The following endowed professorship, funded by Gesellschaft für Forschungsförderung Niederösterreich (GFF NÖ), is offered at the Faculty of Health and Medicine in the Department for Evidence-based Medicine and Evaluation at the University for Continuing Education Krems, Austria:

 

Professorship for Artificial Intelligence in Health Service Research (m/f/d) according to § 98 UG (Austrian Universities Act)

min. 30-40 hrs./week

Inserat Nr.: SB25-0158

 

The professor will establish and lead a Center for Artificial Intelligence (AI) in Health Services Research within the Department for Evidence-based Medicine and Evaluation, part of the Faculty of Health and Medicine at the University for Continuing Education Krems (UWK). The professor will collaborate closely with the Centre for Evidence-based Health Services Research and Cochrane Austria, both integral units of the Department for Evidence-based Medicine and Evaluation, which together offer strong expertise in the application of AI to health services research.

A 20% secondment to the Institute of Machine Learning (IML) at Johannes Kepler University Linz (JKU) will foster intense knowledge exchange, ensuring that IML’s expertise in AI research translates directly into healthcare innovation. The professor will build a research team including two PhD positions (one at UWK and one at JKU).

Research Focus Areas:

  • AI for evidence synthesis and health communication: Developing Large Language Models (LLMs) that automate evidence synthesis and enhance health literacy by providing reliable, accessible health information.
  • Efficient AI models: Enhancing efficiency and scalability of LLMs with long-context processing while ensuring privacy-compliant, locally deployable solutions.
  • Optimization in healthcare: Improving healthcare processes and resource allocation through generative AI–based optimization methods for the analysis of routinely collected health data.

Your tasks:

  • Research leadership:
    Establish and lead an internationally visible research program in AI for health services research, integrating strategic vision with social, organizational, and economic leadership in managing research activities, resources, and collaborations.
  • Teaching and supervision:
    Develop and evaluate educational offerings (e.g. courses in master and PhD programmes, professional development courses, microcredentials), including a certificate program in AI for Health Services Research, and supervise doctoral candidates.
  • Funding acquisition:
    Secure competitive national and international research grants.
  • Academic and public engagement:
    Promote the visibility of the Centre’s work through high-impact publications, conference presentations, and engagement with broader academic, healthcare, and societal communities (including "third mission" activities).

 

Your profile:
To be considered for the position, the following selection criteria must be met:

  • Completed university degree (doctorate/PhD) in Computer Sciences, Data Sciences, Natural Sciences, Life Sciences or a closely related field as well as a habilitation or an equivalent qualification
  • Expertise in sub-symbolic AI or a closely related field
  • Proven track record (e.g. ERC Grant, Ellis Network, non-peer reviewed papers, international peer-reviewed conference workshops etc.) of research in the development of state-of-the-art machine learning or other AI methods
  • Publication history in top-tier conferences in the field of machine learning (e.g., Conference on Neural Information Processing Systems [NeurIPS], International Conference on Learning Representations [ICLR], International Conference on Machine Learning [ICML]).
  • Experience in leading research projects involving the design and adaptation of modern AI methods to real world problems in interdisciplinary collaborations
  • Experience in acquiring research grants and external funding from public or industry sources
  • Strong academic teaching experience in machine learning, and deep learning at the graduate and undergraduate levels and didactic skills
  • Gender equality and diversity competence; if this is not the case, the willingness to complete appropriate further training within two years of taking up the professorship
  • Excellent written and spoken English (min. C1) and German (min. B2)

In addition, the following criteria are desirable:

  • Proven ability to apply the expertise in state-of-the-art deep learning ranging from theoretical to applied aspects, and strong skills in data analysis and statistical modeling in diverse real-world applications, ideally related to healthcare
  • Experience in managing research teams, ideally interdisciplinary teams
  • Leadership experience and management skills in social, organizational and economic terms
  • Successful acquisition of third-party funding as a Principal Investigator
  • Experience in (co-)supervising students and doctoral candidates
  • Anchoring in the relevant scientific community (proven by memberships, (co-) authorship, activities in editorial boards, conference organization etc.)
  • Excellent communication skills including a track record of public outreach activities
  • Ability to bridge the gap between technical AI concepts and healthcare applications
  • Interdisciplinary collaboration skills
  • Knowledge in or experience with ethical considerations, data privacy, and security regulations
  • The ability to translate research findings into practical healthcare applications

 

The University for Continuing Education Krems recognizes the significant innovation potential arising from the diversity of its employees and is committed to diversity as a guiding principle in accordance with its Code of Conduct and leadership principles.

At the same time, the University aims to increase the proportion of female professors and explicitly invites qualified women to apply. In cases of equal qualifications, preference will be given to female candidates. To promote equal opportunities for all applicants, scientific achievements will be assessed with consideration of biographical factors, such as part-time employment and caregiving responsibilities, as indicated in the application documents. 

Individuals with disabilities who fulfil the necessary qualifications are strongly encouraged to apply for this position.

The professorship will be initially appointed for a fixed term of 5 years in accordance with the appointment procedure outlined in § 98 UG (Austrian University Act). The position includes the option for conversion to permanent employment.

 

The minimum remuneration for this professorship will be EUR 6,713.30 gross per month (14x), on a full-time basis (according to the collective agreement of the universities §49 VwGr. A1). A willingness to negotiate higher salary exists for candidates with appropriate qualifications and professional experience.

 

Required documents to demonstrate the application criteria (in English):

  • Application abstract
  • Curriculum Vitae (CV) - Including academic background, professional experience, and relevant achievements
  • Cover letter - Addressing your interest in the position and alignment with the role’s requirements (max. 2 pages)
  • Concept paper – Outlining your vision for shaping and developing the professorship in terms of concrete research directions (max. 3 pages).
  • List of projects – Including project titles, funding sources, duration, and your specific role/contribution
  • Publications – full list of publications and discussion of the relevance of 3 selected papers in the context of this professorship (in total max. 1 page)
  • List of teaching activities and associated evaluations

 

We look forward to receiving your convincing application by 9th March 2026 at the latest to the Rector's Office of the University for Continuing Education Krems, Dr.-Karl-Dorrek-Straße 30, 3500 Krems, by post or by e-mail to berufungsmanagement@donau-uni.ac.at. If you have any questions, please contact Georg Kaiserschatt, MA (e-mail: berufungsmanagement@donau-uni.ac.at, telephone number: +43 2732 893 2204).

The University for Continuing Education Krems processes your personal data and voluntarily provided sensitive personal data (e.g., health data) within the framework of pre-contractual measures according to Art. 6/1/b GDPR, Art. 9/2/a GDPR, and, if applicable, Art. 49/1/b GDPR for the purpose of handling your application. For more information, please visit: Data Protection - University for Continuing Education Krems (donau-uni.ac.at). By submitting your application, you have acknowledged/accepted the privacy policy.

Supplementary Data Protection Notice:

Based on our legal obligation pursuant to § 98 of the Universities Act (UG), the personal data you provide as part of your application will also be disclosed to external reviewers who are bound by confidentiality, for the purpose of assessing your suitability. These reviewers will retain your data for a maximum of 12 months after their assessment has been submitted to the University for Continuing Education Krems.