Faculty of Business, Economics and Statistics
… is one of the major faculties of the University of Vienna, bringing together eight departments and several centers across business, economics, statistics, economic sociology and related fields.
… is supported by more than 260 staff members dedicated to high-quality research, teaching and administration.
… educates over 7,500 students across Bachelor’s, Master’s and PhD programmes.
… trains doctoral candidates in structured PhD programmes and fostering innovative and internationally oriented research through the Oskar-Morgenstern Doctoral School
Supervisor / Research Interests and Supervision Areas
Jan Fabian Ehmke
Research Focus
The Business Analytics Group is part of the Department of Business Decisions and Analytics. We investigate combined methods of descriptive and predictive analytics to create data-driven decision support systems. In particular, we investigate and extend methods from applied operations research and business analytics. We are particularly interested in analyzing large amounts of real data (e.g., from transactional or sensor data). We include these within dynamic and stochastic optimization approaches to provide decision support for applications in transportation, mobility, and logistics. We offer undergraduate and graduate classes dealing with business analytics, operations research, and methods of computational transportation.
Research environment
The Research Group Business Analytics is part of the Department of Business Decisions and Analytics. Our group currently has four PhD students and four postdocs, who are embedded in the department. We will provide access to literature and computational power for experiments. We will also integrate the postdocs in co-supervision of our PhD students and provide resources for conference travelling.
Expectations towards postdoctoral fellows in this programme
The expected postdoc should be interested in quantitative research in mobility, logistics, and transportation. They should be willing to co-supervise PhD students and cooperate with members of the group in general. They should be willing to work on high-quality publications to be submitted to renowned international journals. They are expected to build their own research topic that they are known for.
Possible research themes or topics for postdoctoral projects
We are open to state-of-the-art quantitative research in the area of transportation analytics. Examples of our current research topics can be found here: https://busan.univie.ac.at/research/
Weblink for further information:
https://busan.univie.ac.at/
Email: jan.ehmke(at)univie.ac.at
Dmitriy Knyazev
Research Focus
We are a group doing research in Market Design, Mechanism Design, Auctions, and Contests. Research questions may include the design of incentive-compatible mechanisms, strategic interaction under incomplete information, and applications of game-theoretic models to business, public policy, and platform settings. The position is suitable for candidates with strong analytical skills and interests in economic theory, operations research, or decision sciences. Depending on the candidate’s profile, research may also interface with optimization, algorithmic approaches, or empirical validation of theoretical predictions.
Research environment
The postdoctoral researcher will be embedded in the Department of Business Decisions and Analytics at the Faculty of Business, Economics and Statistics, University of Vienna. The department offers a highly international and interdisciplinary research environment, with expertise spanning decision sciences, operations research, economics, and analytics. The postdoc will collaborate closely with faculty working on game theory, market design, and optimization, and will have opportunities to interact with researchers across the faculty and the wider Vienna academic ecosystem. The University of Vienna provides excellent research infrastructure, strong support for international collaboration, and access to doctoral students, seminars, and visiting scholars.
Expectations towards postdoctoral fellows in this programme
Postdoctoral fellows are expected to pursue independent, high-quality research in their area of expertise and to contribute actively to the department’s research activities. This includes developing publishable research projects, collaborating with faculty members, and presenting work at internal seminars and international conferences. Fellows are encouraged to submit their research to leading journals in economics, business, and decision sciences, and to apply for external research funding where appropriate. Depending on departmental needs, postdoctoral fellows may contribute to limited teaching or supervision activities, particularly at the graduate level. Active participation in the academic life of the department and engagement with doctoral students are expected.
Possible research themes or topics for postdoctoral projects
We are completely open to any proposals that involve a substantial analytical approach!
Weblink for further information:
https://sites.google.com/site/dmitriyaknyazev/
Email: dmitriy.knyazev(at)univie.ac.at
Bernhard Kittel
Research Focus
Recently my work has focused on justice attitudes, group decision making and marginal groups in the labor market, using mostly experimental methods, population surveys and interviews. I have been involved as a principal investigator in a DFG research group on need-based justice in distributive decisions, an FP7 framework project on economic self-sufficiency as well as a project on the integration of refugees and I have directed the Austrian Corona Panel Project. Current work includes experimental studies of contestatory and collaborative arguing in deliberation, and I have been co-organizer of a citizens’ convention on the Austrian security strategy. Cooperative research applications on moralizing consumption in the context of climate change and on trust in contract development in the construction sector are currently under review. A book project focuses on need satisfaction as a fundamental justice principle of contemporaneous societies.
Research environment
The department of economic sociology is a very small department in the Faculty of Business, Economics and Statistics entrusted with familiarizing students of business administration and economics with the social and societal context of economic decisions. It offers possibilities of cooperation with, inter alia, the departments of sociology, government, political science, communication sciences, psychology and cultural and social anthropology, but also reaches out to the University of Business and Economics, the Central European University and the Technical University of Vienna. It also has established connections with the research departments of the Chamber of Labor. The department is well connected to various international scholarly networks and integrated in the German academy of sociology, which fosters theory-driven empirical work in the tradition of analytical sociology. The Faculty has a center for experimental economics and currently builds a data center.
Expectations towards postdoctoral fellows in this programme
A postdoc researcher is expected to build an own, independent research program that nevertheless is capable of connecting to one or more research areas in the department, which are, broadly speaking, (1) structures, institutions and dynamics of the labor market and the welfare state in Austria and in comparative perspective, (2) justice attitudes and behavior, (3) political and societal responses to climate change, and (4) trust in markets. The postdoc researcher will also teach two courses per semester in the field of economic sociology in the curriculum of (international) business administration. The postdoc researcher is expected to publish in highly reputed scientific journals and to acquire external funding.
