PhD position in Computational Linguistics, Utrecht University, Netherlands
Department: LLC/UiL OTS
Institution/Organization: Utrecht University
Duties: Research,Project Work
Specialty Areas: Computational Linguistics
The Utrecht Institute of Linguistics (UiL OTS) invites applications for a PhD position in computational semantics in the research program ‘Forests and Trees: the Formal Semantics of Collective Categorization’, a five-year research program funded by an ERC Advanced Grant from, led by PI Yoad Winter. The project aims to investigate the mechanisms underlying our linguistic ability to conceptualize collections, as exemplified by the sentence “the Rockies are near” which categorizes a collection of mountains by estimating distance from the nearest mountain in the Rockies. Collective categorization forms an important probe into the connections between grammar and the mind, and is crucial for artificial intelligence. For instance, a command to a domestic robot such as “take those books out of their packages and arrange them alphabetically on the shelf” requires the robot to act on individual books while understanding internal relations within the collection. Spatial collective categorization is also important for natural language interfaces of Geographic Information Systems.
The research program takes an interdisciplinary approach and makes use of insights from linguistics and psychology, and methods from computational linguistics/natural language processing. The program consists of three work packages: in psycholinguistics, formal semantics and computational linguistics. This opening concerns a PhD position in the computational work package, to be carried out with the collaboration of Tejaswini Deoskar (ILLC/UvA and UU) and Joost Zwarts (UU).
This project makes use of large language corpora and modern machine learning methods in order to analyse spatially-based concepts expressed in language (“the Rockies are far”, “the books are inside the box”, “the soldiers are surrounded”). The project’s methodology involves an interaction between data-driven machine learning and semantic parsing, as well as principles in formal semantics for analysing spatially-based collective categorization. The PhD candidate will have the opportunity to study the above topic based on their own expertise and research ideas, while keeping to the broad goals of the project. The project offers collaboration with a broader team of NLP researchers (Khalil Sima’an, Jelle Zuidema, James Hampton).
Applicants should hold, or be about to complete, an excellent Master's degree in computational linguistics, computational psycholinguistics, artificial intelligence, computer science, or a related field. Candidates should have a strong background in artificial intelligence, machine-learning and computer science as well as an interest in formal semantics. Candidates with an interdisciplinary background are particularly encouraged to apply. Good programming skills, proficiency in spoken and written English, as well as a keen interest in problem solving and research are essential.
Tasks for the PhD candidate include:
- completion and defence of a PhD thesis within four years.
- regular presentation of intermediate research results at workshops and conferences.
- publication of at least two peer-reviewed articles in established international journals or conference proceedings.
- help with organizational tasks connected to the project, such as the organization of conferences and workshops.
- participation in all training programmes and expert meetings scheduled for the project.
- participation in selected training programmes scheduled for the Research Institute, Graduate School and the National Research School.
For further details about the program, the research environment and conditions as well as the requirements on candidates and applications please check the application website.
Applications Deadline: 15-Mar-2018
Web Address for Applications: https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs
Dr Maaike Schoorlemmer
m.schoorlemmer at uu.nl