Project staff member (PhD Position)

Do you want to participate in Austria's largest joint project on the fundamentals of Artificial Intelligence and contribute to WU Vienna’s vision of boosting AI? Do you want to understand how things are connected and make a fundamental impact? We are seeking highly motivated and talented individuals to join the Institute for Retailing and Data Science (Prof. Nils Wlömert) and the Institute for Statistics and Mathematics (Prof. Kurt Hornik) at one of Europe’s largest and most modern business and economics universities on a campus where quality of work is also quality of life. We are looking for support at the

Institute for Retailing & Data Science and the Institute for Statistics and Mathematics
Part-time, 30 hours/week
Starting June 01, 2025, and ending after 4 years   The successful candidate will conduct cutting-edge research on combining symbolic and sub-symbolic AI in collaboration with our partners at Johannes Kepler University Linz, AAU Klagenfurt, ISTA, TU Graz, and TU Vienna.   The vision of Bilateral AI is to educate a new generation of top-quality AI scientists with a holistic view of symbolic and sub-symbolic AI methods. Training and mentoring young researchers is a central activity combining groundbreaking research work with an education program. The training will be distributed over the six participating institutions.   We are currently inviting applications for a Project Staff Member position (PhD position). The successful candidate will work under the main supervision of Prof. Nils Wlömert (Institute for Retailing and Data Science) and Prof. Kurt Hornik (Institute for Statistics and Mathematics). The Institute for Retailing and Data Science applies AI and data-driven techniques to solve real-world business problems, particularly in retailing and consumer behavior. The Institute for Statistics and Mathematics focuses on advancing methods in statistics, data science, and AI, particularly in areas that emphasize rigorous, quantitative approaches. Together, these institutes foster a collaborative and interdisciplinary environment with access to strong research infrastructure and unique data, enabling innovative research at the intersection of theory and application in Artificial Intelligence. Moreover, the PhD is expected to collaborate on a broader level under the co-supervision of another key researcher from the BILAI network (https://www.bilateral-ai.net/consortium/).

What to expect

Research area:
The research for this position focuses on integrating symbolic and sub-symbolic AI methods to enhance interpretability and decision-making in AI systems. We primarily aim to contribute to research modules 5 (Causality) and 6 (Explainability) (https://www.bilateral-ai.net/research/research-modules). Potential topics include:  (i)            Combining dense vector representations with knowledge graphs for applications such as recommender systems, retail management, and fraud detection, enhancing transparency through structured, symbolic relationships between entities. (ii)           Applying causal inference with contextual embeddings to assess the impact of marketing actions, providing rule-based, interpretable insights into customer behavior and strategy effectiveness. (iii)         Creating explainable AI methods to make AI-driven decisions, such as those of recommender systems and targeting algorithms, more transparent and understandable for consumers. (iv)         Developing novel methods for causal inference with text-based treatments,
leveraging natural language processing and causal representation learning
techniques. Applications will focus on impact evaluation in recommender systems
and retail management, providing insights into how textual content influences
consumer behavior.   Candidates will be trained within the Bilateral AI Doctoral School (https://www.bilateral-ai.net). Joint seminars, scientific workshops, and compulsory courses outside the PhD students’ research fields will also be designed to encourage interdisciplinarity. Apart from that, students will be involved in grant applications, conference organization, Bachelor and Master student supervisions, and teaching. Each student will be supervised by two experienced and internationally renowned professors with different research fields (symbolic / sub-symbolic AI). The training will also provide a career development program, advice and support for students with innovative business ideas, and workshops for presentation and soft skills. We offer a stimulating environment that fosters both academic excellence and professional development, with ample resources and support to pursue innovative research ideas.

What you have to offer

We invite applications from candidates with a strong background in computer science, information systems, business informatics, economics, statistics, management, or related fields with a quantitative focus. The ideal candidate should have expertise in areas such as:

• Machine learning and data science
• Embedding techniques and neural networks
• Quantitative marketing, econometrics, or applied statistics
• Causal inference and explainable AI
• Recommender systems or other relevant areas of marketing analytics
• Knowledge representation and reasoning
• Graph theory, knowledge graphs, or decision support systems
• Multimodal content generation

  Applicants are expected to have strong programming skills, particularly in Python, R, SQL, Java, or C++, and proficiency with semi-structured data formats (e.g., JSON) and domain-specific query languages (e.g., graph query language).   Position Requirements: Candidates must hold a master’s degree that qualifies them to enroll in a PhD program, in one of the relevant subjects (see above). They should have solid practical and theoretical foundations in at least one of these areas. Strong academic performance, programming expertise, and proficiency in English are required. PhD students will be actively involved in joint seminars, workshops, teaching, and interdisciplinary projects across the participating institutions.   Do you want to join the Institute for Statistics and Mathematics and the Institute for Retailing and Data Science, as well as become part of the BILAI network? Then please submit your application. The following documents must be submitted (in English) by the call deadline: 1.    Letter of motivation (detailing previous research achievements, research goals, career plans); 2.    A complete CV, including a list of previous scientific expertise, awards, grants, stays abroad, attended lectures, attended summer schools, attended workshops, skills, and publications (if applicable); 3.    Abstract in English of the applicant’s MSc thesis, BSc thesis, or of a research project; 4.    A complete list of completed studies and transcripts of all grades; 5.    Two academic recommendation letters; 6.    Proof of proficiency in English (usually TOEFL/IELTS/CAE).   By submitting your application, you agree with your application being shared also with members of the BILAI admission committee from other partner universities in the BILAI network.   Join us in shaping the future of AI! We are excited to receive your application and welcome you to a vibrant, collaborative research community dedicated to advancing AI knowledge. We are looking forward to hearing from you! If you have any questions regarding the position or application documents prior to application, don’t hesitate to contact me for further information nils.wloemert@wu.ac.at with the subject: "[BILAI position]"

What we offer you

• Inspiring campus life with over 2,400 employees in research, teaching, and administration and approximately 21,500 students
• A modern campus with spectacular architecture in the heart of Vienna
• Excellent accessibility by public transportation
• Meaningful work in an open-minded, inclusive, and family-friendly environment
• Flexible working hours
• A wide range of benefits, from an in-house medical officer to athletic activities and a meal allowance to a variety of employee discounts

Curious? Visit our website and find out more at www.wu.ac.at/benefits   BILAI network: https://www.bilateral-ai.net/consortium/ Research modules: https://www.bilateral-ai.net/research/research-modules
The minimum monthly gross salary amounts to €2,786.10 (14 times per year). This salary may be adjusted based on job-related prior work experience. In addition, we offer a wide range of attractive social benefits.

Do you want to join the WU team?
Then please submit your application by April 02, 2025 (ID 2361).
We are looking forward to hearing from you!