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through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data
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approached as a situated process emerging through the interaction of data, models, professional judgement, and organisational context. Depending on your interests and empirical setting, the project will
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change in crisis responses over the long term. You will combine historical source research with digital methods to analyse large-scale corpora of textual and/or visual sources. You will work with existing
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research. The cluster currently has 10 faculty members, whose research interests include computational geometry and topology, graph and FPT algorithms, algorithms for massive data, geo-visualization, and
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indicators and neurotransmitter sensors (fiber photometry), opto- and chemogenetics, engram visualization and mouse behavior. By joining our team at the University of Amsterdam, you will contribute to a deeper
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., PsychoPy, E-Prime, Gorilla, Presentation). Hands-on experience in data visualization, data analysis, and programming in R and/or Python. Experience in, and aptitude for, complex statistical modelling (inc
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to shape how humans and AI interact in high-stakes contexts. You will help define how AI can support—not replace—human judgment, ensuring that technology empowers rather than undermines trust and autonomy
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interact in high-stakes contexts. You will help define how AI can support—not replace—human judgment, ensuring that technology empowers rather than undermines trust and autonomy. You will be part of
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user-interaction tests in target groups and record and analyse psychophysiological measures of autonomic nervous system balance during acute stress such as heart rate variability. You will help optimise
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are promoting more resource intensive lifestyles under banners of health, safety and pleasance. While the Human-Computer Interaction (HCI) community shaping smart technologies is still coming to terms with its