For Students

Open Thesis Topics

Students who are eager to develop their skills by doing a research-oriented thesis in our group should mail their interests to webis@listserv.uni-weimar.de. Suitable topic candidates are shown in the following list. Your own suggestions for topics are also welcome, for which you can draw inspiration from our recent publications.

  • AQLQA: Mining Direct Answers from Dozens of Search Engines over 25 Years
  • Large-scale Rank Fusion Evaluation

Open Student Assistant Topics

Students who want to improve their skills and work with us can apply for a position as a student assistant at webis@listserv.uni-weimar.de. We are currently looking for assistants to work on the following topics:

  • We currently have no open topics. You can always let us know if you're interested.

Ongoing Theses

  • Halle
    • Building Medical Knowledge Graphs for Knowledge Injection in LLMs (supervised by Alexander Bondarenko and Jan Heinrich Merker)
  • Jena
    • Evaluating Pre-Training Techniques for Single-Vector Encoder Models (supervised by Ferdinand Schlatt)
    • Testing the Limits of Multi-Vector Bi-Encoder Models (supervised by Ferdinand Schlatt)
    • Dense Boolean Retrieval for Systematic Reviews (supervised by Ferdinand Schlatt)
    • Improving Learned Lexical Retrieval Models by Removing Lexical Dependencies (supervised by Ferdinand Schlatt)
    • Reducing the Size of Dense Retrieval Indexes by Removing Unimportant Terms (supervised by Ferdinand Schlatt)
    • Argument Mining in the AQL (supervised by Ines Zelch)
    • Construction of Fine-Grained Retrieval Pipelines With PyTerrier (supervised by Maik Fröbe and Jan Heinrich Merker)
    • Agent-based Retrieval-Augmented Biomedical Question Answering (supervised by Jan Heinrich Merker and Wilhelm Pertsch)
  • Leipzig
    • Extracting negated causal statements (supervised by Tim Hagen)
    • Facets of complexity in scholarly political language (supervised by Magdalena Wolska)
    • Simplifying the language of political argumentation (supervised by Magdalena Wolska)
    • Lightweight Passage Re-ranking Using Embeddings from Pre-trained Language Models (supervised by Ferdinand Schlatt and Harry Scells)
    • Logical Features of Neural Networks (supervised by Maximilian Heinrich)
    • Active Learning for Text Classification (supervised by Christian Kahmann and Christopher Schröder)
    • Incorporating Knowledge Graph Embeddings in Large Language Models (supervised by Ferdinand Schlatt)
    • Normdaten-Disambiguierung und Reconciliation auf Korpusdaten (supervised by Erik Körner and Felix Helfer)
    • Statistical Bootstrap Tests with Redundant Data (supervised by Maik Fröbe)
    • Mining Trigger Warnings from the Web and Social Media (supervised by Matti Wiegmann)
  • Weimar
    • Employing Personal Knowledge Graphs in User Simulation in Conversational Search (supervised by Nailia Mirzakhmedova)
    • Building an Image Generator for Arguments (supervised by Maximilian Heinrich)
    • Information Extraction from Scientific PDFs (supervised by Tim Gollub)
    • Adding Contextual Awareness to LLM-based Story Generation (supervised by Tim Gollub)
    • Prompt Framing Effects on Large Language Model Subjectivity Judgements (supervised by Nailia Mirzakhmedova)
    • How Humans Detect Cloned Voices (supervised by Johannes Kiesel and Marcel Gohsen)
    • Story Orchestration for Multi-Agent Collaboration for Automatic Story Generation (supervised by Marcel Gohsen)
    • Do Large Language Models Extrapolate Personas of Dialog Participants from Context? (supervised by Marcel Gohsen)
    • Developing a Teaching Assistant for Course Materials with Retrieval-Augmented Generation (supervised by Marcel Gohsen)
    • Crafting Multi-Modal Learning Experiences based on Course Materials (supervised by Marcel Gohsen)
    • Efficient and Effective Neural Translation Language Model for Search (supervised by Harry Scells)
    • Rating the Degree of Search Engine Optimization of Websites (supervised by Janek Bevendorff)
    • Personalizing Question Answering (supervised by Matti Wiegmann and Marcel Gohsen)
    • Web Search Archeology in the Archive Query Log (supervised by Jan Heinrich Merker, Simon Reich, and Matti Wiegmann)
    • Re-ranking with Health-related Retrieval Axioms (supervised by Jan Heinrich Merker and Maximilian Heinrich)

Resources for Students

Vacancies

Dear prospective PhD student, unsolicited applications to the Webis group (webis.de) are welcome. However, we cannot promise that open positions are available at the time of your application.

The Webis Group is a tightly cooperating research network, formed by computer science chairs at the universities of Groningen, Hannover, Jena, Kassel, Leipzig, and Weimar. Our mission is to tackle challenges of the information society by conducting basic and applied research with the goal of prototyping and evaluating future information systems. We are an experienced research group where team spirit and active collaboration has top priority. We are looking for open-minded graduates and PhDs who want to develop both as a researcher and as a person. The working language of our group is English; fluency in German is not required.

Interested students should have finished either a master or a PhD in computer science, mathematics, or a related field with excellent or very good grades. A solid background in mathematics and statistics is expected—as well as very good programming skills.

--> Benno Stein
Bauhaus-Universität Weimar
On behalf of the Webis group

Email: webis@listserv.uni-weimar.de
Web: webis.de