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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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where there is no clear or well-defined solution. SSM emphasizes understanding problems from multiple stakeholders' perspectives, facilitating the exploration of different viewpoints and fostering a
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conducted through surveys targeting a diverse group of stakeholders involved in rural entrepreneurship policies across multiple levels in order to identify success factors, best practices, and the ways
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copy of the master’s thesis if finished and available Certified copies of academic diplomas and certificates. (i.e. Diploma, transcript. Diploma supplement for both bachelor and master). Diplomas
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to timetables and service locations while considering requirements of various personnel and special requests during operations based on specific train unit conditions. This requires multiple-criteria decision
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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flood extents under different storm surge scenarios, as determined through high-fidelity CFD-DEM simulations? - What is the optimal spatial arrangement (single/multiple lines, angle of incidence) of PBs
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sensing (e.g., PlanetScope, Sentinel-1), advanced numerical modelling (HEC-RAS, Delft-FM), and targeted field surveys to map mining intensity, simulate channel adjustment, and assess changing flood hazards
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GPR and EMI imaging methods at multiple scales to enhance our understanding of the soil–root system Designing and implementing novel inversion algorithms for GPR and EMI data Identifying links between
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current and future disease risk and burden across multiple pathogens with environment- and climate-sensitivity. Your tasks: Building a diverse set of models for short-term predictions and the long-term