Professor of Data Science Methods in Information Systems; tenured, level W2

The Department of Information Systems in the School of Business and Economics at the University of Münster, Germany, is currently inviting applications for the position of

to commence on 1 April 2027 or as soon as possible thereafter.

We envision for this professorship to further strengthen the Department of Information Systems in terms of its global reputation for research and teaching, as well as its contribution to and significance for society and the economy. Therefore, we are looking for an outstanding individual and engaged researcher with a specialisation in data science methodology and with experience in transferring theory and methods into socio-technical applications.

The successful candidate will integrate well into the department and its ecosystem and will contribute to the further development of the dynamic Information Systems team in Münster. Candidates are expected to have established an international reputation in their field.

The Department of Information Systems at the University of Münster is one of the largest and most prestigious Information Systems departments in Germany with an exciting and friendly international research environment that spans several research fields ranging from computer science and mathematics to business and economics. As the headquarters of the European Research Center for Information Systems (ERCIS), the department is connected to over 30 partner institutions in Europe and beyond.
The department offers a wide-ranging and comprehensive education in Information Systems by providing a profound foundation in computer science, mathematics, and business. In particular, the curriculum integrates methods, processes and data, as well as innovation-oriented perspectives on digital transformation and technology in different application areas, into a broad and interdisciplinary programme.
Members of the department regularly publish in leading journals in the field, (e.g., MISQ, ISR, and Management Science) as well as in premier outlets of disciplines related to natural science, machine learning or computational intelligence (e.g., Nature, ICML, TEVC, GECCO). The department promotes an active dialogue with other research disciplines, thought leaders from industry, and society, which is reflected in interdisciplinary third-party funding, extensive collaborations with practice as well as publications in outlets such as CACM, the MIT Sloan Management Review, and Harvard Business Review.

Please visit our website ( ), for more information.

We are looking for an outstanding individual who will engage with our department and its lively ecosystem and work toward making important and impactful contributions to academia, business, and society. In that, we are open to welcoming diverse profiles regarding methodological orientation, field of interest, and seniority level. Applicants are invited to describe how they envision integrating with and advancing the department.
Given the profile of the department, we are particularly seeking candidates who have contributed to data science methodology through the development of methods grounded in sound theoretical foundations. Therefore, applicants must have in-depth expertise in computer science, mathematics, or statistical methods and a strong interest or application focus in business, society and/or public administration. Applicants should also demonstrate a clear research focus on the aforementioned areas, as well as the ability and interest to establish meaningful links with the existing expertise in the department, including machine learning, operations research, operations management, social media analytics, business process management, digital innovation, and public administration.

At the same time, the applicant is expected to complement the department’s existing research and teaching portfolio.
The successful candidate will contribute to teaching activities in our Information Systems BSc, MSc, and PhD programs. In particular, the professorship is expected to contribute to the foundational education in statistics in the bachelor’s degree programs as well as to the data science major in our master’s program. Further courses can be offered based on the candidate’s specific research profile. The successful candidate is expected to contribute to the ongoing development of our degree programmes and to pioneer new educational approaches.
We expect the successful candidate to publish in established information systems, computer science, or statistics outlets. Active contributions to the international information systems, computer science, or statistics communities are highly encouraged. We also recognise publications in established outlets from related interdisciplinary research and application fields. Beyond academic conference or scholarly journal publications, we value an active dialogue with industry and society, and recognise publications in…