Professor of NLP & Interdisciplinary Data Science

Iventa Austria Personalwerbung GmbH; Österreich; Vor Ort; EUR 84.587 - 103.384; Vollzeit

Benefits dieser Stelle

Flexible hours

Further education opportunities

Diversity-focused environment

Zusammenfassung

University of Graz seeks a Professor for NLP within IDea_Lab, emphasizing fundamentals and interdisciplinary applications across humanities, sciences, law and economics. The professorship aims to strengthen methodological expertise and expand research networks within the university.

The successful candidate will contribute to teaching, seek external funding, and promote collaboration across faculties while supporting interdisciplinary research in machine learning, data science and digital

Qualifikationen

• PhD/Doctorate required.
• Habilitation or equivalent in computer science, computational linguistics or related disciplines.
• Outstanding academic qualifications in research and teaching.
• Experience in attracting third‑party funding is desirable.
• Strong didactic skills and ability to use digital media.

Aufgaben

• Lead NLP-focused research across the University of Graz within the IDea_Lab.
• Foster interdisciplinary collaboration and teaching across faculties.
• Develop and implement methodological innovations in NLP and related fields.
• Engage in science communication and open science practices.
• Mentor early career researchers and build interdisciplinary networks.

Kenntnisse

Gender mainstreaming

Diversity management

English proficiency

Digital didactics

Leadership experience

Ausbildung

PhD/Doctorate

Habilitation or equivalent in CS/Computational Linguistics

Excellent research and teaching record

Experience abroad

Jobbeschreibung

University of Graz seeks a Professor for NLP within IDea_Lab, emphasizing fundamentals and interdisciplinary applications across humanities, sciences, law and economics. The professorship aims to strengthen methodological expertise and expand research networks within the university.

The successful candidate will contribute to teaching, seek external funding, and promote collaboration across faculties while supporting interdisciplinary research in machine learning, data science and digital