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Field
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various components of the hydrological cycle (such as precipitation, evapotranspiration, runoff, and infiltration), forms the core of traditional hydrological modeling approaches. Although powerful
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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of rural communities toward resilient, inclusive and climate-smart business models. The focus of this PhD will be on modelling and assessing the sustainability and macroeconomic implications
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and develop their individual
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable
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, including weather, climate and sea state forecasting. The Air-Sea Fluxes group at the Institute of Coastal Ocean Dynamics conducts laboratory- and field-based research, by developing and deploying unique
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teacher-student synchronization. However, this synchronization necessitates an exact student model, making the ACT often inexact and susceptible to uncertainty and variability. The project will aim