Professor of Machine Learning Methods 2

University of Graz; Graz; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

University of Graz seeks a professor to lead probabilistic machine learning with strong focus on methodological foundations and interdisciplinary applications across humanities, natural and social sciences. The role strengthens the IDea_Lab and fosters cross-faculty collaboration, teaching excellence and scientific leadership.

The appointed professor will advance probabilistic models, uncertainty quantification, and open science, and will build robust networks with partners inside and outside

Qualifikationen

• Austrian or equivalent foreign higher education degree corresponding with the position (doctorate/PhD).
• Habilitation or equivalent qualification in Mathematics, Computer Science or related disciplines.
• Outstanding academic qualifications in research and teaching in the relevant discipline and for the profile of the professorship.
• Success in attracting subject-specific project grants, particularly where competitively awarded third-party funds are concerned.
• Skills in higher education didactics including the use of digital media.
• Skills in the supervision and guidance of early career researchers.
• Professional experience abroad during academic career.
• Management and leadership experience.
• Gender mainstreaming and diversity management skills.
• Excellent knowledge of English and willingness to learn German.
• Outstanding scientific achievements in both the interdisciplinary applications and the methodological development of probabilistic machine learning.
• Experience and expertise in interdisciplinary collaboration, demonstrated by relevant publications in high-ranking journals of the respective application domain
• Experience and/or willingness for interdisciplinary teaching.
• Experience in science communication (preferable)
• Experience in open science (preferable)

Aufgaben

• Strengthen the methodological expertise of the IDea_Lab and promote interdisciplinary research.
• Be responsible for probabilistic ML teaching across the University of Graz.
• Build robust interdisciplinary research networks within the University and with partners.
• Develop novel interdisciplinary concepts and research approaches.

Kenntnisse

Interdisciplinary collaboration

Open science practices

Science communication

Leadership experience

English proficiency

Ausbildung

Doctorate / PhD

Habilitation or equivalent

Jobbeschreibung

Scientific Profile

The professorship focuseson the methodological foundations and applications of probabilistic machine learning methods in the interdisciplinary context of a comprehensive university. Probabilistic models and probabilistic machine learningmethods are key building blocksof modern AI and constitute a fundamental basis for the application of AI in the humanities, natural sciences, environmental sciences, law, social sciences, and economics.

Suitable candidates will, for example, address topics such as

• the development and analysis of probabilistic models (e.g. Bayesianmodels, latent variablemodels),
• efficient inference methods(e.g. sampling methods),
• uncertainty quantification, calibration, and probabilistic forecasting, as well as the interdisciplinary application of these methods.

The professorship is embedded in the IDea_Lab of the University of Graz, which is the recently established Interdisciplinary Digital Lab for foundational and application‑driven research in machine learning, data science and digital transformation. The professorship maintains close ties to statistics, optimisation, data science, applied mathematics, as well as the various specialised fields of the university.

The position is explicitly intended to strengthen the methodological expertise of the IDea_Lab, to promote interdisciplinary research in the field of probabilistic machine learning across the entire University of Graz, and to be responsible for this area in teaching. The appointed professor is expected to have a strong intrinsic interest in building robust interdisciplinary research networks withinthe University of Graz, startingfrom the inter‑faculty IDea_Lab, and in consolidating the field – together with the professorships already based at the IDea_Lab and research partners in the individual faculties and departments – through novel interdisciplinary concepts and research approaches.

Employment Requirements

• Austrian or equivalent foreign higher education degree corresponding with the position (doctorate/PhD)
• Habilitation or equivalent qualification in Mathematics, Computer Science or related disciplines
• Outstanding academic qualifications in research and teaching in the relevant discipline and for the profile of the professorship (commensurate with stage of academic career and interruptions in employment due to caring responsibilities)
• Success in attracting subject‑specific project grants, particularly where competitively awarded third‑party funds are concerned
• Skills in higher education didactics including the use of digital media
• Skills in the supervision and guidance of early career researchers
• Professional experience abroad during academic career
• Management and leadership experience
• Gender mainstreaming and diversity management skills
• Excellent knowledge of English and willingness to learn German
• Outstanding scientific achievements in both the interdisciplinary applications and the methodological development of probabilistic machine learning
• Experience and expertise in interdisciplinary collaboration, demonstrated by relevant publications in high‑ranking journals of the respective application domain
• Experience and/or and willingness for interdisciplinary teaching
• Experience in science communication (preferable)
• Experience in open science (preferable)

Selection Criteria

The successful candidate will be highly motivated, aiming for academic excellence and integrity in research and teaching. He/she will have demonstrated ability to collaborate constructively in a responsible manner and inspire colleagues and students in an interdisciplinary, internationally oriented context.

Application Documents

• Letter of application
• Curriculum vitae with a description of your academic career
• List of publications, numbered, with a complete bibliographic information, sorted by
  • monographs
  • (co‑edited volumes)
  • journal articles
  • other information
• Teaching statement including presentation of teaching to date
• List of previous research projects and collaborations
• Description of future research intentions
• List of your five most important publications

Please submit your application documents in English.

Equality Principle

The University of Graz is committed to increasing the proportion of female employees, especially in leadership roles. We therefore encourage qualified female colleagues in particular to apply for this position. In case of equal qualifications, women will receive priority consideration.

Please note that in order to comply with the applicable data protection regulations, we can only accept applications via our web-based applicant tool for this vacant position.

Hearing Dates

Planned dates of the applicant`s presentation: March 1-3, 2027

Contact

Univ. Prof. Dr. Martin Holler ([e-mail])