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into high-purity powders. Using mechanochemical processing, you will investigate and control phase formation, particle size distribution, morphology, and flowability. You will then establish additive
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. You will use human in vitro models, including astrocytes and brain organoids generated from induced pluripotent stem cells (iPSCs) of people with MLC and healthy controls. You will investigate disease
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pioneers challenged the institutional and normative foundations of public service broadcasting. These actors offered a stark critique of government control over media based on cultural cohesion
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, the effectiveness of Helix—and other advanced wake-mixing strategies—strongly depends on the accuracy of the wind farm models used to design and evaluate these control strategies. Improving the predictive capability
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to science, engineering and society. You will focus on optimization-based, data-driven and partially model-based control methods. You will have access to a strong research network and a broad range of
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support the development of safer flood defence systems and more reliable flood risk assessments. Your responsibilities As a PhD researcher, you will: Develop continuum-based two-phase models to predict
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: Develop continuum-based two-phase models to predict internal erosion and pipe progression in clay-sand layered dikes. Derive constitutive modelling approaches from high-fidelity DNS-DEM data generated
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PhD position to research novel fast controlled photonic integrated switches for low latency and highly scalable AI compute clusters. The electro-optical communications (ECO) group in the Faculty
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of dynamical systems, control of complex and uncertain systems, motion control for high-tech systems, model predictive, networked, supervisory, neuromorphic, and learning-based control, cyber-physical systems
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biogeochemical processes that govern their behaviour. Job description The PhD candidate will develop and analyse new process-based mathematical models to improve our understanding and predictive capability