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Processes (CLARA). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in
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interaction? Which parameters and mechanisms govern the response of a lined tunnel? How can the complex, time-dependent behaviour of deep plastic clay and segmented concrete lining be captured in models
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-disciplinary domain. Specific research topics to apply to bioacoustics might include: low-footprint machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods
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interest in metal–impurity interactions, interfacial phenomena and its commitment to computation-guided design for green and circular steel production. You will collaborate closely with researchers from
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infiltration (LCI) in steels and the inhibitory role of silicon aligns with the team's broader interest in metal–impurity interactions, interfacial phenomena and its commitment to computation-guided design for
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, you will: Contribute to defining metrics and indicators across spatial (schoolyard, street, neighborhood, city) and temporal (daily, weekly, seasonal) scales, combining sensor-based data with human
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, seasonal) scales, combining sensor-based data with human-centered behavioral mapping and on-site observation. Help develop harmonized data collection, integration, and analysis protocols ensuring consistency
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+ Institute for Nanotechnology. The project offers a combination of hands-on experimental work, data analysis, physical interpretation and close interaction with industrial partners. You will contribute to a