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who would revel in pushing the boundaries of technology. Context and Challenge The airtightness of a building is a critical parameter in determining energy efficiency, ventilation adequacy, and overall
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. We would therefore strongly encourage qualified women to apply for the position. Your tasks develop surrogate models to approximate high-fidelity phase field simulations, incorporating physics-informed
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autonomous by embedding machine learning algorithms to search through different reaction parameters Person Specification Candidates should have been awarded, or expect to achieve, EITHER: A Bachelors degree in
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qualified women to apply for the position. Your tasks develop surrogate models to approximate high-fidelity phase field simulations, incorporating physics-informed loss functions to enhance model accuracy and
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these constraints into the training objective, complicating model training. This project aims to leverage advancements in computer vision, particularly in implicit neural representations, to embed priors in neural
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electrical and thermal modelling, parameter/state estimation, diagnostics/prognostics and system control. It is difficult to be unaware of the efforts going into the development of low-carbon alternatives
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Muscle Dynamics: Approximate muscles as “cables” with Hill model dynamics within the SOFA framework. Simulate muscle contraction patterns and their interaction with the larva’s environment, including
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, materials and their condition. Second, simulation of pulse propagation in cables with variable parameters quantified in experimental studies. Third, utilizing signal processing and machine learning to develop
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generation of social, computer-based, and cyber-physical systems that make a substantial contribution to the welfare of our society, for example, via embodied intelligent systems that are tailored to users
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conducted with different composite material parameters (thickness, lay-up, and types of fibre and matrix) in order to develop optimised FML composites with high durability and fatigue life. The expected