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for-students.html
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---
layout: default
nav_active: for-students
title: Webis For Students
description: Collection of resources relevant to our students
---
<nav class="uk-container">
<ul class="uk-breadcrumb">
<li><a href="index.html">Webis.de</a></li>
<li class="uk-disabled"><a href="#">For Students</a></li>
</ul>
</nav>
<main class="uk-section uk-section-default">
<div class="uk-container">
<h1>For Students</h1>
<ul class="uk-list">
<li><span data-uk-icon="chevron-right"></span> <a href="for-students/completed-theses.html">Completed Theses</a></li>
</ul>
<ul class="uk-list">
<li><span data-uk-icon="chevron-down"></span> <a href="#open-thesis-topics">Open Thesis Topics</a></li>
<li><span data-uk-icon="chevron-down"></span> <a href="#open-student-assistant-topics">Open Student Assistant Topics</a></li>
<li><span data-uk-icon="chevron-down"></span> <a href="#ongoing-theses">Ongoing Theses</a></li>
<li><span data-uk-icon="chevron-down"></span> <a href="#resources">Resources for Students</a></li>
<li><span data-uk-icon="chevron-down"></span> <a href="#vacancies">Vacancies</a></li>
</ul>
</div>
<div class="uk-container uk-margin-medium">
<div id="search-control">
<input type="text" class="uk-input" id="filter-field" placeholder="Type here to filter…"/>
</div>
</div>
<div class="uk-container uk-margin-medium">
<h2><a id="open-thesis-topics"></a>Open Thesis Topics</h2>
<p>
Students who are eager to develop their skills by doing a research-oriented thesis in our group should mail their interests to <a href="mailto:[email protected]?subject=Application%20for%20a%20Thesis%20at%20Webis">[email protected]</a>. 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 <a href="publications.html">publications</a>.
</p>
<div class="webis-list uk-margin-remove-top">
<ul> <!-- sorted alphabetically by title -->
<!--<li>We currently have no open topics. You can always let us know if you're interested.</li> -->
<li data-mentor="marcel gohsen, matti wiegmann">Personalizing Question Answering</li>
<!--<li data-mentor="christopher schröder">Active Learning for Text Classification</li>-->
<!--<li data-mentor="martin potthast">Adversarial Learning of Writing Style Representations</li> [needs additional supervisor]-->
<!--<li data-mentor="martin potthast, norbert siegmund, benno stein">Argumentation in Software Engineering</li>-->
<!--<li data-mentor="janek bevendorff, magdalena wolska">Authorship Attribution based on Supra-segmental Features</li>-->
<!--<li data-mentor="roxanne el baff, khalid al-khatib">Automatic Generation of Persuasive Texts</li>-->
<!--<li data-mentor="maik fröbe">Automatic Updates of Relevance Labels for Web Search</li> -->
<!--<li data-mentor="sascha bondarenko">Axiomatic Argumentative Web Scale Document Re-ranking</li>-->
<!--<li data-mentor="maik fröbe">Building and Operating a Search Engine for Free With Github Pages as an Enabler for a Diverse Search Ecosystem</li>-->
<!--<li data-mentor="maik fröbe">Children as Searchers: Improving Web Search for Children</li>-->
<!--<li data-mentor="wei-fan chen, khalid al-khatib">Detecting Bias in Media</li>-->
<!--<li data-mentor="christian kahmann">Crawling and Extraction of insurance websites and subsequent multilabel classification of available insurance products</li> -->
<!--<li data-mentor="maik fröbe">Does Training Data from different Corpora benefit Learning-to-Rank?</li>-->
<!--<li data-mentor="matthias hagen, sascha bondarenko">Entity Linking for Comparative Questions</li>-->
<!--<li data-mentor="khalid al-khatib">Exploiting Argumentation Knowledge Graphs for Argument Generation</li> [at full load] -->
