진학프로석·박사 채용 접수 플랫폼

The Department of Software Engineering consists of about 50 researchers and teachers from 20 countries. Our tradition in software engineering traces back to 1990 when we pioneered Sweden’s first academic education in the software engineering area in cooperation with Ericsson. The department’s research and education environment, SERL Sweden – the Software Engineering Research and Education Lab, has since then expanded into a world-leading research environment in empirical software engineering.

Work description

You are expected to explore both software architecture and software design in the era of artificial intelligence, addressing both how AI can support engineering practices (AI4SE) and how the integration of AI components transforms the nature of software systems (SE4AI). From an architectural perspective, the research investigates how the inclusion of AI elements—such as LLMs challenges conventional architectural styles, architecture evaluation methods, and governance models, requiring new approaches for modularity, decoupling, versioning, deployment, and lifecycle management. At the same time, the project delves into software design concerns, focusing on the internal structure and evolution of AI-enabled components themselves, including the design of retrainable pipelines, model-wrapping services, LLM prompting logic, data pre/post-processing components, and explainability hooks.

As a postdoctoral researcher, you will be a key member of the research team and work closely with both industry and academic partners. Your work will include:

• • Investigate how the integration of AI components such as LLMs, retrainable ML models, and RAG modules impacts software architecture, including implications for modularity, lifecycle management, and architectural evaluation methods.
• • Study how AI alters software design principles and patterns, focusing on the internal structure and evolution of AI-enabled components, including prompting logic, data transformation flows, retraining mechanisms, and explainability scaffolding.
• • Analyze the interaction between architectural decisions and design-level tradeoffs in AI-intensive systems, addressing issues such as non-determinism, continuous data dependencies, testability, and maintainability.
• • Different strategies for evaluating architectures, including but not limited to simulation, best-practice pattern evaluations and testing, inventing and utilizing evidence and measurements to evaluate and compare architectural solutions.
• • Publishing research findings in top-tier conferences and journals, and contributing to industrially relevant research in software engineering.

For this position, we are looking for a candidate with a background in software engineering, software architectures, data analysis, and artificial intelligence.

Up to 20% of the total work time may be related to other tasks than research, such as teaching and supervision of doctoral students. The applicant is expected to actively participate in the department’s research and educational activities.