The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer! Your responsibilities Multi-criteria decision support through item ranking is an understudied research direction. Current solutions exhibit considerable limitations, primarily due to their inability to meet the multi-faceted nature of human decision-making. Choosing between thousands of relevant items is a common task, where people are left alone with the need to express and balance multiple desirable preferences at once. Item rankings are a popular and universal approach to structuring unorganized item collections by multiple criteria at the same time. In interactive solutions, people can express multiple preferences, used by algorithms to compute human-centered and personal rankings. Visual Analytics (VA) is a field of research that supports complex human decision-making tasks by bringing together human intellectuality with the computational power of algorithms in effective human-in-the-loop approaches. In this project, we will demonstrate how cutting-edge VA principles can be transferred to item ranking, to overcome remaining challenges, demonstrate effective and efficient interactive ranking creation solutions, and empower broad audiences. Limitations of ranking systems mainly include their incompatibility for the elicitation of item- and attribute-based preferences, insufficient handling of user-introduced uncertainty, inadequate guidance for engaging with large item sets, lacking interaction histories, inefficient human-centric feedback loops, or a lack of explanations and transparency of ranking algorithms, thus creating a disconnect between the technology and nuanced user needs. Finally, interactive ranking creation does not yet make use of interfaces for eliciting implicit user preferences, e.g., in textual form using large language models. We offer: Hands-on supervision/mentorship for further career development Support in conducting excellent research and in publishing results in top international journals and conferences Creative working atmosphere in a motivated, cooperative, and technically very well-equipped environment Possibility to work with several Ph.D. students in the lab in topics around IVDA, particularly on personalized VA for item ranking Excellent professional and personal development possibilities and hence, excellent basis for a future career in interactive visual data analysis in an industrial context Specific benefits like flexible working hours, young scientist promotion opportunities, parental leave benefits, nursery services, and care for dependents and much more Very good salary, according to local university regulations and standards in Switzerland Your profile Ph.D. degree, e.g., in Informatics, ML/AI, Data Science, or HCI. Strong publication record and ability to conduct scientific work and dissemination activities in the realm of visual analytics. Excellent communication and collaboration skills, and ability to work in interdisciplinary teams. Ability to independently teach university-level courses and supervise students. Extensive expertise in some of these areas: visual analytics, data science, information retrieval, data mining, machine/deep learning, AI, natural language processing, explainable AI, human-centered AI, responsible AI, algorithmic fairness, biases, transparency, HCI, applied research methods, or types of empirical research. Profound skills in programming in Python and supervise programming projects.
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