and software engineering experience. It also exposes students to a company-focused research culture, and provides them with valuable contacts for future job searches. Most of the CDT's industrial partners have agreed to host students as interns. Furthermore, we have partnered with the Alan Turing Institute to enhance our internship programme.
The CDT aims to attract students from a diverse range of backgrounds, including computer science, AI, maths and statistics, engineering, linguistics, cognitive science, and psychology. This interdisciplinary cohort requires a training approach that is more flexible than the standard three-year PhD, which is why this programme takes the form of a four-year PhD with integrated training. It interleaves training at the level of a master's degree (180 credits of courses and project work) with PhD research (480 credits). The advantages of this structure are:
- By mixing courses and PhD work, students gradually progress from classroom teaching to independent research. At the same time, research will inform their learning experience from the first day, and they can immediately apply skills learned in the classroom to their PhD project.
- Students can take the courses that are relevant to their research when they need them, rather than having to anticipate all their training needs in advance and front-load all their courses in year 1.
- The degree structure allows for maximum flexibility to accommodate a cohort of students with a wide range of backgrounds. Students who have a lot of prior NLP training, for example, would be expected to do a research-heavy first year (followed by advanced courses informed by their PhD project), while students with less relevant backgrounds can take a larger number of foundational courses upfront.
- While all students select an individual set of courses, there are also shared components that everyone takes, which together with a program of staff- and student-led events will promote cohort formation (e.g., the annual CDT Festival, the bimonthly Language Lunch, the weekly NLP speaker series, regular industry days).
Contemporary research in NLP uses complex machine learning models such as neural networks, and thus requires considerable computing resources. CDT students will have access to a large GPU (graphics processing unit) cluster and to a terabyte storage array, both dedicated for NLP research. Furthermore, they will have access to the Edinburgh Compute and Data Facility (ECDF), a central University resource that maintains a cluster of over 4,000 compute cores and a large high performance storage facility. A number of our industrial partners provide in-kind support to the CDT in the form of compute credits, GPU hardware, and access to proprietary datasets.
Some of the PhD projects conducted under the auspices of the CDT will involve lab-based experiments that investigate human language and speech processing. Students will use our state of the art experimental facility comprising sound studios, an anechoic chamber, an eye-tracking lab with three high resolution trackers, and a suite of experimental booths for perception experiments. The Bayes Centre includes a dedicated virtual/augmented reality lab combined with motion capture and eye-tracking.
The demand for NLP practitioners in industry, science, commerce, and the public sector outstrips supply. A wide range of companies are aggressively recruiting well-trained NLP experts because there are relatively few available. The CDT is designed to meet this training need.
Graduates will be part of a new generation of researchers with the technical skills and interdisciplinary awareness to become leaders in NLP.
Our existing research groups have produced graduates who now occupy academic positions in some of the best universities in the world; work for global leaders in the IT industry; or have jobs with a wide variety of SMEs (small and medium-sized enterprises) and start-ups, some of which they have founded.
A minimum UK 2:1 honours degree, or its international equivalent, in computer science, linguistics, cognitive science, AI, or a related discipline.Most students accepted to the programme hold a first class degree.
Applicants coming directly from a bachelors or masters degree are welcome.
We particularly welcome applications from members of communities under-represented in computer science.
Check whether your international qualifications meet our general entry requirements:
English language requirements
You must demonstrate a level of English language competency at a level that will enable you to succeed in your studies, regardless of your nationality or country of residence.
English language tests
We accept the following English language qualifications at the grades specified:
IELTS Academic: total 6.5 with at least 6.0 in each component
TOEFL-iBT: total 92 with at least 20 in each section
PTE Academic: total 61 with at least 56 in each of the Communicative Skills scores
CAE and CPE: total 176 with at least 169 in each paper
Trinity ISE: ISE II with distinctions in all four components
Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.
Degrees taught and assessed in English
We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:
We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries.
If you are not a national of a majority English speaking country, then your degree must be no more than three and a half years old at the beginning of your programme of study.*
(*Revised 8/11/2018 to provide more accurate information on English language qualifications expiry dates. Revised 22/03/2019 to provide more accurate/comprehensive information.)
Find out more about our language requirements:
Approximately 8 studentships are available, covering both maintenance at the research council rate of £15,009 per year and tuition fees. Studentships are available for UK, EU, and non-EU nationals.
Search for scholarships and funding opportunities:
- School of Informatics
- 10 Crichton Street
- Central Campus
- EH8 9AB
This programme is not currently accepting applications. Applications for the next intake usually open in October.
Start date: September 2019
Awards: PhD (48 mth FT)
You will be asked to submit a research proposal and CV.
Find out more about the application process for this programme on the Centre for Doctoral Training in Natural Language Processing website:
Find out more about the general application process for postgraduate programmes:
- School of Informatics
- 10 Crichton Street
- Central Campus
- EH8 9AB