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at the HOME RATE ONLY. International students and EU students without Settled Status will need to cover the difference between the home and the international fee rates. Visas and associated costs are not
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. Project description Data-driven mathematical and statistical models are increasingly used in life science research and healthcare. Quantifying the uncertainty associated with these models is crucial
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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
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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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LiDAR based foundation models to radar, as well as the development of multimodal foundation models incorporating radar. A further challenge is how different radar representations and sensor configurations
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different radar representations and sensor configurations can be accommodated within a general foundation model framework, and to what extent a common model can generalize across them. Research directions may
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noisy, partially mediated observations. These models will incorporate biologically informed structure, including protein-protein interaction networks derived from data-driven sources such as protein
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. The project will bridge wind farm aerodynamics, advanced control, system identification, filtering, and data-driven modelling, with a strong emphasis on combining physical knowledge with measurements rather
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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software developers to integrate data‑driven models with mechanistic or physics‑based models and domain expertise; showing thought leadership on applying data & AI-solutions in the food & biobased domain