Workshop series
Workshop series
© Uni Münster – Web und Design

Target group: doctoral and postdoctoral researchers

GenAI Lab is a practice-oriented workshop series designed for doctoral and postdoctoral researchers who want to explore the potential of Generative AI (GenAI) technology in their academic work. Each workshop focuses on a specific area and includes practical examples or case studies applicable across disciplines. Participants will engage in interactive activities, hands-on exercises (including prompting techniques), and reflective discussions.

This training is suitable for:

  • Curious beginners with little to no prior knowledge or hands-on experience who wish to make their research activities more efficient, impactful, and innovative using GenAI tools.
  • Basic practitioners with some knowledge and application experience who are looking for deeper insights into specific GenAI tools and want to improve their use without going into too much technical detail.

Please review the individual workshop descriptions to check whether a given session matches your current level of proficiency with generative AI tools.

Requirements: Participation is open to those who have secured their spot and belong to the target group.

Die Sprache des Workshop-Titels gibt an, in welcher Sprache der Workshop durchgeführt wird. // The language of the workshop title indicates the language in which the workshop will be delivered.

  • Thu, 21 Jan 2027, 14:00–17:00 / Get acquainted with ChatGPT: From understanding to using

    Target group: An elementary understanding of how GenAI algorithms work facilitates practical usage and adherence to good scientific practice. This introductory workshop is designed for participants with no prior experience in machine learning  (ML) and bridges the gap between foundational knowledge and hands-on application.

    In the first part, Demystifying ‘Artificial Intelligence’: What It Means for a Machine to Learn, participants will discover how algorithms learn from data, how ML differs fundamentally from human learning, and why anthropomorphizations are so often misleading. In the second part, The Machinery of Large Language Models (LLMs), the workshop sharpens its focus: participants will learn how text is represented for ML algorithms, how transformers are constructed and trained, and how they generate meaningful text. Finally, in the third part, Putting Knowledge into Practice, participants will deepen their understanding of how LLMs can be used appropriately through selected examples.

    Objectives:

    • Acquire essential key terms (e.g. AI, machine learning, deep learning) and background information useful throughout the workshop series (and beyond)
    • Learn how text is represented and processed by machine learning models
    • Understand the structure and training processes behind transformers
    • Gain introductory knowledge of other generative AI models
    • Gain hands-on experience with LLM usage

    Facilitators: Dr Oliver Kamps, Dr Katrin Schmietendorf (Center for Data Science and Complexity (CDSC))
    Venue: Zoom

  • Mon, 1 Feb 2027, 14:00–17:00 / Generative AI in scientific practice? 

    Target group: doctoral and postdoctoral researchers

    Ethical concerns about GenAI have given rise to broad discussions on its implications for good scientific practice. Part I of the workshop differentiates between various uses of GenAI in scientific practice to understand different levels of risk. Part II addresses matters of cultural bias and infrastructural power as sustainability aspects of GenAI relating to matters of scientific freedom and epistemic injustices. Next to condensed knowledge transfer, we rely on interactive exercises throughout the workshop, exploring prompt-engineering practices, bias-testing tools, and the capabilities of GenAI applications.

    Objectives:

    • Differentiate uses of GenAI in scientific practice

    • Gain insights into current discussions on the use of GenAI in science and research

    • Understand epistemic risks associated with GenAI

    • Reflect on transparency and sustainability of GenAI in relation to scientific accountability

    Facilitators: Dr Anne Mollen (FB 06, ifk), Dr Iva Ognjanovic (CERes)
    Venue: Zoom

  • Tue, 9 Feb 2027, 12:00–16:00 / Using GenAI when producing academic content in English 

    Target group: This workshop is for doctoral and postdoctoral researchers with a working knowledge of English who want to use English more confidently in academic contexts.

    English is the language of academic research, teaching, presentation and publication, and you are often expected to present and write fluently and appropriately in English. This can be a daunting task for a non-native speaker. In this workshop, you will be introduced to generative AI tools that can help and support you in building these skills and make your writing process more efficient. We will practice revising texts with specific AI tools, ideally using your own texts, so participants are encouraged to come prepared with a draft of a small and specific writing project they are currently working on (see below). We will also explore AI tools and strategies for creating and revising slides, improving oral and aural fluency, and tailoring texts to different audiences according to Anglo-American academic conventions.

    Objectives:

    • Acquire specific techniques for efficiently and effectively revising academic texts (either written in or translated into English) with the help of AI tools

    • Discover AI tools for improving written, oral and aural skills in various academic contexts

    • Gain insight into how to adapt texts for different English academic contexts with the help of AI tools

    • Understand the advantages and limitations of using AI tools for creating or revising output in academic English

    Requirements: Participants must come prepared with a (partial) draft of an unpublished text, e.g., a grant application, article, thesis chapter/section or conference paper.

    Facilitators: Dr Julie Davies (Sprachenzentrum)
    Venue: Zoom

  • Fri, 23 Apr 2027, 09:00–13:00 / Using GenAI in the literature review process and analysis

    Target group: This workshop is designed for doctoral and postdoctoral researchers in all subject areas who aim to enhance their structural and systematic literature review skills by integrating generative AI tools. Prior experience in literature reviews is helpful but not required. Beginners with a curiosity for AI applications are welcome.

