Ehud Reiter's Blog

Ehud's thoughts and observations about Natural Language Generation

I have funding for a PhD student to work with me on Advanced Data Storytelling at Aberdeen University.  The student will collaborate with and be partially supervised by Arria NLG staff, and will be expected to spend 6 months working as an intern at Arria (www.arria.com).

The position is funded by EPSRC, so funding is only available for UK and EU nationals with 3 years residency in the UK.

Application deadline is *23 June 2017* (apologies for short notice!).  See FindAPhD for more information and instructions on how to apply.

Project Desciption (From FindAPhD)

There is growing interest in software systems which can tell stories (in English) about real-world data. After all, humans have evolved so that they often perceive and explain the world via stories, and often the best way to present complex data to a doctor or engineer is via a story. At the same time, there is also a growing body of research on generating fictional stories using computational creativity techniques. The goal of this project would be to bring these worlds together, and in particular explore whether techniques developed for generating fictional stories can be adapted to telling stories about real-world data, in order to support doctors, engineers, and other people who need to understand and act on data.

This project will be done in conjunction with Arria NLG (www.arria.com), which specialises in building Natural Language Generation (NLG) computer systems that tell stories about data; these stories support and empower people who need to understand the data. Arria is very interested in exploring whether techniques developed for generating fictional stories could enhance its technology. The student will collaborate with and be partially supervised by Arria staff throughout his or her studies. He or she will also be expected to spend 6 months working as an intern at Arria, which will provide a deep understanding of Arria’s technology and clients.

The successful candidate should have, or expect to have, an Honours Degree at 1st Class (or equivalent) in Computing Science or related discipline.