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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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scenarios. Your research will map multilevel governance structures and you will co‑create mitigation strategies through participatory workshops. You will model farmers’ adaptation behaviour using agent‑based
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from this PhD project into an agent-based model. This model will be developed by other PhDs in the project team and simulates household adaptation behaviour over time in global flood-prone regions
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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governance, simulation and modelling (agent-based modelling, discrete-event simulation, network models), data modelling / interoperability (e.g., ontologies/semantics, data standards, API-based exchange
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that entrepreneurs face when they want to produce life-sustaining goods in a regenerative manner. Regenerative practices require business models supported by an organizational design structure that focus on restoring