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Field
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-specific networks driving the cellular responses. Given the complexity and dynamic state of signaling networks, the current understanding of their constituents and how they are spatiotemporally regulated in
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neuron electrophysiology as well as complex network dynamics in the context of specific perturbations. You will use these data to map the disease in terms of electrophysiological dynamics and stratify
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world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and
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, scheduling and operations of complex systems. This topic will pursue integrated, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and
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neuron electrophysiology as well as complex network dynamics in the context of specific perturbations. You will use these data to map the disease in terms of electrophysiological dynamics and stratify
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of the complex networks that the project uncovers. They will be expected to carry out high-level research related to the aims of the research project, submitting publications regularly to refereed journals and
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to modeling interactions between physical and digital infrastructures to enhance energy management, transportation networks, and urban sustainability. Key Responsibilities • Design and implement digital
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Description: The specialist in urban energy networks is responsible for the design, analysis, and optimization of energy networks in urban environments. We are seeking a dynamic and motivated specialist to join
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the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity of relationships between the nodes of networks with a mul-tidimensional nature
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate