66 modelling-complexity-geocomputation PhD positions at Technical University of Denmark in Denmark
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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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machine learning techniques to develop local graph representation models, which will be aggregated globally to enhance their predictive power and translational relevance, all while maintaining strict data
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batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery
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of extracellular matrix (ECM) remodelling during wound healing. Yet, many proteolytic processes remain uncharacterized due to the complexity of the ECM and limitations in current detection strategies. Advances in
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modeling of complex information systems, and SDU and the Royal Danish Defence College’s established intelligence studies and practice. By introducing computational modeling to traditional intelligence
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at the intersection of machine learning and operations research to design and operate the water networks of future sustainable societies. Water networks are characterized by their complex topologies and highly non
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. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process & microstructure with