Professor of Machine Learning
vor 2 Wochen
The University of Klagenfurt wants to attract more women for professorships. The University of Klagenfurt is pleased to announce the following open position at the Department of Artificial Intelligence and Cybersecurity, Faculty of Technical Sciences, in compliance with the provisions of 98 (open-ended) or 99 (limited to 5 years) of the Austrian Universities Act: Professor of Machine Learning / Data Science (all genders welcome) This is a full-time position. The decision on either 98 (open-ended term) or 99 (five-year fixed term) depends on the candidates' qualifications and will be made upon appointment. With approximately 12,000 students, the University of Klagenfurt is a young, vibrant and innovative university, located at the intersection of Alpine and Mediterranean culture in an area that offers exceptionally high quality of life. As a public university pursuant to 6 of the Austrian Universities Act, it receives federal funding. The Times Higher Education (THE) Young University Rankings 2021 ranked it among the 50 best young universities in the world. The university operates under the motto "Beyond Boundaries". In accordance with its key strategic road map, the Development Plan, the university's primary guiding principles and objectives include the pursuit of scientific excellence regarding the appointment of professors, favourable research conditions, a good faculty-student ratio, and the promotion of the development of early career researchers. Machine Learning and Data Science and their application in Artificial Intelligence open new opportunities for science, but also pose challenges for current and future societies. This position offers an opportunity to focus on cutting-edge Machine Learning and/or Data Science research and methods while critically engaging with their implications for people. We are looking for a highly qualified and internationally recognized scientist with high engagement in developing and sustaining an ambitious and innovative research programme. The professor will be involved in teaching in a variety of degree programmes, including the Bachelor's programme Robotics and Artificial Intelligence and the international Master programme Artificial Intelligence and Cybersecurity. Active and close collaboration with the Digital Age Research Center (DARC; ) established at the university is expected. The duties of the position include: Representing the field of Machine Learning / Data Science in research and teaching Teaching in relevant degree programmes at Bachelor's, Master's, and Doctoral level, both in English and German, as well as supervision of student projects and academic theses Advising and mentoring of students and early career researchers Competitive research grant acquisition and management Interdisciplinary collaborations, especially with the social sciences Contribution to the special focus area of Humans in the Digital Age Collaboration with industry partners Participation in university management Participation in third mission and public relations activities Required qualifications: Habilitation or equivalent qualification in Computer Science or a relevant neighbouring field Excellent research and publications in Machine Learning / Data Science, including theoretical and technical foundations Experience in the acquisition and management of competitive third-party funded research projects Teaching competence and experience at university level Experience in the (co-)supervision of academic theses Ambition to establish interdisciplinary collaborations Fluency in English Desired qualifications: Interdisciplinary experience Excellent scientific dissemination skills International experience Experience with academic administrative duties Competence in leadership and teamwork Competence in gender mainstreaming and diversity management German language skills are not a formal prerequisite, but proficiency at level B2 is expected within two years. The remit of the professorship requires that the successful candidate will establish Klagenfurt as primary place of work. The university is committed to increasing the number of women among the faculty, particularly in high-level positions, and therefore specifically invites applications from qualified women. Among equally qualified candidates, women will receive preferential consideration. People with disabilities or chronic diseases who meet the qualification criteria are explicitly invited to apply. The salary is subject to negotiation. The minimum gross salary for the position at this level (salary group A1 for University Staff according to the Austrian Universities' Collective Bargaining Agreement) is currently EUR 92,460 per year. In accordance with the Austrian Income Tax Act an attractive relocation tax allowance can be granted for the first five years in the case of appointments to professorships in Austria. The prerequisites are subject to examination on a case by case basis. Please submit your application in English by e-mail to the University of Klagenfurt, Office of the Senate, attn. Mag.a (FH) Sabine Seebacher via no later than 16 March, 2025, including: a mandatory principal part not exceeding five pages (). The submission of the mandatory principal part mentioned above constitutes a necessary condition for the validity of your application. one single PDF including: a letter of motivation a detailed scientific CV a comprehensive list of publications, talks, and of all courses taught a research statement a teaching statement a plan for interdisciplinary collaborations, especially with the social sciences supplementary documents where applicable (e.g., course evaluations) links to publicly available versions of your three most important publications within the scope of this professorship For general information please refer to the information leaflet provided at For specific information about the position please contact Univ.-Prof. Wolfgang Faber (). We regret that the university cannot reimburse applicants' travel and lodging expenses incurred as part of the selection and/or hiring procedure.
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Professor of Machine Learning
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