PhD Position in Responsible AI in Software Engineering Education

The Center for Industrial Software (CIS) at the Maersk Mc-Kinney Møller Institute , University of Southern Denmark , invites applications for a three-year PhD position in Responsible AI in Software Engineering Education . The position is based at SDU’s campus in Sønderborg and is available from 1 March 2027 or as soon as possible thereafter. The position is funded by the Novo Nordisk Foundation and is part of PREPARE — Pedagogical Alignment for Responsible AI in Software Engineering Education , a joint project between SDU and the IT University of Copenhagen (ITU). CIS is a young but fast-growing unit whose research groups span cybersecurity, artificial intelligence, embedded systems, and software engineering. Our students and staff come from Denmark, the rest of the EU, and beyond, and our working language is English. About the position Generative AI has arrived in our classrooms faster than our pedagogy has adapted to it. Students increasingly delegate the very things we are trying to teach them — verification, trade-off reasoning, judgment, accountability — to tools whose reasoning they cannot inspect. Most institutional responses so far have been restrictions or isolated policies, and neither addresses the underlying problem. This project takes the opposite route: if AI is here to stay in software engineering practice, responsible AI use should be deliberately taught, practiced, and assessed. This is a unique position in that research and its consequences sit in the same place. You will not be studying a distant phenomenon and writing it up; you will be running studies in live courses, designing interventions from what you find, and seeing them change how software engineering is taught. If you see yourself as someone who wants to help our discipline navigate the AI disruption rather than wait for it to settle, this is that opportunity. Responsibility and opportunities Concretely, you can expect to: Design and conduct empirical studies of how software engineering students generally use generative AI — how they justify it, what they delegate to it, and where their agency is preserved or surrendered. Translate those findings into agency artifacts, practicum activities, and assessment designs that can be used by real instructors in real courses. Co-develop and evaluate self-learning components, and contribute to alignment work on intended learning outcomes, activities, and assessment together with the ITU stream. Work directly with the head of programs and...

Summary and match are AI-generated; verify details on the original posting.

Listed via EURES. All sources