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complex systems, will you help us develop a new generation of road traffic prediction methods? Job description Road traffic is a highly complex dynamic system. Minor disruptions can lead to major delays
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research the traffic-bounded pollution in Barcelona under the TRACE work frame (Traffic-Related Aerosol Characterization and Emissions). The focus will be to characterize the urban traffic aerosol with
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to conduct research on drone traffic control systems (UTM/U-Space systems), specifically to develop advanced services that automate flight authorization and negotiation with operators and pilots
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interfaces to share intermediate data for distributed training and processing, generating large traffic flows. Low and deterministic latency will be required for specific application in data centre for AI
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routes entangled photons in the presence of classical telecom traffic in multi-node quantum networks. Information Efficient distribution and routing of entanglement are indispensable for quantum‑secure
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technology for decarbonized mobility. However, their safe and sustainable deployment in dense urban traffic remains challenging due to uncertain vehicle–battery dynamics, sensor or actuator faults, critical
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these technologies as competing alternatives, this project explores how they can operate as complementary technologies within a unified hybrid network, allowing traffic to be intelligently routed over the most
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management
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to increasing traffic loads and environmental effects, efficient methods for monitoring their condition become essential. Traditional inspection approaches can be costly, time-consuming, and limited in spatial
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel