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optimization, machine learning, control theory, or stochastic modeling. Crucially, the ideal candidate must have a proven track record of viewing civil infrastructure through a holistic, interconnected
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control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line on the theory
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European Magnetism Association EMA | Nijmegen, Provincie Gelderland | Netherlands | about 2 months ago
Home > JOBS Ultrafast Magnetism in Frustrated Materials [ All offers ] 2026-07-24 | PhD Lab/Company : HFML-FELIX Location : Nijmegen, Netherlands Yearly income : https://www.nwo-i.nl/en/vacancies/phd
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the analysis of nonlinear phenomena in dynamical networks. These phenomena include tipping points and adaptation across multiple timescales, with applications in restoration ecology. Ecosystems are an
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actions in distributed power grid systems at INSA Lyon (France). This thesis is co-supervized by LAAS-CNRS. Future energy networks will increasingly rely on interconnected and distributed
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intellectually stimulating environment to enable high quality work in strategic directions that are of significant impact to industry, science and technology. For more details, please view https
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project The PRONTO project aims at modeling public transport networks with stochastic partial differential equations. The project is joint between research groups in mathematics and automatic control
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- Control of Communication networks - Markovian Processes - Network Based Localisation / Radio based connectivity - Adaptive bandwidth - Mesh networking - Wireless Sensor Networks - Edge Computing
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firewalls, intrusion detection systems, secure virtual private networks (VPNs), cloud security, and other supporting solutions. The Network Security Engineer assists with compliance with applicable
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control methods such as Model Predictive Control (MPC) are often limited by discrepancies between the nominal model and the actual system behavior. The objective of this thesis is to improve model