<!-- li data-mentor="christopher schröder">Extreme Multi-Label Classification of German Book Titles</li -->
<!--<li data-mentor="khalid al-khatib">Harvesting the Web for Building Evidence-based Knowledge Graphs</li>-->
<!--<li data-mentor="khalid al-khatib">Identifying Successful Debating Strategies in Social Media</li>-->
<!--<li data-mentor="benno stein, martin potthast">Information Theory and Authorship</li>-->
<!--<li data-mentor="maik fröbe, harry scells, christopher akiki">Measuring the Correlation of the Effectivenes of Large Language Models and Retrievability</li>-->
<!--<li data-mentor="maik fröbe">Multi-Task Learning with IR Axioms</li>-->
<!--<li data-mentor="nailia mirzakhmedova">Persuasive Argument Generation using Generative Adversarial Networks</li> -->
<!--<li data-mentor="martin potthast, benno stein, matthias hagen, janek bevendorff">Paraphrasing Operations for Heuristic Author Obfuscation</li>-->
<!--<li data-mentor="maik fröbe">Query Obfuscation for Dense Retrieval Models</li>-->
<!--<li data-mentor="marcel gohsen">Question Analytics of Conversational QA-Systems: A Gamified Study</li>-->
<!--<li data-mentor="matthias hagen, sebastian günther">Simulating Search Behavior</li>-->
<!--<li data-mentor="khalid al-khatib, shahbaz syed">Summarizing Online Discussions</li> [at full load] -->
<!--<li data-mentor="khalid al-khatib>Text Mining Methods for Intelligent Writing Assistance</li> [at full load] -->
<!--<li data-mentor="nailia mirzakhmedova">Unraveling Argumentation Strategies through XAI Techniques</li> -->
<li data-mentor="Jan Heinrich Merker">Re-ranking with Health-related Retrieval Axioms</li>
<li data-mentor="Jan Heinrich Merker">Agent-based Retrieval-Augmented Biomedical Question Answering</li>
<li data-mentor="Jan Heinrich Merker">AQLQA: Mining Direct Answers from Dozens of Search Engines over 25 Years</li>
<li data-mentor="Jan Heinrich Merker">Large-scale Rank Fusion Evaluation</li>
<li data-mentor="Matti Wiegmann, Jan Heinrich Merker">Web Search Archeology in the Archive Query Log</li>
</ul>
</div>
<h2><a id="open-student-assistant-topics"></a>Open Student Assistant Topics</h2>
<p>
Students who want to improve their skills and work with us can apply for a position as a student assistant at <a href="mailto:[email protected]?subject=Application%20for%20a%20Thesis%20at%20Webis">[email protected]</a>.
We are currently looking for assistants to work on the following topics:
</p>
<div class="webis-list uk-margin-remove-top">
<ul> <!-- sorted alphabetically by title -->
<li>We currently have no open topics. You can always let us know if you're interested.</li>
<!-- <li data-mentor="matti wiegmann">Analyzing and Tuning Chat Bots for Emotional Support Tasks</li> -->
</ul>
</div>
<div class="webis-list">
<h2><a id="ongoing-theses"></a>Ongoing Theses</h2>
<ul>
<li>Halle
<ul>
<!-- add new thesis here -->
<li>Building Medical Knowledge Graphs for Knowledge Injection in LLMs (supervised by Alexander Bondarenko and Jan Heinrich Merker)</li>
</ul>
</li>
<li>Jena
<ul>
<!-- add new thesis here -->
<li>Evaluating Pre-Training Techniques for Single-Vector Encoder Models (supervised by Ferdinand Schlatt)</li>
<li>Testing the Limits of Multi-Vector Bi-Encoder Models (supervised by Ferdinand Schlatt)</li>
<li>Analyzing the Effectiveness of Community Self-moderation on the Fediverse (supervised by Jan Heinrich Merker and Matti Wiegmann)</li>
<li>Large-scale Query Log Analyses (supervised by Jan Heinrich Merker)</li>
<li>Dense Boolean Retrieval for Systematic Reviews (supervised by Ferdinand Schlatt)</li>
<li>Improving Learned Lexical Retrieval Models by Removing Lexical Dependencies (supervised by Ferdinand Schlatt)</li>
<li>Reducing the Size of Dense Retrieval Indexes by Removing Unimportant Terms (supervised by Ferdinand Schlatt)</li>
