Computational linguistics is the science of understanding and modeling human language using computers. Since human language has many forms – spoken, signed and written – and involves various organs such as the vocal tract, ears, face, hands, eyes, and the brain, our research covers the full range of these modalities and senses.

Fluency in spoken communication – the ability to speak with smooth, natural timing and appropriate speed – forms the foundation of successful spoken interaction, enabling efficient and effective exchange of information. It is one of the most salient hallmarks of spoken language proficiency. While fluency has been extensively studied in speech communication, its role in sign language, where language is conveyed entirely through the visual-spatial modality, remains largely unexplored.
In a newly funded SNSF project, “Fluency in Speech and Signing” (FluSS), we aim to understand how utterance production and cognitive mechanisms in sign language compare to those in speech. Specifically, we will investigate whether the mechanisms that underlie fluency in speech also play a critical role in sign language fluency. The project consists of three closely interconnected subprojects: (1) Fluency across modalities and proficiency levels (Prof. Dr. Tobias Haug, University of Teacher Education in Special Needs, HfH), (2) Automatic analysis of fluency in speech and signing (Prof. Dr. Sarah Ebling, University of Zurich), and (3) Common cognitive processes in speech and signing (Prof. Dr. Volker Dellwo, University of Zurich). The project is carried out in collaboration with Prof. Dr. Nivja de Jong (Leiden University).

For Subproject 2, we are seeking a PhD candidate (4 years) at the Department of Computational Linguistics, University of Zurich. The subproject deals with automatic analysis of fluency in speech and signing: We will leverage machine learning methods-more specifically, deep learning methods-to investigate the automation of fluency analysis in speech and signing. The PhD position will focus on the sign language side.

The Department of Computational Linguistics conducts research and teaching in artificial intelligence for language and speech. Subproject 2 will be based in the Language, Technology and Accessibility group (Prof. Dr. Sarah Ebling) but will involve close collaboration with all other subprojects. The experimental work will be carried out in the laboratory of the Linguistic Research Infrastructure (LiRI).

• Conduct research throughout all phases of the project, adhering to the milestones and deliverables
• Develop approaches to sign language fluency analysis using machine learning (deep learning) methods, primarily focusing on the three sign languages of Switzerland
• Write a PhD thesis in the broader context of the project
• Present your findings at international conferences and in scientific publications
• Assume primary responsibility for the development and maintenance of a lab recording software
• Supervise student assistants in the project

• Excellent Master's degree in computational linguistics, computer science/computer vision, AI, or a related discipline
• Strong analytical programming skills (Python)
• Strong software engineering skills (lab recording interface)
• Theoretical and practical knowledge of machine learning (deep learning) methods, as demonstrated by familiarity with at least one major deep learning framework
• Experience in computer vision
• Experience in NLP is a plus
• Knowledge of or interest in open research data (ORD) approaches, including FAIR data
• Familiarity with camera technology
• Proficiency in English
• Knowledge of German is a plus
• Interest in sign languages and sign language linguistics; readiness to engage with the sign language community and to acquire one of the Swiss sign languages
• Preexisting knowledge of a sign language is a plus
• Very good communication, interpersonal, and organizational skills

Information on your application

• Excellent research conditions (including access to state-of-the-art equipment, infrastructure, and shared facilities) in a highly attractive city
• Friendly working environment in an enthusiastic interdisciplinary team
• Exchange with other research groups of the department as part of dedicated events (colloquia, lecture series)
• Salary in accordance with the cantonal regulations and the guidelines of the SNSF, starting from CHF 50'403 in the first year and increasing to 53'617 in the third year
• This position is limited up to 4 years