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Field
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), we aim to close this gap, by developing AI models and tools for tabular data, to help organizations, of any size, domain, and level of data literacy, get insights from structured data, efficiently
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with colleagues from RWTH Aachen and visit their facilities. The aim in this PhD project is to conceptualize and model the asynchronous architecture for future power grids. As we depart away from
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will also use finite volume-based numerical simulations and (if desired by the student) mathematical modelling. You will work alongside other researchers within the Fluid Dynamics Research Centre
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to reduce AC losses and boost power density. Today's modelling tools are not yet equipped to fully explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers
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well as across the full life cycle. Expected Outcomes Development of aircraft energy consumption model(s) Adaptation and application of the model for different fuels and/or propulsion systems, and for different
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approach is the use of digital twins—virtual models that replicate a patient’s heart using mathematical equations describing cardiac physiology and clinical data (e.g., ECGs, MRI scans). However, creating
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research. The project will involve computational modelling using physics- and machine learning-based methods and would suit a top student with a background in Physics, Engineering, Mathematics or similar
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model of the patients’ condition is required. This PhD will investigate how knowledge models can be built and maintained for healthcare applications. The project will explore the use of combining
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. Examples of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world
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. We will explore both experimental techniques as well as computational models to provide feedback to design higher efficient devices. The materials characterisation will include XRD, SEM/TEM, XPS, and