Below, you will find current topics that can be worked in the context of a , a Bachelor’s or a Master’s Thesis. The context indicates the scope of the work, and the keywords give you further information about the topic and its domain.
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Managing distressed patients in clinical environments is a challenging yet critical skill for healthcare professionals. Patients exhibit diverse emotional responses—ranging from anxiety and shyness to outright resistance-making it essential for clinicians to adapt their approach. Traditional training methods often lack the realism needed to prepare professionals for these high-stakes interactions.
The Apertus project from EPFL, ETH, focuses on developing a Swiss-based Large Language Model (LLM) with strong multilingual capabilities. While the model performs competitively on general language tasks, it currently struggles with structured programming challenges such as:
Modern LLMs are increasingly enhanced with the ability to interact with external tools such as:
Modern AI coding tools allow developers and agents to generate hundreds of lines of code in seconds. However, our standard processes for managing software—like Git feature branches and pull requests—were created over two decades ago when writing code by hand was a slow process. Because code generation is now nearly instant, the main bottleneck in software engineering has shifted from writing code to reviewing, testing, and integrating it.
AI coding assistants are now widely used in professional software development. The prompts developers write, the responses they receive, the subsequent edits they make, and the rework they perform before committing code remain almost entirely invisible for in-depth analysis. Without access to the full interaction between developer intent (i.e., a prompt) and AI output, it is not possible to study whether AI-generated code actually addresses what the developer needed.