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Field
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of mixed fixed-flexible transport networks? Job description The increase of public transport usage has clear potential in transforming our environment to be more liveable, sustainable and convenient. However
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urban design, environmental stressors (e.g. heat, air pollution, pollen), and social factors (e.g. safety, norms, networks) influence active lifestyles; develop and test physical activity and destination
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AI-driven solutions for sustainable, efficient, and collaborative port operations of the future. Job description European seaports must achieve net zero emission by 2050 and 55% emission reduction
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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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products and actinides such as uranium. This purification process is highly complex, involving multiple steps under extreme conditions - high temperatures and corrosive environments. Research focus: This PhD
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must achieve net zero emission by 2050 and 55% emission reduction (‘fit for 55’) by 2030 as agreed in the European Green Deal and comply with the FuelEU Maritime and EU Emissions Trading System
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. On the other hand, typical design cycles in industry still make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap
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arrangements perform in practice; how they allocate responsibilities and risks; and how they handle uncertainty, interdependencies, and the growing complexity of public tasks. The project focuses on core
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adoption. Tiny internal defects, process variability, and complex geometries can make quality assurance slow, expensive, or even impossible with traditional inspection methods. This PhD project, part of a
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with an overview of complex projects, you ensure continuity in recurring annual work. You are aware of the political, administrative, and societal context and communicate effectively, presenting results