Research engineer in computational linguistics - Hiring in process/Finished, not possible to apply

Are you a computational linguist looking for new challenges?

The Humanities Lab is a certified knowledge center within the European Research and Infrastructure Consortium Common Language Resources and Technology Infrastructure (CLARIN ERIC) and a node in the Swedish national consortium for language technology, Nationella Språkbanken and Swe-Clarin. To meet the rapidly growing needs for support, guidance and project work in the domain of language technology, we need to boost our capacity especially in areas with a focus on text extraction, topic modelling, automated information extraction, and machine-based methods such as deep learning and word vectors.

Tasks

• Work with method development and projects on text extraction, topic modeling and automated information extraction, in collaboration with researchers from different disciplines; (e.g. language sciences, history, sociology, medicine, economics);
• Act as a contact person towards the lab's users, help to guide users to other units outside the lab; inform them about updates and other changes in the lab;
• Educate users through courses and workshops with a focus on both theory and practice;
• Act proactively towards other units at LU that work with AI and machine learning (e.g. AI@Lund, e-science eSSENCE, the graduate school COMPUTE, and LU's computing center LUNARC);
• Contribute to the Lab's local and national Swe-Clarin work and internationally in CLARIN ERIC; help coordinate resources.

Qualifications

You

• must have a PhD and a research background in a relevant discipline (computational linguistics, etc.);
• must have good knowledge and experience of topic modeling and contextualized representations of languages (word vectors);
• must have experience of practical work with NLP applications and machine learning;
• should have experience with developing NLP applications in suitable programming environments, e.g., Python;
• should have experience in producing linguistic resources for training and testing of NLP models;
• should have experience in visualizing and explaining NLP models;
• must have very good knowledge of Swedish and English.

Please include work samples from your own projects on github or colab.

Experience from a multi-user lab is an advantage. Other welcome features are flexibility and pedagogical ability since the work requires collaboration with users with very different levels of knowledge.