Job opportunity Project staff member (pre-doc) at Wirtschaftsuniversität Wien Jobportal

Do you want to dive into state-of-the-art research on large language modeling and information retrieval

We are seeking two highly motivated prospective PhD students to join the newly established Vienna Research Group funded by WWTF and led by Dr. Svitlana Vakulenko. The objective of the group is to develop novel approaches to modeling knowledge specifically designed for use by an LLM. The group is positioned within the Institute for Data Process and Knowledge Management which boasts world-class excellence in reasoning data management and knowledge representation research. We offer an environment where you can accelerate your learning outcomes receive guidance and support to realize your full potential.

The ability of Large Language Models (LLMs) to generate contextually relevant natural language responses is truly impressive and a growing number of people are using them on a regular basis to address their information needs. However since LLMs are parametric models unlike databases they were not designed to reliably store data. While they are trained on massive amounts of textual data from the Web and are likely to pick up factual knowledge from it their responses are while usually fluent and grammatically correct often not factually correct which makes them to appear plausible and effectively deceive their users. Alternative RAG approaches that condition LLM generation on a set of retrieved search results also fail in many cases when information needs are more complex and search results are not optimal.

• Exciting research projects: You will be investigating and understanding the limitation of the current LLM-based approaches in the context of information retrieval applications as well as designing and evaluating novel LLM-based approaches for storing and retrieving large volumes of textual data.
• Support Activities: You will be encouraged (but not required) to get involved in preparing new project proposals workshop/conference organization Bachelor and Master student supervision as well as teaching activities.
• Teamwork: You will be collaborating with legal researchers and practitioners by testing the research prototypes within a real-world setting.
• Learning from top researchers: The program will provide career development guidelines advice and support for students with innovative business ideas and workshops for developing presentation and other soft skills.

• Academic degree: You have completed a masters degree that qualifies you for enrolling in a PhD program at WU in one of the following subject areas:
  • Computer Science
  • Mathematics
  • Information Systems
  • or a related field of study
• Language skills: You are fluent and able to express yourself very well in both spoken and written English
• Data skills: You have knowledge of programming languages such as Python
• Additional skills: Experience with software/research projects leveraging LLMs or other machine learning models
• Motivation: Strong motivation to conduct research in the field of knowledge representation and information retrieval an interest in diving into the cutting-edge research and experimenting with large language models

If you feel the profile fits you and you are interested in the job we look forward to receiving your application.

Applications should include the following information:

• a CV listing all education and work experience awards/grants stays abroad link to your GitHub account workshops hackathons publications (if applicable);
• a letter of motivation;
• Master thesis (or pre-final draft: if your thesis is not yet finished please submit a statement by the thesis main supervisor confirming feasibility of finishing your degree by 1st February 2026);
• two recommendation letters.

WU is dedicated to the principle of equal opportunities and is strongly committed to diversity and inclusion. Since WU seeks to increase the number of its female employees in academic and management positions qualified women are strongly encouraged to apply. Women with equal qualifications are given priority. Qualified candidates with disabilities are also encouraged to apply.

Do you have any questions or do you require additional information Please contact: