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! Job description This 4-year fully funded PhD position is part of the ERC Consolidator project “Systemic physical climate risk in complex adaptive economies” (SPHINX). The SPHINX-research program is made
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of the way. With 3,200 m² of state-of-the-art lab facilities, housed in a museum with more than 40 million natural history objects, dedicated mentorship, and access to our broad international network
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of buildings. This presents many opportunities, but also requires careful planning and operation to deal with emerging challenges such as network congestion. Recently, positive energy districts (PEDs), i.e
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sustainable battery for thermal storage. The idea is to combine waxes obtained through pyrolysis of plastic waste streams, with ultra-conductive graphene networks, i.e., nanometer sized carbon platelets
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Your job Do you want to understand how ecosystems function? Do you have good knowledge of Dutch Flora and experience in writing Dutch reports? Are you eager to explore how a complex interplay of
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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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. This simple unit is limiting the learning capabilities of recurrent neural network models in tasks characterized by multi-timescale and long-range temporal dependencies. To implement multi-scale adaptation, in
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efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize
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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