Start of employment February 2026, Employment 80 % (+ 20 % personal PhD contribution), temporary
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).
Your responsibilities
-------------------------
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
Your profile
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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 (oral and written)
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
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Our offer:
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
Please submit your application (cover letter with a description of your research interests, CV, academic records, programming samples, writing samples, references, optionally list of publications) as a single PDF file.
The application deadline ends when the position is filled. Review of applications starts November 20th, 2025.
What we offer
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Work-Life Balance
Flexible working models (such as part-time positions, mobile working, job-sharing)
Childcare at the kihz foundation of UZH and ETH
Learning and Development
Wide range of continuing education courses of UZH and the Canton of Zurich
Language Center run jointly with ETH Zurich
Food
Food and drinks at reduced prices in the UZH cafeterias
Lunch-Check-card with UZH contribution
Healthcare
Special conditions on the Academic Sports Association ASVZ
Free seasonal flu vaccinations
Rest and relaxation at the quiet room in the university tower
Discounts
Private traffic: Carsharing, rent a vehicle, parking space
Digitalization: Hardware, software, mobile phone subscriptions
Special conditions on hotel reservations
Conditions of Employment
Policies of the UZH
Most UZH staff are employed according to public law
International Services
Support for people from outside Switzerland
Campuses
Campuses Zurich City, Zurich Irchel, Oerlikon and Schlieren
Sites Zurich West, Old Botanical Garden, Botanical Garden and Lengg
Location
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###
Department of Computational Linguistics
Andreasstrasse 15, 8050 Zurich, Switzerland
Further information
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Questions about the job
Prof. Dr. Sarah Ebling
Working at UZH
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