Professor of Machine Learning / Data Science

Digital Age Research Center (D!ARC) 
University Professors  | Full time
Application deadline:  2 October 2019
Reference code: 576/01-PERS/19

Announcement

The University of Klagenfurt strives to appoint a greater number of qualified women to professorships.

The University is pleased to announce the following open position, in compliance with the provisions of § 99 Austrian Universities Act:

Professor of Machine Learing / Data Science

This is a full-time position, commencing at the earliest opportunity with a fixed term of 5 years. The university may subsequently advertise a permanent position for a Full Professor of Machine Learning / Data Science.

The University of Klagenfurt is a young, vibrant, and innovative university with approximately  10,000 students and is located at the intersection of Alpine and Mediterranean culture in an area that offers exceptionally high quality of life. As public university pursuant to § 6 of the Universities Act, it receives federal funding. The university operates under the motto “Beyond Boundaries!”. The QS Top 50 Under 50 University Ranking 2020 rates it among the 150 best young universities worldwide.

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 in relation to the appointment of professors, favourable research conditions, a good faculty-student ratio, and the promotion of the development of young scientists.

The professorship will primarily be situated within the new “Digital Age Research Center (D!ARC)” that embodies the guiding theme “Humans in the Digital Age” of the university, but close collaboration with the well-established Faculty of Technical Sciences is also expected. The faculty was launched in 2007 and has since expanded to encompass the three specialist fields of computer science, information and communications technology, and mathematics, and is currently endowed with a total of 24 full professorships and 20 associate professorships (see www.aau.at/en/tewi/).

We are looking for a highly qualified and internationally recognized scientist who is capable of representing the subject in teaching and research, with high engagement in developing and sustaining an ambitious and innovative research program. Applicants from all areas of Data Science with a focus on Machine Learning are encouraged to apply.

Area of responsibility

The duties of the position include:

  • Representing the academic fields of Data Science with a focus on Machine Learning through research
  • Participation in relevant degree programs at Bachelor and Master level
  • Advising and mentoring of students and junior academic colleagues
  • Competitive research grant acquisition and management
  • Maintaining and expanding co-operations with industry partners
  • Contribution to public relations activities of department and faculty
  • Participation in university management

 

Requirements

Required qualifications:

  • Habilitation or equivalent qualification in a relevant field
  • Relevant doctoral degree
  • Excellent research and publication record in Data Science with a focus on Machine Learning
  • Embeddedness in the international research community
  • Excellent English language skills

Desired skills

The university also expects:

  • Proven university teaching record
  • Experience in the supervision of academic theses at all graduation levels
  • Experience in the acquisition, implementation, and management of third-party funded research projects
  • International experience
  • Willingness to co-operate with other research groups at the AAU, in particular at the Faculty of Technical Sciences
  • Capability to undertake interdisciplinary co-operation
  • Excellent scientific dissemination skills
  • Competence in the organization and leadership of teams
  • Competence in the field of gender mainstreaming and diversity management

Additional information

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 future professor shall establish Klagenfurt as her/his primary place of work.

The university is committed to increasing the number of women among the academic staff, 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 € 71,900 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 by e-mail, consisting of a mandatory principal part not exceeding five pages (for more detailed information please refer to www.aau.at/en/jobs/information and to the paragraph below), a comprehensive list of publications and lectures and of all courses taught, a research statement, as well as any supplementary documents where applicable (e.g. course evaluations), to the University of Klagenfurt, Office of the Academic Senate, f.a.o. Ms. Sabine Tomicich (application_professorship@aau.at) no later than October 2 2019. Submission of the mandatory principal part mentioned above constitutes a necessary condition for the validity of your application.

For general information please refer to www.aau.at/en/jobs. For specific information about the position please contact Wolfgang Faber (Tel.: +43 463 2700 3712; wolfgang.faber@aau.at).

The University of Klagenfurt will not reimburse applicants’ travel and lodging expenses incurred as part of the selection and/or hiring process.