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learning models—alters the way software systems evolve (SE4AI). A strong focus will be on the post-deployment lifecycle of ML components, including drift detection, model decay, retraining triggers, and
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to assess and ensure the safe, predictable, and transparent behavior of systems incorporating machine learning and generative models. Design and prototype frameworks or tools that support systematic V&V
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retrainable pipelines, model-wrapping services, LLM prompting logic, data pre/post-processing components, and explainability hooks. The research will examine how design patterns, principles, and quality
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description You are expected to investigate how software development organizations can leverage internal process metrics and external usage or stakeholder data to improve software quality and delivery
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and developing (generative) AI to improve software development processes as well as the quality of software artefacts (e.g., code or designs). We are, therefore, looking for a candidate with experience
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, computer graphics and visualization, and cryptography and computer security. There are a number of research projects in all areas. Work description The position includes research and teaching in