<li>Estimating the Trustworthiness of Wikipedia Articles (supervised by Jan Heinrich Merker and Matthias Hagen)</li>
<li>Argument Mining in the AQL (supervised by Ines Zelch)</li>
<li>Construction of Fine-Grained Retrieval Pipelines With PyTerrier (supervised by Maik Fröbe and Jan Heinrich Merker)</li>
</ul>
</li>
<li>Leipzig
<ul>
<!-- add new thesis here -->
<li>Extracting negated causal statements (supervised by Tim Hagen)</li>
<li>Creating the Dataset for the Touché 25 Shared Task: Image Retrieval/Generation for Arguments (supervised by Maximilian Heinrich and Johannes Kiesel)</li>
<li>Facets of complexity in scholarly political language (supervised by Magdalena Wolska)</li>
<li>Simplifying the language of political argumentation (supervised by Magdalena Wolska)</li>
<li>Text2SQL. Exploring Relational Databases with Natural Language User Interfaces (supervised by Tim Gollub)</li>
<li>Psychological Features of Argumentation (supervised by Maximilian Heinrich)</li>
<li>Lightweight Passage Re-ranking Using Embeddings from Pre-trained Language Models (supervised by Ferdinand Schlatt and Harry Scells)</li>
<li>Logical Features of Neural Networks (supervised by Maximilian Heinrich)</li>
<li>Classification of Multimodal Social Media Posts (supervised by Tim Gollub)</li>
<li>Active Learning for Text Classification (supervised by Christian Kahmann and Christopher Schröder)</li>
<li>Incorporating Knowledge Graph Embeddings in Large Language Models (supervised by Ferdinand Schlatt)</li>
<li>Normdaten-Disambiguierung und Reconciliation auf Korpusdaten (supervised by Erik Körner and Felix Helfer)</li>
<li>Statistical Bootstrap Tests with Redundant Data (supervised by Maik Fröbe)</li>
<li>Mining Trigger Warnings from the Web and Social Media (supervised by Matti Wiegmann)</li>
</ul>
</li>
<li>Weimar
<ul>
<!-- add new thesis here -->
<li>Building an Image Generator for Arguments (supervised by Maximilian Heinrich)</li>
<li>From Schemes to Fallacies: A Deep Dive into Argument Classification (supervised by Maximilian Heinrich)</li>
<li>Dynamic Generation of Knowledge Graphs for Complex Academic Search Tasks (supervised by Maximilian Heinrich and Tim Gollub)</li>
<li>Information Extraction from Scientific PDFs (supervised by Tim Gollub)</li>
<li>Adding Contextual Awareness to LLM-based Story Generation (supervised by Tim Gollub)</li>
<li>Prompt Framing Effects on Large Language Model Subjectivity Judgements (supervised by Nailia Mirzakhmedova)</li>
<li>How Humans Detect Cloned Voices (supervised by Johannes Kiesel and Marcel Gohsen)</li>
<li>Automated Conversational Search Evaluation (supervised by Nailia Mirzakhmedova and Johannes Kiesel)</li>
<li>Retrieval Augmented Generation for Enhanced Access to Industrial Documentation (supervised by Tim Gollub)</li>
<li>Story Orchestration for Multi-Agent Collaboration for Automatic Story Generation (supervised by Marcel Gohsen)</li>
<li>Do Large Language Models Extrapolate Personas of Dialog Participants from Context? (supervised by Marcel Gohsen)</li>
<li>Developing a Teaching Assistant for Course Materials with Retrieval-Augmented Generation (supervised by Marcel Gohsen)</li>
<li>Crafting Multi-Modal Learning Experiences based on Course Materials (supervised by Marcel Gohsen)</li>
<!--<li>Information Extraction from Academic Mailing Lists (supervised by Tim Gollub, todo: move to completed thesis)</li>-->
<li>Topic Segmentation with Large Language Models (supervised by Johannes Kiesel)</li>
<li>Mining Linked Data on Web Scale (supervised by Nikolay Kolyada)</li>
<li>Efficient and Effective Neural Translation Language Model for Search (supervised by Harry Scells)</li>
<li>Rating the Degree of Search Engine Optimization of Websites (supervised by Janek Bevendorff)</li>
</ul>
</li>
