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on these comparisons, you will create agent-based models (ABMs) that define interaction rules based on observed similarities and differences in events [4], with a focus on the specific role of individual differences
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or social robots; trust and reliance on conversational agents designed to be charming and disarming; so-called "dark patterns" and manipulative tactics in the user interfaces of a range of technologies, from
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generation of experts in ingestible medical technologies. These orally delivered, minimally invasive devices are designed to traverse the gastrointestinal (GI) tract, enabling diagnostics, therapy, sampling
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as Physical Geography, Geology, or Engineering Geology, with a numerical background in earth surface processes. Field experience and skills in GIS and programming skills are necessary. The scholarship
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, environmental data science, or a closely related STEM discipline Demonstrated expertise in urban spatial data analytics, with proficiency in GIS software (e.g. QGIS, ArcGIS) and geospatial methods Experience in
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, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data, disambiguate historical agents, and contribute
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training in field work techniques, ecological modelling and GIS will be provided by an interdisciplinary supervisor team. Funding duration – 4 years Funding Comment This scholarship covers the full cost
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powerful AI companies, in democratic security, and analysis of the development of new forms of agentic and adversarial AI that could undermine democracy. The candidate will be based in Lancaster University’s
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical