We are seeking candidates in the field of Mathematics for Responsible Artificial Intelligence (RAI). RAI is an interdisciplinary effort to develop AI systems that are fair, accountable, transparent, and socially considerate. The growing adoption of advanced AI technologies has highlighted the importance of addressing ethical, legal, and societal concerns. Despite the need for responsible AI, it is estimated that most technical AI research focuses on increasing the AI capabilities, with only a very small fraction dedicated to AI safety. The research of the new assistant professor tenure track (APTT) will focus on the mathematics of responsible and trustworthy AI. The professorship will be embedded in the Department of Mathematical Modeling and Machine Learning (DM3L) and concentrates on devising mathematical foundations and principles to enhance the accountability, transparency and explainability, fairness and non-discrimination, of AI systems. More specifically (but not exclusively), we seek candidates with competences around the following pillars (i) accountability: developing systems where algorithmic decisions can be traced and audited; ensuring that outcomes are verifiable against standards and rules; (ii) transparency and explainability: creating interpretable models where the decision process is clear; (iii) fairness and non-discrimination: designing algorithms to make unbiased decisions by mathematically defining fairness (e.g., demographic parity, equality of opportunity), and integrating these definitions into model optimization and evaluation processes (hereby acknowledging the complications of algorithmic notions of fairness); (iv) AI alignment : developing AI models that operate in a way that is consistent with human goals, intentions, and values. The professorship will focus on a deeper mathematical understanding of accuracy, explainability, mitigation of bias, reliability, and robustness of RAI.

Assistant Professorship tenure track for Mathematics for Responsible AI

Spring 2027

The successful candidate must be an outstanding researcher in their field of computer science, machine learning, AI, applied mathematics or statistics with a proven track record in terms of research output and ideally acquisition of third-party funding, as well as teaching and mentoring. The future assistant professor tenure track is expected to strengthen the scientific impact and societal role of the Department of Mathematical Modeling and Machine Learning (DM3L). The future assistant professor tenure track will supervise PhD students and contribute to teaching and its further development at both Bachelor and Master level. The successful candidate is expected to teach 2–4 hours per week during the semester in English or German for the new BSc and MSc programs "Applied Mathematics and Machine Learning" in the domain of mathematical concepts for RAI. The modules will be "cross-listed" for the corresponding study programs at the Department of Informatics at the University of Zurich (UZH).

What we offer

Our employees benefit from a wide range of attractive offers.

Location

Department of Mathematical Modeling and Machine Learning (DM3L)

Information on your application

The professorship is part of the new Responsible AI Cluster at UZH, which is part of the UZH.ai initiative. This RAI Cluster will bring together interest and vast expertise across multiple faculties at UZH, enable new joint collaborations nationally through the Swiss AI Initiative, and internationally through collaboration with non-profit institutes and university RAI centers.

UZH sees researchers as modern leaders who conduct excellent research - taking into account the Open Science principles - through their own research projects as well as the promotion of excellent junior researchers, and who help to shape a future-oriented University with innovative research-based teaching. Situated in the open-minded and family-friendly city of Zurich, which combines the vibrant cultural scene in a modern European city with the convenient accessibility to its beautiful natural surroundings, UZH is well integrated in the city's community and research environment.

UZH provides generous research support, including dedicated funds for personnel, running expenses, and competitive start-up packages. Additionally, the successful applicant is expected to acquire external research funding. Zurich's scientific environment encompasses a rich spectrum of diverse activities.

The employment conditions for this position follow UZH's legal regulations and include part-time options. UZH is an equal-opportunities employer, and the Faculty of Science, in particular, strives to increase the percentage of women and underrepresented groups in leading positions. Therefore, qualified female researchers are particularly encouraged to apply. Care-time interruptions are considered during the evaluation of applicants of all genders.

Applicants are kindly invited to submit their applications, which should include:

• a cover letter (max. 1 page)
• a Curriculum Vitae with date of submission, including teaching and supervisory track record; outreach activities; a list of acquired competitive funding, including role and amount awarded to the candidate
• a description of their research outputs relevant to this application and their importance for the field (at most five outputs, max. 1 page in total)
• a research plan describing their mid-term scientific strategy and expected impact (max. 2 pages)
• a teaching reflection on their educational values, tools and methods, and their potential contribution to the curriculum development at UZH (max. 1 page)
• a description of their track record and/or planned measures towards diversity, equality, inclusion, and sustainability (max. 0.5 page)
• a list of publications and other research outputs, including datasets, code, etc.
• a copy of their PhD certificate

Please note that page limitations do not include references.

The evaluation processes at UZH and the Faculty of Science follow the DORA recommendations for assessing research quality and impact. Applicants are thus asked to refrain from referring to non-personal measures such as impact factors.

Please upload your application to www.mnf.uzh.ch/responsibleAI by 28 April 2026. The interviews will take place on 17 and 18 June 2026.

Further information

Questions about the job

Prof. Dr. Jan D. Wegner
Professor

Working at UZH

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