I was trained as a computer scientist, but my research group has diverse interests in natural language processing, and we work on many problems in this area, from theoretical to empirical. We tend to focus on basic curiosity-driven research in areas that aren't yet well understood, in order to improve the foundations of the field. We view NLP as an interdisciplinary field, and to do interdisciplinary research, you need a discipline. So I look for collaborators from mathematics, machine learning, computer science, and linguistics. I don't expect you to be an expert in all of these fields—few people are—but I do expect you to learn something about all of them from a diverse of group of collaborators.

Prospective PhD students

I take one or two new PhD students each year. To apply, you must write a research statement. I am happy to discuss this with keen students, but I expect you to have done some reading and thinking first in an area of mutual interest, and I expect you to enter that discussion with some specific questions and ideas. To give you a flavor of things I'm currently interested in:

Natural language understanding systems confront a menagerie of complex and subtle phenomena. Deep learning is a useful tool in building these systems, but it’s only one tool among many, and we don't fully understand its power or its flaws. Projects in this area aim to improve our understanding; here are some examples:

  1. Deep learning researchers claim that their models learn to represent linguistic properties of language without any explicit guidance. But recent results hint that they are simply very good at memorizing local correlations. What do deep models really learn about language? We will use advanced techniques to probe their representations, and invent new techniques where we need to.
  2. For a system to understand a text and answer questions about it, the system must distill the meaning of the text into a set of facts (semantic parsing). We can represent these facts as a graph: entities and events become nodes, and relationships between them become edges. We now have datasets that pair text with such graphs, and we'd like to learn a semantic parser from this data, so we need to model graphs. How do we design and use deep probabilistic models of graphs?

I'm interested in many things involving language, structure, and learning. To get a sense of what some of those things are, you can read some of my recent papers. I am happy to discuss specific questions or ideas related to my published work. If you only have a vague idea and you want me to supply you with a topic, then I will simply refer you back to this page.

If you're excited about natural language, but not these topics, you may want to contact other members of Edinburgh NLP or browse PhD topics they have proposed. If you aren't interested in natural language, my research group is not a good fit for you, and you should contact a different supervisor in the School of Informatics.

If you're excited about all of this, I encourage you to apply for a PhD. I advise students in two different programs:

  1. PhD students in the Institute for Language, Cognition, and Computation. This is a three-year research-only program. Read the application guidance.
  2. MSc + PhD students in the Center for Doctoral Training in Data Science. This is a one-year MSc including coursework and research, followed by a three-year research-only PhD. Read the application guidance.

You cannot apply by emailing your documents to me. You must use the university's common application system, which you can find in the application guidance links above.

If you already have an MSc in a relevant area, you can apply for the ILCC PhD. If you do not have an MSc, or if you'd like to strengthen your technical background before starting your PhD, apply for the CDT. You can apply to both programs concurrently. Read more about the application process here.

I only review applications in winter admissions cycle. For a September start, apply by the second week of December in the preceding year. That is not a hard deadline, but applying by then ensures that the school will consider you for funding, which is crucial since we only make funded offers (unless you have a full outside scholarship). I cannot advise you on your chances of admission, which depend on factors outside my control.

Current students in Edinburgh

If you're interested in working with me and you are a current student in one of the CDTs; an MSc, MInf, or undergraduate honours student; or a currently enrolled visiting student, then please get in touch!

Prospective interns and visitors

I do not currently have any openings for internships. When I do, I will list them here. Please do not send me an unsolicited application.

I will not host visiting scholars who I do not know personally. If you are already visiting the university I am happy to talk about research.

Prospective Postdocs

I do not currently have any openings for postdocs.