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engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and
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stakeholder analysis, using methods such as literature review, qualitative interviews, and network analysis to identify key actors, trust flows, and governance dynamics. Building on these insights and those
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our external partners, and act as an ambassador towards the mass spectrometry community on our behalf. Join an expert team performing cutting-edge research, ranging from technological development and
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the local electricity system, while acquiring academic perspectives? Information This position is dual fold and has both a teaching and a research related aspect. Power networks are critical
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for when and how AI agents should intervene, how they represent and communicate data, and how they adapt to evolving group dynamics over time. A specific interest is group decision-making and sensemaking
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development of simplified continuum-based models, enabling fast assessments across large quay wall networks. This position is part of the Bridge and Quay Walls (Bruggen en Kademuren) programme of
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value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions
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-personalised services - as Large Language Models become widely accessible, they're reshaping how we live, work, play and connect. This rapid shift sparks big questions: Whose norms and values shape this AI
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-informed ML Experience working with Linux and HPC environments is an advantage. Strong communication skills and excellent proficiency in English. You enjoy working in an international, interdisciplinary team
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, or materials informatics. Familiarity with explainable AI or counterfactual explanation methods. Experience with molecular dynamics data, graph neural networks, or multi-component system modelling. Track record