    Participants will explore the capabilities and limitations of GenAI in supporting processes of literature reviews, covering key stages of the process – from defining research questions to extracting and synthesizing information. The session will introduce practical AI tools and prompts to assist with defining text corpora, generating research questions, developing search strings for databases, and synthesizing results. Hands-on exercises will provide participants with opportunities to experiment with these tools and prompts, allowing them to integrate AI into various stages of their literature review workflow. 

    Objectives:

    • Understand the structure and workflow of literature reviews and how AI can enhance that process

    • Use AI in the formulation of research questions, search strings, and the exploration of innovative themes

    • Use AI in the quality assessment, data extraction, and synthesis of findings

    • Discover strategies for leveraging AI in coding and presenting research results

    Facilitators: Dr Nils Beese (ULB), Dr Filipe Pessoa (CIT)
    Venue: CERes, Schlossplatz 6, room 001

  • Sommer 2027 / Vibecoding

    TBA

    Veranstaltungsleitung: Dr. Daniela Feistauer (FB 07)
    Ort: CERes, Schlossplatz 6, Raum 001

  • Sommer 2027 / GKI in der geisteswissenschaftlichen Forschungsmethodik: Qualitative Daten

    Zielgruppe: Der Workshop richtet sich an Doktorand:innen und Postdoktorand:innen in den Geisteswissenschaften, die in ihrer Forschung qualitative Daten analysieren und dabei generative KI (GKI) als unterstützendes Werkzeug einsetzen möchten.

    Wie kann generative KI die Analyse qualitativer Daten – z. B. Interviews, historische Quellen, literarische Texte, ethnografische Notizen – in den Geisteswissenschaften unterstützen? Dieser Workshop bietet eine Einführung in GKI-Tools und zeigt praxisorientiert, wie Daten vorbereitet, analysiert und interpretiert werden können. Es wird aber auch über den Einsatz reflektiert und es werden die Möglichkeiten und Grenzen dieser Technologien für die Forschung erkundet.

    Ziele:

    • Verständnis der Grundlagen von generativer KI (GKI) und ihrer Funktionsweise vor dem Hintergrund geisteswissenschaftlicher Forschung
    • Fähigkeit, qualitative Daten methodisch für die Analyse mit GKI aufzubereiten
    • Beispiele für die Anwendung von KI-Tools zur Analyse und Interpretation qualitativer Daten
    • Kritische Reflexion über Chancen, Grenzen und ethische Aspekte von GKI

    Veranstaltungsleitung: Ludger Hiepel (FB 02, IBET)
    Ort: Zoom

  • Sommer 2027 / GenAI in research methodology: Quantitative data

    Target group: This workshop is aimed at doctoral and postdoctoral researchers who may have played around a bit with ChatGPT or other GenAI programmes, but otherwise have little to no experience in applying GenAI to work with quantitative data.

    After an overview of the capabilities and limitations of GenAI for data analysis, participants will explore data cleansing and pre-processing, exploratory and statistical analysis, data visualization, and reporting with GenAI. They will have the opportunity to test strategies and specific prompts using provided datasets or datasets of particular interest to them.

    Objectives:

    • Acquire background information on data analysis with GenAI
    • Learn about capabilities and limitations of GenAI in this context
    • Explore specific strategies for using GenAI for data ‘wrangling’, exploration, visualization and utilization
    • Gain hands-on experience with GenAI for these purposes
    • Develop a sense for independent results validation

    Facilitators: Dr Martin Korth (IVV Naturwissenschaften, NWZ), Dr Filipe Pessoa (CIT), Dr Rodolphe Dewarrat (University of Münster, CRIS.NRW)
    Venue: CERes, Schlossplatz 6, room 001

GenAI Lab Team and acknowledgements
GenAI Lab Team and acknowledgements

The GenAI Lab is a collaborative initiative bringing together expertise from across the University of Münster.

Current development and delivery: 
Dr Nils Beese (ULB), Dr Julie Davies (Sprachenzentrum), Dr Daniela Feistauer (FB09), Ludger Hiepel (FB 02, IBET), Dr Oliver Kamps (CDSC), Dr Martin Korth (IVV Naturwissenschaften, NWZ), Dr Anne Mollen (FB06, ifk), Dr Iva Ognjanovic (CERes–initiative lead), Dr Filipe Pessoa (CIT), Dr Katrin Schmietendorf (CDSC).

Initial conceptualisation and previous contributions:
We would particularly like to acknowledge colleagues who contributed to the initial conceptualisation and earlier development and delivery of the GenAI Lab: Friedrich Bach, Dr Rodolphe Dewarrat, Dr Jan-Martin Geiger, Heike Mersmann-Hoffmann, Dr Stefan Roski, and Jonathan Wandscheer. Our heartfelt thanks goes to Benedikt Lennartz and Prof. Dr Benjamin Risse for their valuable insights and support during the initial conceptualisation phase.

Registration

If you would like to participate in this event and it is already marked as fully booked, you are welcome to join the waiting list. It often happens that registered participants cancel their attendance, which creates available spots. Free spots are allocated in the order of waiting list registrations. If spots become available within 72 hours before the event starts, we will notify several registrants simultaneously. These spots will then be allocated on a 'first come, first served' basis.