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knowledge for sustainable formulation design. Using different data-driven feature representations, AI foundation models will generate chemical embeddings to predict key physicochemical properties. Coupled
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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will be hosted in the Department of Mechanical Engineering, where Prof. Balabani leads an experimental fluid mechanics group. Her work includes advanced microfluidic modelling of thrombosis (“thrombosis
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will be hosted in the Department of Mechanical Engineering, where Prof. Balabani leads an experimental fluid mechanics group. Her work includes advanced microfluidic modelling of thrombosis (“thrombosis
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welcome motivated students with a strong background in engineering or science, such as physics, mathematics, computer science, or related disciplines. Skills in mathematics, computational modelling
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mechanism. The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all, the traditional
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within trusted digital environments. Their research focuses on ontology-driven conceptual modelling, FAIR data stewardship, and model-driven system/service engineering, dealing with data-driven services
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breaking towards achieving silent aircraft design? Applications are invited for one funded 3.5-year PhD studentship for the project titled ”Data-driven modelling and control of turbulence-generated noise” in
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
for automated, data-driven diagnostics, integrating AI with high-resolution imaging and sensing offers a transformative solution. AI models can learn to recognize subtle damage patterns, enabling faster, more
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health management (IVHM) system that leads to enhance safety, reliability, maintainability and readiness. Generally, prognostics models can be broadly categorised into experience-based models, data-driven