</ul>
</div>
<h2><a id="resources"></a>Resources for Students</h2>
<ul>
<li><a href="for-students/completed-theses.html">Completed Theses</a></li>
<li><a href="https://webis.de/facilities.html?q=thesis">Thesis knowledge base</a></li>
<li><a href="https://webis.de/facilities.html">General Webis resources</a></li>
<li><a href="https://webis.de/lecturenotes.html?q=generic#lecturenotes-generic">Lecturenotes on scientific working</a></li>
</ul>
<h2><a id="vacancies"></a>Vacancies</h2>
<!--
<ul>
<li>
-->
Research position on Watermarking for Large Language Models at the Bauhaus-Universität Weimar
<p>
The Webis Group at the Bauhaus-Universität Weimar (<a href="https://weimar.webis.de">weimar.webis.de</a>) is offering a three-year research position in a joint BMBF project with the Fraunhofer IDMT and Artifact GmbH. Salary is based on the collective agreement for the public sector in Germany, TV-L 13, 100%. The engagement can start immediately, but we are also flexible if the start date of a suitable candidate is later this year. There is the possibility of further employment in our research group.
</p><p>
The offered position deals with innovations and current developments in the field of Text Watermarking and Large Language Models and is very attractive for PhD students or experienced postdocs interested in innovative and fundamental research in the field of Artificial Intelligence, Machine Learning, and Natural Language Processing. The offered position is considered as qualification position, i.e., for non-postdocs we actively support to do a PhD (Dr. rer. nat.).
</p><p>
Prospective candidates should have finished either a master or a PhD in computer science, mathematics, statistics or a related field with excellent or very good grades. Solid knowledge of mathematics and statistics is required for this position - as well as very good programming skills.
</p><p>
We are an experienced research group where team spirit and active collaboration are top priorities. We are looking for open-minded graduates, PhD students, or postdocs who want to develop both as researchers and as a person. The working language of our group is English; fluency in German is not required.
</p><p>
We are interested in increasing the proportion of women in computer science research and particularly welcome applications from suitably qualified women. We do not discriminate on the basis of religion, color, gender, age, or disability and are committed to a family-friendly recruitment policy.
</p><p>
Interested and qualified candidates are invited to submit their application by March 2nd to <a href="mailto:[email protected]">[email protected]</a>. The application (preferably as a single PDF file) should contain the following documents: a cover letter describing yourself and your interests, a detailed CV, high school diploma (Abitur), academic transcripts stating courses taken and grades earned, and a list of publications (if any).
</p>
<!--
</li>
</ul>
<p>
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.
<p>
The Webis Group is a tightly cooperating research network, formed by computer science chairs at the universities of
<a href="https://groningen.webis.de/">Groningen</a>,
<a href="https://hannover.webis.de/">Hannover</a>,
<a href="https://jena.webis.de/">Jena</a>,
<a href="https://kassel.webis.de/">Kassel</a>,
<a href="https://leipzig.webis.de/">Leipzig</a>, and
<a href="https://weimar.webis.de/">Weimar</a>.
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.
</p>
<p>
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.
</p>
<p>
-->
Benno Stein<br>
Bauhaus-Universität Weimar<br>
On behalf of the Webis group
</p>
<p>
Email: [email protected]<br>
Web: webis.de
</p>
</div>
</main>
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