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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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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 retrainable ML models, LLMs
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industry at both national and international levels, with applications in the transport and manufacturing sectors. Work tasks mainly consist of research, data collection and analysis, writing scientific
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the following programming languages/environments: Python, PyTorch (or similar), and experience with LLM frameworks (e.g., Hugging Face, LangChain) or data analysis tools. Hold a Master of Engineering or
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in one or more of the following programming languages/environments: Python, PyTorch (or similar), and experience with LLM frameworks (e.g., Hugging Face, LangChain) or data analysis tools. Hold a
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collaboration with industry at both national and international levels, with applications in the transport and manufacturing sectors. Work tasks mainly consist of research, data collection and analysis, writing
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of autonomous systems, including coordinated mission planning. The position also includes tasks such as planning and implementation of experiments, construction of experimental setups, data analysis, and