Postdoc: Multimodal Language Tech & Digital Humanities

University of Helsinki; Helsinki; On-site; EUR 45,000 - 46,000; Full time

Job summary

The University of Helsinki invites a Postdoctoral Researcher in Language Technology or Digital Humanities for a 28-month fixed-term position starting January 2027. The role is based in the Multimodality Research Group, Department of Languages, Helsinki.

The appointee will build multimodal corpora with layered annotations, apply computer vision and large language models, and publish findings in lead- and co-authored papers, collaborating across humanities, CS, and engineering.

Qualifications

• PhD required in language technology, digital humanities or related field.
• Experience applying computational methods to large multimodal data is essential.
• Solid programming skills and experience with libraries for ML models are required.
• Experience building annotated datasets and handling large data with HPC is advantageous.
• Ability to work independently and in a multidisciplinary research group.

Responsibilities

• Contribute to building large multimodal corpora with multi-layer annotations across page-based and audiovisual media.
• Develop approaches using computer vision and large language models to annotate data.
• Evaluate and refine annotations using human-in-the-loop methods.
• Report results in lead- and co-authored publications submitted to suitable venues.

Skills

Programming

ML libraries

Data annotation

Teamwork

English proficiency

Education

Doctoral degree in language technology / digital humanities

Tools

High-performance computing

Computational libraries

Large language models

Job description

The University of Helsinki invites a Postdoctoral Researcher in Language Technology or Digital Humanities for a 28-month fixed-term position starting January 2027. The role is based in the Multimodality Research Group, Department of Languages, Helsinki.

The appointee will build multimodal corpora with layered annotations, apply computer vision and large language models, and publish findings in lead- and co-authored papers, collaborating across humanities, CS, and engineering.