Possible research themes or topics for postdoctoral projects
The search will be thematically open, but some connection to ongoing research in the department, not necessarily only my own work, would be appreciated. An experimental approach would be very welcome, but other analytical approaches such as survey research or computational social science would also be considered an asset.
Weblink for further information:
https://soc.univie.ac.at/en/
Email: bernhard.kittel(at)univie.ac.at
Christoph Fuchs
Research Focus
My research lies at the intersection of marketing, human behavior, and technology. I study how technological and institutional changes shape individual perceptions, judgments, and behavior, and how these psychological processes translate into broader market and societal outcomes. Methodologically, my work combines experiments, surveys, and large-scale secondary data.
My current research agenda focuses on four main areas. First, I examine how artificial intelligence (AI) affects consumers, workers, and society. By combining experimental methods with cross-country secondary data, I study how AI adoption influences trust, perceived fairness, political attitudes, and acceptance of market and policy outcomes. Second, I investigate how consumers perceive and respond to new technologies, identifying psychological factors that drive adoption, resistance, or abandonment beyond functional performance. Third, I study how policymakers can design laws, regulations, and institutional “S-frames” that reduce psychological reactance and increase public acceptance. Finally, I explore the psychological foundations of creativity, examining how agency, constraints, and involvement shape creative performance and innovation.
Research environment
The research environment is collaborative, supportive, and strongly interdisciplinary. Professors, PhD students, and postdoctoral researchers work closely together in a setting that values open intellectual exchange, constructive feedback, and joint problem solving. Regular research meetings and seminars foster continuous learning and high academic standards. The group actively collaborates with faculty in psychology and economics, allowing researchers to draw on complementary theoretical perspectives and methodological approaches. Members benefit from access to laboratory infrastructure and data resources that support both experimental and large-scale data-driven research. Methodological rigor, transparency, and open science practices are emphasized across projects. The group aims to publish its work in top-level field journals as well as leading general-interest journals. Networks with other institutions in Vienna, including the Vienna University of Economics and Business (WU Vienna), further support academic development and cross-institutional research initiatives.
Expectations towards postdoctoral fellows in this programme
We expect postdoctoral researchers to be intellectually curious, highly motivated scholars who aim to develop an independent research profile within a collaborative and supportive environment. Postdocs are encouraged to pursue their own research ideas and also collaborate with professors. Solid training in statistical methods and experimentation is required, along with adherence to open science practices; further methodological development is actively supported. We value analytical rigor, initiative, and openness to feedback. Postdocs are expected to participate in research meetings and seminars. We expect a background in business research (e.g., marketing), psychology, or economics, with an interest in interdisciplinary research. We expect postdocs to produce papers targeted at high-quality publications and participate in grant applications.
Possible research themes or topics for postdoctoral projects
Specific topics would need to be discussed in person.
Weblink for further information:
https://marketing.univie.ac.at/team/wissenschaftliche-mitarbeiterinnen/christoph-fuchs/
Email: christoph.fuchs(at)univie.ac.at
Christa Cuchiero
Research Focus
The Research Group Quantitative Risk Management and Mathematical Finance works at the interface of mathematical finance, risk management, stochastics, statistics as well as machine learning and AI .
Many of the mathematical and stochastic problems that we are dealing with arise from questions in finance and economics with a focus on risk assessment. To exploit upside risks on the one hand and reduce downside risks on the other hand, mathematical models which are as close as possible to reality should be chosen. Nowadays this has become a feasible task as AI and machine learning approaches have opened the door to more data-driven and thus more robust models, enabling realistic data driven risk inference.
Concrete topics that we are working on include universal structures in mathematical finance, affine and polynomial processes,
theory and applications of machine learning, especially signature methods and deep neural networks.in dynamic contexts.
Research environment
Our research group on Quantitative Risk Management and Mathematical Finance is part of the Department of Statistics and Operations Research. A part from the more senior faculty members our group currently has two PhD students and two postdocs, and regularly hosts guest researchers.
We will provide access to literature and computational power for numerical implementations. We will also integrate the postdocs in our research seminars and provide resources for conference traveling.
Expectations towards postdoctoral fellows in this programme
The postdoc candidates should be interested in the topics of our research group and should have a finished their Phd studies at the interface of mathematics, stochastics, finance and machine learning. They should be willing to co-supervise PhD students and cooperate with members of the group in general. They should be willing to work on high-quality publications to be submitted to renowned international journals and build their own research portfolio.
Possible research themes or topics for postdoctoral projects
For research themes we refer to recent publications and talks of the members of the research group.
Weblink for further information:
https://quarimafi.univie.ac.at/
Email: christa.cuchiero(at)univie.ac.at
Tatyana Krivobokova
Research Focus
Our group works on high-dimensional regression and dimension reduction, simultaneous inference, modelling of complex experimental data, change-point analysis and differential privacy for dependent data. We have collaborative projects in Biology (microbiom study), Biophysics (protein dynamics), Chemistry (high-throughput experimental data), Astrophysics (simulation of galaxies) and several more.
Research environment
The Research Group Statistical Methods is part of the Department of Statistics and Operations Research. Our group currently has two PhD students and two postdocs, who are embedded in the department. We will provide access to literature and computational power. We will also integrate the postdocs in co-supervision of our PhD and Masters students and provide resources for conference travelling.
Expectations towards postdoctoral fellows in this programme
The expected postdoc should have a solid background in mathematical statistics and ideally have experience or interest to work on collaborative projects with natural sciences. They are expected to publish in high-ranked journals of the field and develop their unique profile.
Weblink for further information:
https://sme.univie.ac.at
Email: tatyana.krivobokova(at)univie.ac.at